Relevant bibliographies by topics / Detr

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  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
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Academic literature on the topic 'Detr'

Author: Grafiati
Published: 1 March 2025

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Journal articles on the topic "Detr"

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Wang, Runqi, Huixin Sun, Linlin Yang, Shaohui Lin, Chuanjian Liu, Yan Gao, Yao Hu, and Baochang Zhang. "AQ-DETR: Low-Bit Quantized Detection Transformer with Auxiliary Queries." Proceedings of the AAAI Conference on Artificial Intelligence 38, no. 14 (March 24, 2024): 15598–606. http://dx.doi.org/10.1609/aaai.v38i14.29487.

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DEtection TRansformer (DETR)-based models have achieved remarkable performance. However, they are accompanied by a large computation overhead cost, which significantly prevents their applications on resource-limited devices. Prior arts attempt to reduce the computational burden of DETR using low-bit quantization, while these methods sacrifice a severe significant performance on weight-activation-attention low-bit quantization. We observe that the number of matching queries and positive samples affect much on the representation capacity of queries in DETR, while quantifying queries of DETR further reduces its representational capacity, thus leading to a severe performance drop. We introduce a new quantization strategy based on Auxiliary Queries for DETR (AQ-DETR), aiming to enhance the capacity of quantized queries. In addition, a layer-by-layer distillation is proposed to reduce the quantization error between quantized attention and full-precision counterpart. Through our extensive experiments on large-scale open datasets, the performance of the 4-bit quantization of DETR and Deformable DETR models is comparable to full-precision counterparts.
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Gu, Yanhong, Tao Zhang, Yuxia Hu, and Fudong Nian. "CC-DETR: DETR with Hybrid Context and Multi-Scale Coordinate Convolution for Crowd Counting." Mathematics 12, no. 10 (May 17, 2024): 1562. http://dx.doi.org/10.3390/math12101562.

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Prevailing crowd counting approaches primarily rely on density map regression methods. Despite wonderful progress, significant scale variations and complex background interference within the same image remain challenges. To address these issues, in this paper we propose a novel DETR-based crowd counting framework called Crowd Counting DETR (CC-DETR), which aims to extend the state-of-the-art DETR object detection framework to the crowd counting task. In CC-DETR, a DETR-like encoder–decoder structure (Hybrid Context DETR, i.e., HCDETR) is proposed to tackle complex visual information by fusing features from hybrid semantic levels through a transformer. In addition, we design a Coordinate Dilated Convolution Module (CDCM) to effectively employ position-sensitive context information in different scales. Extensive experiments on three challenging crowd counting datasets (ShanghaiTech, UCF-QNRF, and NWPU) demonstrate that our model is effective and competitive when compared against SOTA crowd counting models.
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Wang, Dashuai, Zhuolin Li, Xiaoqiang Du, Zenghong Ma, and Xiaoguang Liu. "Farmland Obstacle Detection from the Perspective of UAVs Based on Non-local Deformable DETR." Agriculture 12, no. 12 (November 23, 2022): 1983. http://dx.doi.org/10.3390/agriculture12121983.

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In precision agriculture, unmanned aerial vehicles (UAVs) are playing an increasingly important role in farmland information acquisition and fine management. However, discrete obstacles in the farmland environment, such as trees and power lines, pose serious threats to the flight safety of UAVs. Real-time detection of the attributes of obstacles is urgently needed to ensure their flight safety. In the wake of rapid development of deep learning, object detection algorithms based on convolutional neural networks (CNN) and transformer architectures have achieved remarkable results. Detection Transformer (DETR) and Deformable DETR combine CNN and transformer to achieve end-to-end object detection. The goal of this work is to use Deformable DETR for the task of farmland obstacle detection from the perspective of UAVs. However, limited by local receptive fields and local self-attention mechanisms, Deformable DETR lacks the ability to capture long-range dependencies to some extent. Inspired by non-local neural networks, we introduce the global modeling capability to the front-end ResNet to further improve the overall performance of Deformable DETR. We refer to the improved version as Non-local Deformable DETR. We evaluate the performance of Non-local Deformable DETR for farmland obstacle detection through comparative experiments on our proposed dataset. The results show that, compared with the original Deformable DETR network, the mAP value of the Non-local Deformable DETR is increased from 71.3% to 78.0%. Additionally, Non-local Deformable DETR also presents great performance for detecting small and slender objects. We hope this work can provide a solution to the flight safety problems encountered by UAVs in unstructured farmland environments.
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Wu, Jianshuang, Changji Wen, Hongrui Chen, Zhenyu Ma, Tian Zhang, Hengqiang Su, and Ce Yang. "DS-DETR: A Model for Tomato Leaf Disease Segmentation and Damage Evaluation." Agronomy 12, no. 9 (August 26, 2022): 2023. http://dx.doi.org/10.3390/agronomy12092023.

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Early blight and late blight are important factors restricting tomato yield. However, it is still a challenge to accurately and objectively detect and segment crop diseases in order to evaluate disease damage. In this paper, the Disease Segmentation Detection Transformer (DS-DETR) is proposed to segment leaf disease spots efficiently based on several improvements to DETR. Additionally, a damage assessment is carried out by the area ratio of the segmented leaves to the disease spots. First, an unsupervised pre-training method was introduced into DETR with the Plant Disease Classification Dataset (PDCD) to solve the problem of the long training epochs and slow convergence speed of DETR. This method can train the Transformer structures in advance to obtain leaf disease features. Loading the pre-training model weight in DS-DETR can speed up the convergence speed of the model. Then, Spatially Modulated Co-Attention (SMCA) was used to assign Gaussian-like spatial weights to the query box of DS-DETR. The different positions in the image are trained using the query boxes with different weights to improve the accuracy of the model. Finally, an improved relative position code was added to the Transformer structure of DS-DETR. Relative position coding promotes the capture of the sequence order of input tokens by the Transformer. The spatial location feature is strengthened by establishing the location relationship between different instances. Based on these improvements, the DS-DETR model was tested on the Tomato leaf Disease Segmentation Dataset (TDSD) constructed by us. The experimental results show that the DS-DETR proposed by us achieved 0.6823 for APmask, which improved by 12.87%, 8.25%, 3.67%, 1.95%, 10.27%, and 9.52% compared with the state-of-the-art: Mask RCNN, BlendMask, CondInst, SOLOv2, ISTR, and DETR, respectively. In addition, the disease grading accuracy reached 0.9640 according to the segmentation results given by our proposed model.
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Liu, Minggao, Haifeng Wang, Luyao Du, Fangsong Ji, and Ming Zhang. "Bearing-DETR: A Lightweight Deep Learning Model for Bearing Defect Detection Based on RT-DETR." Sensors 24, no. 13 (June 30, 2024): 4262. http://dx.doi.org/10.3390/s24134262.

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Detecting bearing defects accurately and efficiently is critical for industrial safety and efficiency. This paper introduces Bearing-DETR, a deep learning model optimised using the Real-Time Detection Transformer (RT-DETR) architecture. Enhanced with Dysample Dynamic Upsampling, Efficient Model Optimization (EMO) with Meta-Mobile Blocks (MMB), and Deformable Large Kernel Attention (D-LKA), Bearing-DETR offers significant improvements in defect detection while maintaining a lightweight framework suitable for low-resource devices. Validated on a dataset from a chemical plant, Bearing-DETR outperformed the standard RT-DETR, achieving a mean average precision (mAP) of 94.3% at IoU = 0.5 and 57.5% at IoU = 0.5–0.95. It also reduced floating-point operations (FLOPs) to 8.2 G and parameters to 3.2 M, underscoring its enhanced efficiency and reduced computational demands. These results demonstrate the potential of Bearing-DETR to transform maintenance strategies and quality control across manufacturing environments, emphasising adaptability and impact on sustainability and operational costs.
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Qin, Yujing, Qian Liu, and Chuhan Lu. "Cold Front Identification Using the DETR Model with Satellite Cloud Imagery." Remote Sensing 17, no. 1 (December 26, 2024): 36. https://doi.org/10.3390/rs17010036.

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The cloud system characteristics within satellite cloud imagery play a crucial role in the meteorological operational analysis of cold fronts, and integrating satellite cloud imagery into automated frontal identification schemes can provide valuable insights for accurately determining the position and morphology of cold fronts. This study introduces Cloud-DETR, a deep learning identification method that uses the DETR model with satellite cloud imagery, to identify cold fronts from extensive datasets. In the Cloud-DETR method, preprocessed satellite cloud imagery is used to generate training images, which are then put into the DETR model for cold front identification, achieving excellent results. The alignment between the Cloud-DETR cold fronts and weather systems during continuous periods and extreme weather events is assessed. The Cloud-DETR method exhibits high accuracy in both the position and morphology of cold fronts, ensuring stable identification performance. The high matching rate between the Cloud-DETR cold fronts and the manually identified ones in the test set, image dataset and labels from 2017 is verified. This indicates that the Cloud-DETR method can provide an accurate cold fronts dataset. The cold fronts dataset from 2005 to 2023 was obtained using the Cloud-DETR method. It was found that over the past 18 years, the frequency of cold fronts displays distinct seasonal patterns, with the highest occurrences observed during winter, particularly along the mid-latitude storm tracks extending from the east coast of East Asia to the Northwest Pacific. The methodology and findings presented in this study could help advance further research on the characteristics of cold front cloud systems based on long-term datasets.
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Liu, Zhiyong, Kehan Wang, Changming Li, Yixuan Wang, and Guoqian Luo. "TIG-DETR: Enhancing Texture Preservation and Information Interaction for Target Detection." Applied Sciences 13, no. 14 (July 10, 2023): 8037. http://dx.doi.org/10.3390/app13148037.

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FPN (Feature Pyramid Network) and transformer-based target detectors are commonly employed in target detection tasks. However, these approaches suffer from design flaws that restrict their performance. To overcome these limitations, we proposed TIG-DETR (Texturized Instance Guidance DETR), a novel target detection model. TIG-DETR comprises a backbone network, TE-FPN (Texture-Enhanced FPN), and an enhanced DETR detector. TE-FPN addresses the issue of texture information loss in FPN by utilizing a bottom-up architecture, Lightweight Feature-wise Attention, and Feature-wise Attention. These components effectively compensate for texture information loss, mitigate the confounding effect of cross-scale fusion, and enhance the final output features. Additionally, we introduced the Instance Based Advanced Guidance Module in the DETR-based detector to tackle the weak detection of larger objects caused by the limitations of window interactions in Shifted Window-based Self-Attention. By incorporating TE-FPN instead of FPN in Faster RCNN and employing ResNet-50 as the backbone network, we observed an improvement of 1.9 AP in average accuracy. By introducing the Instance-Based Advanced Guidance Module, the average accuracy of the DETR-based target detector has been improved by 0.4 AP. TIG-DETR achieves an impressive average accuracy of 44.1% with ResNet-50 as the backbone network.
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Zhang, Haiyan, Huiqi Li, Guodong Sun, and Feng Yang. "MDA-DETR:Enhancing Offending Animal Detection with Multi-Channel Attention and Multi-Scale Feature Aggregation." Animals 15, no. 2 (January 17, 2025): 259. https://doi.org/10.3390/ani15020259.

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Conflicts between humans and animals in agricultural and settlement areas have recently increased, resulting in significant resource loss and risks to human and animal lives. This growing issue presents a global challenge. This paper addresses the detection and identification of offending animals, particularly in obscured or blurry nighttime images. This article introduces Multi-Channel Coordinated Attention and Multi-Dimension Feature Aggregation (MDA-DETR). It integrates multi-scale features for enhanced detection accuracy, employing a Multi-Channel Coordinated Attention (MCCA) mechanism to incorporate location, semantic, and long-range dependency information and a Multi-Dimension Feature Aggregation Module (DFAM) for cross-scale feature aggregation. Additionally, the VariFocal Loss function is utilized to assign pixel weights, enhancing detail focus and maintaining accuracy. In the dataset section, this article uses a dataset from the Northeast China Tiger and Leopard National Park, which includes images of six common offending animal species. In the comprehensive experiments on the dataset, the mAP50 index of MDA-DETR was 1.3%, 0.6%, 0.3%, 3%, 1.1%, and 0.5% higher than RT-DETR-r18, yolov8n, yolov9-C, DETR, Deformable-detr, and DCA-yolov8, respectively, indicating that MDA-DETR is superior to other advanced methods.
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Zheng, Zhiqiang, Mengbo Wang, Xiaoyu Zhao, and Zhi Weng. "Adltformer Team-Training with Detr: Enhancing Cattle Detection in Non-Ideal Lighting Conditions Through Adaptive Image Enhancement." Animals 14, no. 24 (December 17, 2024): 3635. https://doi.org/10.3390/ani14243635.

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This study proposes an image enhancement detection technique based on Adltformer (Adaptive dynamic learning transformer) team-training with Detr (Detection transformer) to improve model accuracy in suboptimal conditions, addressing the challenge of detecting cattle in real pastures under complex lighting conditions—including backlighting, non-uniform lighting, and low light. This often results in the loss of image details and structural information, color distortion, and noise artifacts, thereby compromising the visual quality of captured images and reducing model accuracy. To train the Adltformer enhancement model, the day-to-night image synthesis (DTN-Synthesis) algorithm generates low-light image pairs that are precisely aligned with normal light images and include controlled noise levels. The Adltformer and Detr team-training (AT-Detr) method is employed to preprocess the low-light cattle dataset for image enhancement, ensuring that the enhanced images are more compatible with the requirements of machine vision systems. The experimental results demonstrate that the AT-Detr algorithm achieves superior detection accuracy, with comparable runtime and model complexity, reaching 97.5% accuracy under challenging illumination conditions, outperforming both Detr alone and sequential image enhancement followed by Detr. This approach provides both theoretical justification and practical applicability for detecting cattle under challenging conditions in real-world farming environments.
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Cao, Xipeng, Peng Yuan, Bailan Feng, and Kun Niu. "CF-DETR: Coarse-to-Fine Transformers for End-to-End Object Detection." Proceedings of the AAAI Conference on Artificial Intelligence 36, no. 1 (June 28, 2022): 185–93. http://dx.doi.org/10.1609/aaai.v36i1.19893.

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The recently proposed DEtection TRansformer (DETR) achieves promising performance for end-to-end object detection. However, it has relatively lower detection performance on small objects and suffers from slow convergence. This paper observed that DETR performs surprisingly well even on small objects when measuring Average Precision (AP) at decreased Intersection-over-Union (IoU) thresholds. Motivated by this observation, we propose a simple way to improve DETR by refining the coarse features and predicted locations. Specifically, we propose a novel Coarse-to-Fine (CF) decoder layer constituted of a coarse layer and a carefully designed fine layer. Within each CF decoder layer, the extracted local information (region of interest feature) is introduced into the flow of global context information from the coarse layer to refine and enrich the object query features via the fine layer. In the fine layer, the multi-scale information can be fully explored and exploited via the Adaptive Scale Fusion(ASF) module and Local Cross-Attention (LCA) module. The multi-scale information can also be enhanced by another proposed Transformer Enhanced FPN (TEF) module to further improve the performance. With our proposed framework (named CF-DETR), the localization accuracy of objects (especially for small objects) can be largely improved. As a byproduct, the slow convergence issue of DETR can also be addressed. The effectiveness of CF-DETR is validated via extensive experiments on the coco benchmark. CF-DETR achieves state-of-the-art performance among end-to-end detectors, e.g., achieving 47.8 AP using ResNet-50 with 36 epochs in the standard 3x training schedule.
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Dissertations / Theses on the topic "Detr"

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Senthivel, Tharsan. "Vers des transformers plus performants pour la détection et le suivi d'objets." Electronic Thesis or Diss., CY Cergy Paris Université, 2024. http://www.theses.fr/2024CYUN1347.

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La détection et le suivi d'objets représentent des défis majeurs en vision par ordinateur, essentiels dans des applications variées telles que la surveillance, les véhicules autonomes et la robotique. L'introduction des modèles Transformer, surpassant les réseaux de neurones convolutionnels (CNN) grâce à leur capacité à modéliser le contexte à longue portée, a conduit à de nombreuses avancées dans ces domaines. Cependant, certains composants des Transformers restent encore sous-explorés, freinant leur adoption à grande échelle.Nous revisitons le modèle Detection Transformer (DETR) et ses requêtes d'objets en proposant des méthodes plug-and-play adaptées à différentes architectures DETR. Celles-ci s'attaquent à la redondance, aux requêtes négatives et à leur mise à jour.D'abord, nous constatons que les requêtes d'objets apprennent des informations redondantes à cause des composants du décodeur Transformer, limitant ainsi leurs performances. Pour remédier à cela, nous proposons DOQ-DETR (Diversified Object Queries DETR), une approche qui encourage l'apprentissage de représentations diversifiées et non redondantes, augmentant ainsi la capacité et l'efficacité du modèle.Ensuite, nous avons observé que certaines requêtes d'objets, bien que de faible confiance (négatives), peuvent fournir de meilleurs résultats d'intersection sur l'union que les requêtes positives. Contrairement aux méthodes conventionnelles qui augmentent le nombre de requêtes, SG-DETR (Subgroup DETR) crée des sous-groupes de requêtes à partir du nombre initial. Pour éviter la redondance entre sous-groupes, DOQ-DETR est appliqué pour diversifier les représentations de chaque sous-groupe, permettant ainsi d'obtenir plusieurs prédictions par objet, avec sélection de la meilleure.Enfin, nous postulons que la mise à jour systématique de toutes les requêtes d'objets n'est pas toujours nécessaire à cause du partage d'informations redondantes. À cet effet, nous introduisons QR-DETR (Query Routing for DETR), un modèle de routage de requêtes qui permet de contourner certaines couches du décodeur Transformer, évitant ainsi l'intégration de connaissances redondantes et favorisant des représentations plus variées.Dans le cadre du suivi d'objets, notamment du suivi d'objet unique, nous proposons une approche différente des trackers classiques. Plutôt que d'éliminer des tokens pour accélérer la recherche, risquant ainsi la perte d'informations pertinentes, nous introduisons TomeTrack, une méthode de fusion de jetons. Cette technique permet de conserver toutes les informations tout en optimisant l'efficacité du suivi et réduisant les coûts de calcul.Des tests approfondis sur des ensembles de données de référence ont démontré les gains de performance obtenus par nos méthodes, tout en répondant à des limitations non résolues par les modèles basés sur Transformers, prouvant ainsi leur efficacité
Object detection and tracking are fundamental challenges in computer vision, crucial for applications like surveillance systems, autonomous vehicles, and robotics. The advent of Transformer models, which excel at modeling long-range context, has provided a powerful alternative to Convolutional Neural Networks (CNNs) for these tasks. Despite their promising performance, many aspects of Transformer-based models remain not fully understood, and several issues continue to hinder their complete utilization.Regarding Transformer-based detectors, we revisit the recent **Detection Transformer (DETR)** model and its object queries, proposing adaptable plug-and-play methods to enhance various DETR architectures. These approaches address issues related to redundancy, negative queries, and query updates.First, our analysis indicates that object queries often capture redundant information due to the Transformer decoder components, resulting in overlapping features that limit their effectiveness. To address this, we introduce DOQ-DETR (Diversified Object Queries DETR), a redundancy reduction training scheme that encourages object queries to learn diverse and non-overlapping representations, thereby maximizing model capacity and improving performance.Second, we observe the presence of queries with lower predicted confidence outperforming those with higher predicted confidence when evaluated only using intersection over union. While conventional methods use query groups, only one group is retained for inference, limiting the model's potential. In contrast, we propose SG-DETR (Subgroup DETR), which creates subgroups of queries to leverage the full potential of all object queries. Additionally, we introduce the DOQ-DETR redundancy reduction scheme among subgroups, promoting diversity between query subgroups.Third, we hypothesize that not all object queries should be updated due to potential redundant information sharing. To tackle this, we propose QR-DETR (Query Routing DETR), a learnable query routing model integrated with the Transformer decoder blocks. This routing mechanism allows queries to selectively bypass specific layers, reducing the risk of redundant knowledge transfer and promoting diverse, non-overlapping representations.Regarding Transformer-based trackers, notably in the context of single-object tracking, we focus on one-stream trackers. We introduce an alternative approach to current one-stream trackers, emphasizing token merging instead of token dropping. Our approach, Tome-Track, processes the search sequence by retaining all information within the sequence while accelerating model processing. We achieve this by merging tokens and providing a condensed search sequence representation without discarding potentially relevant information, thereby enhancing tracking performance and computational efficiency.Extensive testing was conducted for each proposed method using specific datasets from the research community. These tests often demonstrated improvements over baseline results while addressing previously unresolved issues within the Transformer framework, highlighting the significant success of our methods
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Santos, Haline Costa dos. "O agrominerador familiar ?Por detr?s da Serra? de Parelhas, Serid? do Rio Grande do Norte." Universidade Federal do Rio Grande do Norte, 2015. http://repositorio.ufrn.br/handle/123456789/20512.

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As condi??es clim?ticas desfavor?veis ? agricultura familiar, associada ? dificuldade legal de aposentadoria para trabalhadores que atuam exclusivamente na minera??o, s?o indica??es fornecidas que norteiam sobre a combina??o entre a ocupa??o agr?cola e a extra??o mineral de um grupo que decidimos titular ?agromineradores?, localizados ?Por detr?s da Serra? da Princesa, no munic?pio de Parelhas, Serid? do RN. Contudo, para al?m desses aspectos, a pesquisa enseja uma an?lise e verifica??o aprofundada de outros fatores que vinculam essas fam?lias a tal associa??o laboral. Os conceitos de Habitus, campo e trajet?ria de Pierre Bourdieu, assim como o de Institui??es de Geoffey Hodgson s?o fundantes neste trabalho para explicar a inser??o desses agricultores em um ambiente institucional moldado por estruturas sociais que influenciam nas escolhas e comportamentos individuais e coletivos e que assinalam para a relev?ncia das estruturas de poder existentes dentro e fora da fam?lia e para o papel das pol?ticas p?blicas direcionadas aos agricultores familiares e garimpeiros. A an?lise dos dados demonstrou que existe uma estrutura cristalizada e que se manifesta h? anos nesse campo, comprovando o enlace que h? entre esses agentes e as institui??es que os rodeiam na composi??o de comportamentos e rotiniza??o de pr?ticas.
Unfavorable climatic conditions to family farming associated to the legal difficulty of retirement for workers who work exclusively in mining are indications provided by previous papers on this topic and guiding of such joint activities in a group that we have decided to call ?agromineradores?, who are located ?Behind de mountain? of Princess at Parelhas, Serid? do RN. However, in addition to these aspects, the research provides comprehensive analysis and thorough examination of other factors that link these families to such labor association. The theories of Habitus, field and trajectory from Pierre Bourdieu as well as the concept of institutions from Geoffrey Hodgson are central in this paper to explain the inclusion of these part-time farmers in an institutional environment shaped by social structures that influence in the choices of individual and collective behavior and leading to the relevance of the power structures within and outside the family, along with the role of public policies directed to family farmers and miners. The data analyzed showed that there is a crystallized structure that manifests themselves for years in this field, proving the link that exists between these agents and institutions that surround them in the composition of behaviors and routinizing of practices.
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Hervert, John Joseph. "Mule deer use of water developments in Arizona." Thesis, The University of Arizona, 1985. http://etd.library.arizona.edu/etd/GetFileServlet?file=file:///data1/pdf/etd/azu_e9791_1985_270_sip1_w.pdf&type=application/pdf.

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Merkt, Juan R. "Social structure of Andean deer (Hippocamelus antisensis) in southern Peru." Thesis, University of British Columbia, 1985. http://hdl.handle.net/2429/24864.

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The taruca (Hippocamelus antisensis) is the only deer species found permanently in rugged mountainous habitat above the tree line. I studied the social organization of this deer in relation to its reproductive cycle and habitat use in the high Andes of southern Peru. Tarucas bred seasonally. Most fawns were observed towards the end of the rainy season between February and April. Mating was most common in June, during the dry season, and antler-shedding in males occurred in September/October, at the onset of the rainy season. The deer lived in social groups and, unlike most seasonally breeding cervids, formed large mixed-sex groups nearly all year. During the birth season, however, all pregnant females segregated to form female associations. At this time, adult males were found equally in mixed-sex groups or in small all-male groups. These groups differed in their habitat use. Female groups used areas of higher elevation, steeper slopes, and greater rock-cover than either male or mixed-sex groups. I suggest that selection of more rugged and concealed habitats by lactating females is primarily an antipredator strategy to reduce risk of predation on fawns. Tarucas are compared with other social Cervidae and with their ecological counterpart: the mountain Caprinae. The social structure of Hippocamelus resembles that of wild goats (Capra spp) and other Caprinae of similar ecology but it differs from that of wild sheep (Ovis spp).
Science, Faculty of
Zoology, Department of
Graduate
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Ebersole, Regina L. "Efficacy of a controlled hunt for managing white-tailed deer on Fair Hill Natural Resource Management Area, Cecil County, Maryland." Access to citation, abstract and download form provided by ProQuest Information and Learning Company; downloadable PDF file, 66 p, 2007. http://proquest.umi.com/pqdweb?did=1253509781&sid=1&Fmt=2&clientId=8331&RQT=309&VName=PQD.

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Hu, Qinglin. "Temporal variation and inter-relationship of movement and resource selection of red deer (Cervus elaphus) with respect to climate : a case study : a thesis submitted in partial fulfillment of the requirements for the degree of Master of Science (Environmental Science) at the University of Canterbury /." Thesis, University of Canterbury. Environmental Science, 2006. http://hdl.handle.net/10092/1299.

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Red deer (Cervus elaphus) is one of at least 31 herbivorous exotic mammals existing in New Zealand. All of these species have the potential to affect environmentral and production values. Reducing their impacts on their values, strengthening effective managements are important issues to a variety of agencies within New Zealand including the Department of Conservation (DOC), Ministry of Agriculture and Forestry (MAF), local and regional governments. This research studied animal movement pattern and habitat use of 2 GPScollared red deer in the Canterbury high country and found (1) deer movement was affected by climatic variables such as rainfall and temperature, which had positive or negative effect on it, and had seasonal variation; (2) deer had dominant landcover use categories, depending on climate, season, and individual characteristics (3) deer had different movement patterns in terms of hourly distances. The purpose of the study is to draw accurate inferences from spatially explicit data for biosecurity managers and policy-makers through: (1) using global positioning system (GPS) as a tool to elucidate the application of GPS on red deer in wildlife management; (2) Animal Movement Analysis Arc View® 3.2 Extension under Arc View® Geographic Information System (GIS); (3) Animal movement analysis which used Generalized Additive Models (GAMs) to show how the movement of red deer was affected by different periods of time, seasons months and climatic variables (for example, rainfall and temperature).
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Holtfreter, Robert W. Ditchkoff Stephen S. "Spatial ecology of male white-tailed deer in the Crosstimbers and Prairies ecoregion." Auburn, Ala, 2008. http://repo.lib.auburn.edu/EtdRoot/2008/SUMMER/Forestry_and_Wildlife_Sciences/Thesis/Holtfreter_Robert_20.pdf.

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Yzasmendi, Arellano Guillermo Rodolfo. "Evaluaci��n por competencias en el razonamiento l��gico-matem��tico y en el cambio de actitud hacia la ciencia." Thesis, Universidad de las Am��ricas Puebla, 2012. http://catarina.udlap.mx/u_dl_a/tales/documentos/det/yzasmendi_a_gr/.

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Ch��zaro, Arellano Eva Hortensia. "Integraci��n del Modelo Pedag��gico basado en la Sabidur��a Nativa. Cerrando el c��rculo del aprendizaje." Thesis, Universidad de las Am��ricas Puebla, 2012. http://catarina.udlap.mx/u_dl_a/tales/documentos/det/chazaro_a_eh/.

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Este estudio de investigaci��n es una contribuci��n a la sistematizaci��n del paradigma nativo como base del conocimiento. Parte del riesgo que se observa en la construcci��n de propuestas interculturales como atenci��n a la diversidad cultural, que todav��a conservan un matiz epistemol��gico occidentalizado. Se da respuesta a la pregunta focal ��C��mo se aprende desde el conocimiento nativoα Mediante una metodolog��a cualitativa impregnada de la incipiente metodolog��a nativa en investigaci��n, se ofrece como objetivo alcanzado la integraci��n del Modelo Pedag��gico Nativo, una tendencia hacia cerrar el c��rculo del aprendizaje. A trav��s de un an��lisis documental profundo, observaci��n participante, grupos de conversaci��n, relatos familiares y entrevistas semiestructuradas; se realiz�� un an��lisis descrito con detalle que evidencia la Sabidur��a Nativa como medio de vida para formar seres humanos ��ntegros en la comunidad y en el Espacio Territorial. Abstract This research is a contribution to the sistematization of the native paradigm as base of knowledge. Consider the problem that is possible to see in the construction of intercultural procces for attend cultural diversity, but with an occidental epistemological base yet
(cont.) Answer the focal question ��How native people learnα With a qualitative methodology and elements from a native methodology for research, the objective is the integration of the Native Pedagogical Model, for close the learning circle. On this study was used methods as deep documental analysis, participant observation, talking circles, familiar stories and interviews. The researcher did an analysis described on details that evidence the Native Wisdom as lifestyle for form whole human beings in the community and Territorial Space..
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Luna, Gijón Gerardo. "Desarrollo de un modelo instruccional para diseñar materiales digitales de aprendizaje en el área de medicina." Thesis, Universidad de las Américas Puebla, 2012. http://catarina.udlap.mx/u_dl_a/tales/documentos/det/luna_g_g/.

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Uno de los retos que existen actualmente en la educación en las ciencias de la salud es el no tener en claro para qué, cómo y cuándo nos sirven los medios digitales como un apoyo en la educación de los estudiantes del periodo de preclínica. Existe una falta de modelos instruccionales dirigidos a profesores del periodo de preclínica de las universidades poblanas, que sean específicos para desarrollar objetos de aprendizaje médicos, y que centren su atención en los procesos de interacción entre las personas y aquella información que producen. Esto da pie y provee de la oportunidad para un proyecto que ayude a innovar y modernizar el alto nivel de preparación, que se exige tengan los futuros practicantes de la medicina en el estado de Puebla. Apoyando a los profesores universitarios, se espera que el impacto y enriquecimiento en su práctica docente repercuta en el aprendizaje de los estudiantes, que estarán mejor capacitados para lidiar con las complejidades de su área, y además contarán con una formación humana de alta calidad. El objetivo de la investigación fue desarrollar un modelo instruccional para diseñar materiales educativos digitales que apoye el Razonamiento Clínico en la enseñanza preclínica y que aprovechara las aportaciones que por separado han hecho diversas áreas del diseño, como son el campo del diseño instruccional y del diseño de la información visual. Para la validación del modelo se utilizó la técnica Delphi. El primer paso fue buscar un panel de profesores expertos, que abarca dos facultades de medicina. A cada uno se le pidió que analizara e hiciera recomendaciones con base en (1) efectividad de las etapas propuestas, (2) adecuación para las condiciones y necesidades de los profesores médicos, (3) tiempo y facilidad de ejecución del modelo. Además se recurrió a la opinión de expertos en educación y en diseño. La retroalimentación obtenida fue positiva, con un alto grado de aceptación del modelo por parte de los expertos. Las etapas y pasos del modelo propuesto son adecuados y valiosos; además se ha realizado una versión condensada del modelo para mejorar tiempo de ejecución y facilidad, para aquellos profesores dedicados a la enseñanza de tiempo parcial en las instituciones. Este estudio provee evidencia de la viabilidad para apoyar a los profesores médicos de las distintas universidades del estado de Puebla, para diseñar materiales digitales educativos mediante un modelo instruccional que promueve el Razonamiento Clínico mediante el uso de casos clínicos, en los estudiantes de medicina durante la preclínica.
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Books on the topic "Detr"

1

Jordan, Wilhelm. Das Apostalgrab, der sakrale Grundstein detr Vatikansichen Basilika. Trier: Selbstverlag Rheinsichen Landesmuseum, 1990.

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Great Britain. Dept. of the Environment, Transport and the Regions. and London Research Centre, eds. Relationship breakdown: A guide for social landlords : a report to the DETR. London: Dept. of the Environment, Transport and the Regions, 1999.

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Association, Local Government. Modernising local government: Improving local services through best value : LGA response to DETR consultation paper. London: Local Government Association, 1998.

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Great Britain. Department of Transport. This is DETR: A guide to the Department of the Environment, Transport and the Regions. London: DETR, 1998.

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Great Britain. Department of Transport. Developing good practice in tenant participation: A guide for the DETR by: Ian Cole... [et al.]. London: Department of the Environment, Transport and the Regions, 1999.

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Institution, of Professionals Managers and Specialists. A public private partnership for NATS?: A union response to the DETR consultation paper National Air Traffic Services. London: Institution of Professionals, Managers and Specialists, 1999.

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Witwer, Ron. Deer tales and dear tales. Narvon, PA: R. Witwer, 2009.

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Barretta, Gene. Dear deer: A book of homophones. New York: Square Fish, 2010.

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Department of Environment,Transport and the regions. Performance indicators for 2000/2001: A joint consultation document produced by DETR and the audit commission on best value and local authority performance indicators for 2000/2001. London: HMSO, 1999.

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Croser, J. Dear Sam, dear Ben. Flinders Park: Era Pub., 1991.

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Book chapters on the topic "Detr"

1

Huang, Yi-Xin, Hou-I. Liu, Hong-Han Shuai, and Wen-Huang Cheng. "DQ-DETR: DETR with Dynamic Query for Tiny Object Detection." In Lecture Notes in Computer Science, 290–305. Cham: Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-73116-7_17.

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Zang, Yuhang, Wei Li, Kaiyang Zhou, Chen Huang, and Chen Change Loy. "Open-Vocabulary DETR with Conditional Matching." In Lecture Notes in Computer Science, 106–22. Cham: Springer Nature Switzerland, 2022. http://dx.doi.org/10.1007/978-3-031-20077-9_7.

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Lin, Zijian, and Junyong Zhai. "DETR with Recursive Gated Convolution Encoder." In Lecture Notes in Electrical Engineering, 785–94. Singapore: Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-99-6847-3_69.

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Shangguan, Zeyu, Lian Huai, Tong Liu, Yuyu Liu, and Xingqun Jiang. "Decoupled DETR for Few-Shot Object Detection." In Lecture Notes in Computer Science, 158–74. Singapore: Springer Nature Singapore, 2024. https://doi.org/10.1007/978-981-96-0966-6_10.

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Senthivel, Tharsan, and Ngoc-Son Vu. "QR-DETR: Query Routing for Detection Transformer." In Lecture Notes in Computer Science, 395–412. Singapore: Springer Nature Singapore, 2024. https://doi.org/10.1007/978-981-96-0960-4_24.

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Kumar, Akhilesh, Satish Kumar Singh, and Shiv Ram Dubey. "Target Detection Using Transformer: A Study Using DETR." In Computer Vision and Machine Intelligence, 747–59. Singapore: Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-19-7867-8_59.

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Du, Penghui, Yu Wang, Yifan Sun, Luting Wang, Yue Liao, Gang Zhang, Errui Ding, Yan Wang, Jingdong Wang, and Si Liu. "LaMI-DETR: Open-Vocabulary Detection with Language Model Instruction." In Lecture Notes in Computer Science, 312–28. Cham: Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-73337-6_18.

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Naeem, Roman, David Hagerman, Lennart Svensson, and Fredrik Kahl. "Trexplorer: Recurrent DETR for Topologically Correct Tree Centerline Tracking." In Lecture Notes in Computer Science, 744–54. Cham: Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-72120-5_69.

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Nguyen, Dung, Van-Dung Hoang, and Van-Tuong-Lan Le. "V-DETR: Pure Transformer for End-to-End Object Detection." In Intelligent Information and Database Systems, 120–31. Singapore: Springer Nature Singapore, 2024. http://dx.doi.org/10.1007/978-981-97-4985-0_10.

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Liu, Zhe, Jinghua Hou, Xiaoqing Ye, Tong Wang, Jingdong Wang, and Xiang Bai. "SEED: A Simple and Effective 3D DETR in Point Clouds." In Lecture Notes in Computer Science, 110–26. Cham: Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-73247-8_7.

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Conference papers on the topic "Detr"

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Wei, Jianghao, Wei Shen, Tao Hu, Qiang Liu, Jie Yu, and Jiahuan Huang. "Dynamic-DETR: Dynamic Perception for RT -DETR." In 2024 6th International Conference on Robotics and Computer Vision (ICRCV), 28–32. IEEE, 2024. http://dx.doi.org/10.1109/icrcv62709.2024.10758592.

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Zhao, Chuyang, Yifan Sun, Wenhao Wang, Qiang Chen, Errui Ding, Yi Yang, and Jingdong Wang. "MS-DETR: Efficient DETR Training with Mixed Supervision." In 2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 17027–36. IEEE, 2024. http://dx.doi.org/10.1109/cvpr52733.2024.01611.

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Li, Xvjian, and Xuekuan Zhang. "LS DETR: Lightweight DETR with Selective Transmission Training Strategy." In 2024 2nd International Conference on Algorithm, Image Processing and Machine Vision (AIPMV), 24–30. IEEE, 2024. http://dx.doi.org/10.1109/aipmv62663.2024.10692215.

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Jiang, Jiaran, Xin Zuo, Xin Shu, Dan Xu, and Ping Qian. "UW-DETR: Underwater Image Instance Segmentation with Co-DETR." In 2024 7th International Conference on Pattern Recognition and Artificial Intelligence (PRAI), 125–30. IEEE, 2024. https://doi.org/10.1109/prai62207.2024.10826932.

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Li, Wenqiang, Aimin Li, Zhiyao Li, Xiaotong Kong, and Yuechen Zhang. "RTS-DETR: Efficient Real-Time DETR for Small Object Detection." In 2024 IEEE International Conference on Systems, Man, and Cybernetics (SMC), 1211–16. IEEE, 2024. https://doi.org/10.1109/smc54092.2024.10831335.

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Yin, Jun, Fei Wu, Chang Lin, Huadong Pan, Bangjie Tang, Haijun Gong, and Hongliang Zhang. "TIP-DETR: Tailored Image Prompts DETR for Few-shot Object Detection." In 2024 12th International Conference on Information Systems and Computing Technology (ISCTech), 1–5. IEEE, 2024. https://doi.org/10.1109/isctech63666.2024.10845518.

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Cao, Feng, Ruoyu Wang, Deyu Li, and Zhiguo Hu. "RS-DETR: An Improved DETR for High-Resolution Remote Sensing Image Object Detection." In 2024 IEEE International Conference on Systems, Man, and Cybernetics (SMC), 1377–82. IEEE, 2024. https://doi.org/10.1109/smc54092.2024.10831356.

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Ge, Ruize, Xiaoyin Hu, and Duo Xiao. "Fire detection method based on improved DETR." In 2024 4th International Symposium on AI (ISAI), 16–20. IEEE, 2024. http://dx.doi.org/10.1109/isai63299.2024.00013.

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Liu, Qiwen, XiaoLi Li, and Zhenlong Du. "Hyperspectral image methane detection based on DETR." In Sixteenth International Conference on Graphics and Image Processing (ICGIP 2024), edited by Liang Xiao, 91. SPIE, 2025. https://doi.org/10.1117/12.3057898.

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Chang, Yajun, Chenlin Zhang, Yang Shui, and Zelong Wang. "Saliency guided RT-DETR for object detection." In Sixteenth International Conference on Graphics and Image Processing (ICGIP 2024), edited by Liang Xiao, 95. SPIE, 2025. https://doi.org/10.1117/12.3057913.

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Reports on the topic "Detr"

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Schmidt, Lene Skytthe Kaarsberg. "Familiepædagogen" - som trivsels- og forebyggelsesaktør. Professionshøjskolen Absalon, 2024. http://dx.doi.org/10.62528/valu2077.

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Forskningsrapporten ”Familiepædagogen” – som trivsel og forebyggelsesaktør belyser, hvad der kendetegner arbejdet med trivsel for ledere og pædagoger, når de har en tæt, forebyggende og opsøgende kontakt med familier. I forskningsrapporten skitseres tre policy `bølger´ for pædagogers og lederes arbejde med familier og børn, hvor trivsel bliver tillagt forskellige betydninger: (1) ”Trivsel som målbart fænomen – ledere og pædagoger forventes at opdele og måle børn”. (2) ”Trivsel som subjektivt oplevet – pædagoger og ledere forventes at leve sig ind i det enkelte barns perspektiv og situation”. (3) ”Trivsel som fællesskaber og tilhør – pædagoger og ledere forventes at skabe almene fællesskaber med plads til forskellighed blandt børn”. I rapportens policy analysen belyses især den sidste trivselsbølge og der rejses en række dilemmaer, som det pædagogisk set kan være vigtigt, at der er opmærksomhed på. I rapporten kan læses om, hvilke glidninger, der sker når aktuelle trivselsdagsordner med idealer om tilhør og fællesskaber fremhæver lederes og pædagogers ”relationskompetence”. Der belyses også, hvordan trivselsbølgen indebærer en økonomisk og administrativ bevægelse, når en vægtning af tilhør for flere børn i fællesskaber driver en udvidelse af almentilbuddet frem, der nu skal løse mere sammensatte opgaver for de samme ressourcer. Begge dele risikerer at individualisere pædagogers og lederes arbejde og at nedtone samfundsmæssigt ulige vilkår for familier, og børn, etiske dilemmaer og den organisatoriske indlejrethed for arbejdet Pædagoger og ledere arbejder i en høj kompleksitet – med talrige familier og børn og ikke blot én enkelt familie og barn ad gangen. I praksis analysen viser rapporten, hvordan pædagoger og ledere sammen udvikler en organisatorisk skarpsindighed, hvor de for at styrke familiers og børns tilhør på daglig basis gentænker deres organiseringer af praksisser og (op)finder ressourcer. Det er et arbejde, der ikke er synligt i organisatoriske diagrammer og arbejdsgange. I rapporten beskrives det som et tilbagevendende pædagogisk arbejde med ”at gøre tilhør”. Dette arbejde slider samtidig, og det forstærker og intensiverer høje følelsesmæssige krav i arbejdet. I lederes og pædagogers arbejde med familier og børn opstår en særlig social bekymringsform: De bekymrer sig for, om der opstår ulighed for familierne og børnene i kontakten med offentlige institutioner og i adgangen til hjælp. Den bekymring adskiller sig fra omsorgsbekymring og udviklingsbekymring. Det er samtidig en bekymringsform, der kan blive hjemløs, da der ofte ikke er nogen steder at placere den, og som de derfor selv tager på sig. Det løbende trivselsarbejde med at skabe tilhør for børn og familier kan for pædagoger såvel som ledere indebærer en tæthed og en voldsomhed. I rollen mellem det lyttende og tillidsopbyggende, og den rolle der ligger i det indgribende strækkes de her til det yderste.
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Eriksson, Birgit, Louise Ejgod Hansen, and Karen Nordentoft. Deltagelse i kulturhuse og andre borgerinvolverende kulturinstitutioner. Aarhus University Library, 2021. http://dx.doi.org/10.7146/aul.429.

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”En aften så fortalte jeg om, hvordan man laver akvarelmaling, og en anden aften var der en, der fortalte om høbinding og hvordan – og en tredje aften var det hende der keramikeren.” ”Så satte de bare et kæmpe skilt op, og det fyldte hele væggen i vores rum med vores Robert Jacobsen plakater.” ”Og det er jo det, som jeg synes, jeg har, og det, som jeg kan se, mine naboer har. En tillid til at vi vil det bedste for vores naboer og for byen – og at vi kan gøre det, vi siger. Og hvis vi ikke kan det, så bliver vi klogere undervejs og ændrer det til det bedre.” ”... et alternativt rum for unge mennesker, som er trygt at være i, som bygger på feministiske normer som safe space og idealer om ligeværd og tryghed, som man kan have svært ved at finde i andre konstellationer.” Disse udtalelser fra brugere er indsamlet i danske kultur- huse og andre borgerinddragende kulturinstitutioner. Men hvad betyder kulturhusene? Hvilken rolle spiller deres rum? Hvilke brugere har de? Og hvilke deltagelsesformer praktiseres? De spørgsmål behandles i denne rapport, som er et resultat af et omfangsrigt kvalitativt studie i 28 kulturhuse. Studiet er sket i samarbejde med medforskere i alle kulturhusene og er anden delundersøgelse i forsknings- og udviklings- projektet DELTAG.
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Kabel, Kristine, Mette Vedsgaard Christensen, Morten Tannert, Lise Olsen, and Sanne Floor Bendixen Sanne Floor Bendixen. Manual for analyse af elevers metasproglige repertoire: Working paper i projektet Writing Educating (2022-25). Aarhus University, October 2024. http://dx.doi.org/10.7146/aul.537.

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I projektet Writing Education (2022-2025) undersøger vi, hvad der karakteriserer relationer mellem elevers skrivning og metasproglige repertoire i forskellige skrivesituationer i danskfaget i 5. og 8. klasse (overordnet forskningsspørgsmål). Det er et kvalitativt tekst- og klasserumsstudie, hvor vi som en del af vores data også har foretaget tekstinterviews med fokuselever fra hver af de deltagende klasser. I dette working paper præsenterer vi en kodemanual til at analysere elevers metasproglige repertoire som det kommer til udtryk i interviews om egne tekster, og til at analysere, hvilket metasprogligt repertoire der kan lægges op til i skriveundervisningsforløb, sådan som det kan indfanges gennem klasserumsobservationer.
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Schmidt, Lene Skytthe Kaarsberg, Jimmy Krab, and Charlotte Jørgensen. Muligheder og barrierer i samarbejde om børn: når kontakt mellem professionelle og forældre er svært. Professionshøjskolen Absalon, January 2022. http://dx.doi.org/10.62528/ommb4402.

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Der opstår dagligt kulturmøder mellem familien, skolen eller daginstitutionen (0–6 år), når forældre, professionelle og børn i mange forskellige rammer og situationer er sammen med hinanden. Kulturmøder forstås her som det, der opstår mellem skolen, familien og/ daginstitutionen, når professionelle, forældre og børn dagligt er sammen, og når der forhandles om hvilke normer og værdier for børns hverdag, som kan gøres gældende. De daglige rammer, samværsformer og situationer i skoler og daginstitutioner oplever professionelle, forældre og børn ofte forskelligt. Forældre og professionelle er samtidig gensidigt afhængige af hinanden, når de er i kontakt om, hvordan børnene har det i skolen, hjemmet og/daginstitutionen. I denne rapport belyser vi forældres og professionelles oplevelse af, hvilke muligheder og barrierer der er for at etablere et samarbejde, som er til gavn for børns trivsel og udvikling. Fokus omfatter især, når familien, skolen og/ daginstitutionen er udfordret i at have og opretholde kontakt med hinanden, og når børn har det svært. Vi zoomer ind på tematikkerne: mobbeprocesser og marginaliserende gruppedynamikker, børns fællesskaber og hvad sprog betyder for deres deltagelse i dem.
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Wallace, Victoria, and Alyss Siegel-Miles. Deer Management. UConn Extension, March 2022. http://dx.doi.org/10.61899/ucext.v1.020.2024.

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Bärenthaler-Sieber, Susanne, and Michael Böheim. ERGEBNISSE DER ZWISCHENEVALUIERUNG DER ERSTEN PHASE DER BREITBANDINITIATIVE. Fteval Journal, January 2019. http://dx.doi.org/10.22163/fteval.2018.301.

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Jespersen, Anna, and Míša Hejná. ”Vokalhelvedet”: hvor svær er dansk udtale, og hvordan undervises der i udtale for andetsprogstalere? Aarhus University Library, 2021. http://dx.doi.org/10.7146/aul.427.

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Det danske sprog anses af mange lørnere som svært at lære, og især anses det som svært at blive flydende i. Dette bliver ofte tilskrevet den svære danske udtale. Artiklen her viser, at sprogskolernes håndtering af udtaleundervisning kan bidrage til voksne andetsprogstaleres udtaleproblemer. Her undersøges voksne lørneres og underviseres iagttagelser omkring det svære danske sprog, og undervisningen af det. I denne undersøgelse inddrages en analyse af undervisningsmateriale brugt ved voksenundervisning i dansk som andetsprog, og en diskussion af danskeksamener for andetsprogstalere. Vores resultater indikerer at udtale, og især vokaler, anses af både lørnere og undervisere som særligt svære at mestre. Samtidig undervises der ifølge vores informanter ikke nok i vokaludtale på de danske sprogskoler. Selvom de to informantgrupper generelt er relativt enige er især mængden af undervisning i udtale et kontrastpunkt mellem lørnere og undervisere. Vi diskuterer denne forskel, samt betydningen af meget lidt undervisningsmateriale der fokuserer på udtale efter DU-modul 1, og et manglende fokus på udtale i danskeksamenerne.
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von Balthasar, Hans Urs. Von der Kultursendung der Kirche. Saint John Publications, 2024. http://dx.doi.org/10.56154/nj.

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Huijser, Marcel, and S. C. Getty. Modified jump-outs for white-tailed deer and mule deer. Nevada Department of Transportation, September 2022. http://dx.doi.org/10.15788/ndot2018.2022.

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The height of the jump-outs should be low enough for the target species to readily jump down to the safe side, or the habitat side, of the fence. At the same time, the jump-outs should be high enough to discourage animals that are on the habitat side of the fence from jumping up into the fenced road corridor. Previous research along US Hwy 93 North in Montana showed that only about 32% of the mule deer and about 7% of the white-tailed deer that appeared on top of the jump-outs, jumped down to safety. For this project, 10 of the jump-outs along US Hwy 93 North were lowered in height and provided with a bar on top. The height of the bars (made from rebar) and their setback from the vertical face of the jump-outs was adjustable and the researchers applied 4 different treatments: 2 different heights (18 and 15 inches) and 3 different setbacks (4, 12, and 15 inches). The overall effectiveness of the lowered jump-outs in allowing white-tailed deer to jump down, regardless of the height and setback of the bar, was only just above 5% (no improvement). For mule deer the effectiveness of the lowered jump-outs in allowing them to jump down, regardless of the height and setback of the bar, was about 64% (this was double the effectiveness of non-modified jump-outs).
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Wagner-Luptacik, Petra. Steigerung der Hebelwirkung der TechnoKontakte Seminare. ARC - Austrian Research Centers, December 2005. http://dx.doi.org/10.22163/fteval.2005.186.

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