Literatura científica selecionada sobre o tema "Constraints annotation"
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Artigos de revistas sobre o assunto "Constraints annotation"
SAMPSON, GEOFFREY, e ANNA BABARCZY. "Definitional and human constraints on structural annotation of English". Natural Language Engineering 14, n.º 4 (outubro de 2008): 471–94. http://dx.doi.org/10.1017/s1351324908004695.
Texto completo da fonteAnderson, Matthew, Salman Sadiq, Muzammil Nahaboo Solim, Hannah Barker, David H. Steel, Maged Habib e Boguslaw Obara. "Biomedical Data Annotation: An OCT Imaging Case Study". Journal of Ophthalmology 2023 (22 de agosto de 2023): 1–9. http://dx.doi.org/10.1155/2023/5747010.
Texto completo da fonteLin, Jia-Wen, Feng Lu, Tai-Chen Lai, Jing Zou, Lin-Ling Guo, Zhi-Ming Lin e Li Li. "Meibomian glands segmentation in infrared images with limited annotation". International Journal of Ophthalmology 17, n.º 3 (18 de março de 2024): 401–7. http://dx.doi.org/10.18240/ijo.2024.03.01.
Texto completo da fonteGrác, Marek, Markéta Masopustová e Marie Valíčková. "Affordable Annotation of the Mobile App Reviews". Journal of Linguistics/Jazykovedný casopis 70, n.º 2 (1 de dezembro de 2019): 491–97. http://dx.doi.org/10.2478/jazcas-2019-0077.
Texto completo da fonteOlivier, Brett G., e Frank T. Bergmann. "The Systems Biology Markup Language (SBML) Level 3 Package: Flux Balance Constraints". Journal of Integrative Bioinformatics 12, n.º 2 (1 de junho de 2015): 660–90. http://dx.doi.org/10.1515/jib-2015-269.
Texto completo da fonteLuo, Yuan, e Peter Szolovits. "Efficient Queries of Stand-off Annotations for Natural Language Processing on Electronic Medical Records". Biomedical Informatics Insights 8 (janeiro de 2016): BII.S38916. http://dx.doi.org/10.4137/bii.s38916.
Texto completo da fonteISMAIL, MOHAMED MAHER BEN, e OUIEM BCHIR. "AUTOMATIC IMAGE ANNOTATION BASED ON SEMI-SUPERVISED CLUSTERING AND MEMBERSHIP-BASED CROSS MEDIA RELEVANCE MODEL". International Journal of Pattern Recognition and Artificial Intelligence 26, n.º 06 (setembro de 2012): 1255009. http://dx.doi.org/10.1142/s0218001412550099.
Texto completo da fonteBABARCZY, ANNA, JOHN CARROLL e GEOFFREY SAMPSON. "Definitional, personal, and mechanical constraints on part of speech annotation performance". Natural Language Engineering 12, n.º 1 (6 de dezembro de 2005): 77–90. http://dx.doi.org/10.1017/s1351324905003803.
Texto completo da fonteGe, Hongwei, Zehang Yan, Jing Dou, Zhen Wang e ZhiQiang Wang. "A Semisupervised Framework for Automatic Image Annotation Based on Graph Embedding and Multiview Nonnegative Matrix Factorization". Mathematical Problems in Engineering 2018 (27 de junho de 2018): 1–11. http://dx.doi.org/10.1155/2018/5987906.
Texto completo da fonteNursimulu, Nirvana, Alan M. Moses e John Parkinson. "Architect: A tool for aiding the reconstruction of high-quality metabolic models through improved enzyme annotation". PLOS Computational Biology 18, n.º 9 (8 de setembro de 2022): e1010452. http://dx.doi.org/10.1371/journal.pcbi.1010452.
Texto completo da fonteTeses / dissertações sobre o assunto "Constraints annotation"
Schild, Erwan. "De l’importance de valoriser l’expertise humaine dans l’annotation : application à la modélisation de textes en intentions à l’aide d’un clustering interactif". Electronic Thesis or Diss., Université de Lorraine, 2024. http://www.theses.fr/2024LORR0024.
Texto completo da fonteUsually, the task of annotation, used to train conversational assistants, relies on domain experts who understand the subject matter to model. However, data annotation is known to be a challenging task due to its complexity and subjectivity. Therefore, it requires strong analytical skills to model the text in dialogue intention. As a result, most annotation projects choose to train experts in analytical tasks to turn them into "super-experts". In this thesis, we decided instead to focus on the real knowledge of experts by proposing a new annotation method based on Interactive Clustering. This method involves a Human-Machine cooperation, where the machine performs clustering to provide an initial learning base, and the expert annotates MUST-LINK or CANNOT-LINK constraints between the data to iteratively refine the proposed learning base. Such annotation has the advantage of being more instinctive, as experts can associate or differentiate data according to the similarity of their use cases, allowing them to handle the data as they would professionally do on a daily basis. During our studies, we have been able to show that this method significantly reduces the complexity of designing a learning base, notably by reducing the need for training the experts involved in an annotation project. We provide a technical implementation of this method (algorithms and associated graphical interface), as well as a study of optimal parameters to achieve a coherent learning base with minimal annotation. We have also conducted a cost study (both technical and human) to confirm that the use of such a method is realistic in an industrial context. Finally, we provide a set of recommendations to help this method reach its full potential, including: (1) advice aimed at framing the annotation strategy, (2) assistance in identifying and resolving differences of opinion between annotators, (3) rentability indicators for each expert intervention, and (4) methods for analyzing the relevance of the learning base under construction. In conclusion, this thesis provides an innovative approach to design a learning base for a conversational assistant, involving domain experts for their actual knowledge, while requiring a minimum of analytical and technical skills. This work opens the way for more accessible methods for building such assistants
Ong, Wai, Trang Vu, Klaus Lovendahl, Jenna Llull, Margrethe Serres, Margaret Romine e Jennifer Reed. "Comparisons of Shewanella strains based on genome annotations, modeling, and experiments". BioMed Central, 2014. http://hdl.handle.net/10150/610105.
Texto completo da fonteBoyd, Adriane Amelia. "Detecting and Diagnosing Grammatical Errors for Beginning Learners of German: From Learner Corpus Annotation to Constraint Satisfaction Problems". The Ohio State University, 2012. http://rave.ohiolink.edu/etdc/view?acc_num=osu1325170396.
Texto completo da fonteWodke, Judith. "Organization and integration of large-scale datasets for designing a metabolic model and re-annotating the genome of mycoplasma pneumoniae". Doctoral thesis, Humboldt-Universität zu Berlin, Mathematisch-Naturwissenschaftliche Fakultät I, 2013. http://dx.doi.org/10.18452/16699.
Texto completo da fonteMycoplasma pneumoniae, one of the smallest known self-replicating organisms, is a promising model organism in systems biology when aiming to assess understanding of an entire living cell. One key step towards this goal is the design of mathematical models that describe cellular processes by connecting the involved components to unravel underlying mechanisms. For Mycoplasma pneumoniae, a wealth of genome-wide datasets on genomics, transcriptomics, proteomics, and metabolism had been produced. However, a proper system facilitating information exchange and mathematical models to integrate the different datasets were lacking. Also, different in vivo observations of metabolic behavior remained unexplained. This thesis presents a combinatorial approach to design a metabolic model for Mycoplasma pneumoniae. First, we developed a database, MyMpn, in order to provide access to structured and organized data. Second, we built a predictive, genome-scale, constraint-based metabolic model and, in parallel, we explored the metabolome in vivo. We defined the biomass composition of a Mycoplasma pneumoniae cell, corrected the wiring diagram, showed that a large proportion of energy is dedicated to cellular homeostasis, and analyzed the metabolic behavior under different growth conditions. Finally, we manually re-annotated the genome of Mycoplasma pneumoniae. The database, despite not yet being released to the public, is internally already used for data analysis, and for mathematical modeling. Unraveling the principles governing energy metabolism and adaptive capabilities upon gene deletion highlight the impact of the reductive genome evolution and facilitates the development of engineering tools and dynamic models for metabolic sub-systems. Furthermore, we revealed that the degree of complexity in which the genome of Mycoplasma pneumoniae is organized far exceeds what has been considered possible so far and we identified 32 new, previously not annotated genes.
Serrano, Martínez-Santos Nicolás. "Interactive Transcription of Old Text Documents". Doctoral thesis, Universitat Politècnica de València, 2014. http://hdl.handle.net/10251/37979.
Texto completo da fonteSerrano Martínez-Santos, N. (2014). Interactive Transcription of Old Text Documents [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/37979
TESIS
Guillaumin, Matthieu. "Données multimodales pour l'analyse d'image". Phd thesis, Grenoble, 2010. http://www.theses.fr/2010GRENM048.
Texto completo da fonteThis dissertation delves into the use of textual metadata for image understanding. We seek to exploit this additional textual information as weak supervision to improve the learning of recognition models. There is a recent and growing interest for methods that exploit such data because they can potentially alleviate the need for manual annotation, which is a costly and time-consuming process. We focus on two types of visual data with associated textual information. First, we exploit news images that come with descriptive captions to address several face related tasks, including face verification, which is the task of deciding whether two images depict the same individual, and face naming, the problem of associating faces in a data set to their correct names. Second, we consider data consisting of images with user tags. We explore models for automatically predicting tags for new images, i. E. Image auto-annotation, which can also used for keyword-based image search. We also study a multimodal semi-supervised learning scenario for image categorisation. In this setting, the tags are assumed to be present in both labelled and unlabelled training data, while they are absent from the test data. Our work builds on the observation that most of these tasks can be solved if perfectly adequate similarity measures are used. We therefore introduce novel approaches that involve metric learning, nearest neighbour models and graph-based methods to learn, from the visual and textual data, task-specific similarities. For faces, our similarities focus on the identities of the individuals while, for images, they address more general semantic visual concepts. Experimentally, our approaches achieve state-of-the-art results on several standard and challenging data sets. On both types of data, we clearly show that learning using additional textual information improves the performance of visual recognition systems
Guillaumin, Matthieu. "Données multimodales pour l'analyse d'image". Phd thesis, Grenoble, 2010. http://tel.archives-ouvertes.fr/tel-00522278/en/.
Texto completo da fonteGhadie, Mohamed A. "Analysis and Reconstruction of the Hematopoietic Stem Cell Differentiation Tree: A Linear Programming Approach for Gene Selection". Thesis, Université d'Ottawa / University of Ottawa, 2015. http://hdl.handle.net/10393/32048.
Texto completo da fonteChen, Yen-Ting, e 陳彥廷. "Dense Correspondence Annotation of Video Data Using Non-Rigid Registration with Salient Feature Correspondence Constraints". Thesis, 2014. http://ndltd.ncl.edu.tw/handle/68845600289225045103.
Texto completo da fonte國立臺灣大學
資訊工程學研究所
103
There are a few existing annotation systems that aim to provide a platform for video annotation. Most of them focus on activity annotation while others concentrate on labeling individual objects. However, the latters focus on only labeling objects with bounding boxes or only using interpolation techniques to help user labeling. Moreover, only one of them try to find the dense correspondence inside the object contour. Issues of dense correspondences annotation across video frames are not well addressed yet. Inspired by this, a video annotation system that focuses on dense correspondences annotation inside the object contour is proposed in this work. In addition, since labeling detail object contour and dense correspondences across a whole video is a daunting task, we also minimize user''s effort by applying an interactive segmentation and tracking algorithm that utilizes information from optical flow and edges that helps the user easier to observe the salient feature correspondences between two video frames. Edges could help the user to find out the detail contour or local patterns of the object. The user is required to check and modify the salient feature correspondences obtained by the algorithm. Dense correspondences in the textureless region are extracted by a non-rigid registration algorithm from the salient feature correspondences verified by the user. The user only needs to label the first frame of the video and correct some minor errors in the subsequent frames for the whole video annotation. The result shows that the proposed framework is more suitable to label non-rigid objects.
Livros sobre o assunto "Constraints annotation"
Williams, Dana A. Contemporary African American Female Playwrights. Greenwood Publishing Group, Inc., 1998. http://dx.doi.org/10.5040/9798400631115.
Texto completo da fonteCapítulos de livros sobre o assunto "Constraints annotation"
Kasahara, Hidekazu, Mikihiko Mori, Masayuki Mukunoki e Michihiko Minoh. "Transportation Mode Annotation of Tourist GPS Trajectories Under Environmental Constraints". In Information and Communication Technologies in Tourism 2015, 523–35. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-14343-9_38.
Texto completo da fonteCao, Yu, Lili Ju e Song Wang. "Grain Segmentation of 3D Superalloy Images Using Multichannel EWCVT under Human Annotation Constraints". In Computer Vision – ECCV 2012, 244–57. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-33712-3_18.
Texto completo da fonteRudova, Hana. "Constraints with Variables’ Annotations and Constraint Hierarchies". In SOFSEM’ 98: Theory and Practice of Informatics, 409–18. Berlin, Heidelberg: Springer Berlin Heidelberg, 1998. http://dx.doi.org/10.1007/3-540-49477-4_33.
Texto completo da fonteWingen, Isabel, e Philipp Körner. "Effectiveness of Annotation-Based Static Type Inference". In Functional and Constraint Logic Programming, 74–93. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-75333-7_5.
Texto completo da fonteSassen, Claudia, e Peter Kühnlein. "Annotating Structural Constraints in Discourse Corpora". In Text, Speech and Dialogue, 435–42. Berlin, Heidelberg: Springer Berlin Heidelberg, 2005. http://dx.doi.org/10.1007/11551874_56.
Texto completo da fonteHan, Jiajie, Jiani Hu e Weihong Deng. "Constrained Spectral Clustering on Face Annotation System". In Communications in Computer and Information Science, 3–12. Singapore: Springer Singapore, 2016. http://dx.doi.org/10.1007/978-981-10-3002-4_1.
Texto completo da fonteDong, Yongquan, Qingzhong Li, Yongqing Zheng, Xiaoyang Xu e Yongxin Zhang. "Semantic Annotation of Web Objects Using Constrained Conditional Random Fields". In Web-Age Information Management, 28–39. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-14246-8_6.
Texto completo da fonteHughes, Jack, e Dominic Orchard. "Program Synthesis from Graded Types". In Programming Languages and Systems, 83–112. Cham: Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-57262-3_4.
Texto completo da fonteXiaoguang, Rui, Yuan Pingbo e Yu Nenghai. "Image Annotations Based on Semi-supervised Clustering with Semantic Soft Constraints". In Advances in Multimedia Information Processing - PCM 2006, 624–32. Berlin, Heidelberg: Springer Berlin Heidelberg, 2006. http://dx.doi.org/10.1007/11922162_72.
Texto completo da fonteDetyniecki, Marcin. "Browsing a Video with Simple Constrained Queries over Fuzzy Annotations". In Flexible Query Answering Systems, 282–88. Heidelberg: Physica-Verlag HD, 2001. http://dx.doi.org/10.1007/978-3-7908-1834-5_26.
Texto completo da fonteTrabalhos de conferências sobre o assunto "Constraints annotation"
Chen, Zhijun, Huimin Wang, Hailong Sun, Pengpeng Chen, Tao Han, Xudong Liu e Jie Yang. "Structured Probabilistic End-to-End Learning from Crowds". In Twenty-Ninth International Joint Conference on Artificial Intelligence and Seventeenth Pacific Rim International Conference on Artificial Intelligence {IJCAI-PRICAI-20}. California: International Joint Conferences on Artificial Intelligence Organization, 2020. http://dx.doi.org/10.24963/ijcai.2020/210.
Texto completo da fonteYuan, Jinhui, Jianmin Li e Bo Zhang. "Exploiting spatial context constraints for automatic image region annotation". In the 15th international conference. New York, New York, USA: ACM Press, 2007. http://dx.doi.org/10.1145/1291233.1291379.
Texto completo da fonteC. Ribeiro, Fabiola Goncalves, Achim Rettberg, Carlos E. Pereira, Charles Steinmetz e Michel S. Soares. "Non-functional Constraints Annotation to Real-Time Embedded System Design". In 2018 VIII Brazilian Symposium on Computing Systems Engineering (SBESC). IEEE, 2018. http://dx.doi.org/10.1109/sbesc.2018.00041.
Texto completo da fonteGuo, Kunpeng, Dennis Diefenbach, Antoine Gourru e Christophe Gravier. "Fine-tuning Strategies for Domain Specific Question Answering under Low Annotation Budget Constraints". In 2023 IEEE 35th International Conference on Tools with Artificial Intelligence (ICTAI). IEEE, 2023. http://dx.doi.org/10.1109/ictai59109.2023.00032.
Texto completo da fontePardo, Alejandro, Mengmeng Xu, Ali Thabet, Pablo Arbelaez e Bernard Ghanem. "BAOD: Budget-Aware Object Detection". In LatinX in AI at Computer Vision and Pattern Recognition Conference 2021. Journal of LatinX in AI Research, 2021. http://dx.doi.org/10.52591/lxai202106254.
Texto completo da fonteTrandabat, Diana. "SEMANTIC ROLE ANNOTATION FOR ELEARNING". In eLSE 2017. Carol I National Defence University Publishing House, 2017. http://dx.doi.org/10.12753/2066-026x-17-179.
Texto completo da fonteMullick, Ankan. "Exploring Multilingual Intent Dynamics and Applications". In Thirty-Second International Joint Conference on Artificial Intelligence {IJCAI-23}. California: International Joint Conferences on Artificial Intelligence Organization, 2023. http://dx.doi.org/10.24963/ijcai.2023/818.
Texto completo da fonteJin, Wanjun, Rui Shi e Tat-Seng Chua. "A semi-na�ve Bayesian method incorporating clustering with pair-wise constraints for auto image annotation". In the 12th annual ACM international conference. New York, New York, USA: ACM Press, 2004. http://dx.doi.org/10.1145/1027527.1027605.
Texto completo da fonteTejero, Javier Gamazo, Martin S. Zinkernagel, Sebastian Wolf, Raphael Sznitman e Pablo Márquez Neila. "Full or Weak Annotations? An Adaptive Strategy for Budget-Constrained Annotation Campaigns". In 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). IEEE, 2023. http://dx.doi.org/10.1109/cvpr52729.2023.01095.
Texto completo da fonteMa, Jiayao, Xinbo Jiang, Songhua Xu e Xueying Qin. "Hierarchical Temporal Multi-Instance Learning for Video-based Student Learning Engagement Assessment". In Thirtieth International Joint Conference on Artificial Intelligence {IJCAI-21}. California: International Joint Conferences on Artificial Intelligence Organization, 2021. http://dx.doi.org/10.24963/ijcai.2021/383.
Texto completo da fonteRelatórios de organizações sobre o assunto "Constraints annotation"
Ghanim, Murad, Joe Cicero, Judith K. Brown e Henryk Czosnek. Dissection of Whitefly-geminivirus Interactions at the Transcriptomic, Proteomic and Cellular Levels. United States Department of Agriculture, fevereiro de 2010. http://dx.doi.org/10.32747/2010.7592654.bard.
Texto completo da fonte