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Journal articles on the topic 'Training visivo'

Author: Grafiati

Published: 11 March 2023

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1

Konukseven, E. Ilhan, M. Ercument Önder, Erkan Mumcuoglu, and Reha Sukru Kisnisci. "Development of a Visio-Haptic Integrated Dental Training Simulation System." Journal of Dental Education 74, no. 8 (August 2010): 880–91. http://dx.doi.org/10.1002/j.0022-0337.2010.74.8.tb04945.x.

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Wei Lou, Wei Lou, Dewen Cheng Dewen Cheng, Luo Gu Luo Gu, Weihong Hou Weihong Hou, and Yongtian Wang Yongtian Wang. "Optical design and evaluation of Alvarez-type vision-training system." Chinese Optics Letters 16, no. 7 (2018): 072201. http://dx.doi.org/10.3788/col201816.072201.

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Glow, Steven D., Vincent J. Colucci, Douglas R. Allington, Curtis W. Noonan, and Earl C. Hall. "Managing Multiple-Casualty Incidents: A Rural Medical Preparedness Training Assessment." Prehospital and Disaster Medicine 28, no. 4 (April 18, 2013): 334–41. http://dx.doi.org/10.1017/s1049023x13000423.

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AbstractObjectiveThe objectives of this study were to develop a novel training model for using mass-casualty incident (MCI) scenarios that trained hospital and prehospital staff together using Microsoft Visio, images from Google Earth and icons representing first responders, equipment resources, local hospital emergency department bed capacity, and trauma victims. The authors also tested participants’ knowledge in the areas of communications, incident command systems (ICS), and triage.MethodsParticipants attended Managing Multiple-Casualty Incidents (MCIs), a one-day training which offered pre- and post-tests, two one-hour functional exercises, and four distinct, one-hour didactic instructional periods. Two MCI functional exercises were conducted. The one-hour trainings focused on communications, National Incident Management Systems/Incident Command Systems (NIMS/ICS) and professional roles and responsibilities in NIMS and triage. The trainings were offered throughout communities in western Montana. First response resource inventories and general manpower statistics for fire, police, Emergency Medical Services (EMS), and emergency department hospital bed capacity were determined prior to MCI scenario construction. A test was given prior to and after the training activities.ResultsA total of 175 firefighters, EMS, law enforcement, hospital personnel or other first-responders completed the pre- and post-test. Firefighters produced higher baseline scores than all other disciplines during pre-test analysis. At the end of the training all disciplines demonstrated significantly higher scores on the post-test when compared with their respective baseline averages. Improvements in post-test scores were noted for participants from all disciplines and in all didactic areas: communications, NIMS/ICS, and triage.ConclusionsMass-casualty incidents offer significant challenges for prehospital and emergency room workers. Fire, Police and EMS personnel must secure the scene, establish communications, define individuals’ roles and responsibilities, allocate resources, triage patients, and assign transport priorities. After emergency department notification and in advance of arrival, emergency department personnel must assess available physical resources and availability and type of manpower, all while managing patients already under their care. Mass-casualty incident trainings should strengthen the key, individual elements essential to well-coordinated response such as communications, incident management system and triage. The practice scenarios should be matched to the specific resources of the community. The authors also believe that these trainings should be provided with all disciplines represented to eliminate training “silos,” to allow for discussion of overlapping jurisdictional or organizational responsibilities, and to facilitate team building.GlowSD, ColucciVJ, AllingtonDR, NoonanCW, HallEC. Managing multiple-casualty incidents: a rural medical preparedness training assessment. Prehosp Disaster Med. 2013;28(4):1-8.

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Caicedo-Quiroz, Rosangela, and Julia Céspedez-Acuña. "HACIA UNA FORMACIÓN DEL TÉCNICO SUPERIOR ENENFERMERÍA DESDE UNA VISION SOCIO-PEDAGOGICA." Identidad Bolivariana 1, no. 1 (January 5, 2017): 22–32. http://dx.doi.org/10.37611/ib1ol122-32.

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Considerations are presented about the formation of the Higher Nursing Technician and the necessary preparation to perform in the social context in actions of health prevention. The ideas constitute a socio-pedagogical modeling proposed from the perspective of the community from a formative intentionality, a epistemological orientation and logical criteria of systematization of the contents and the practice, to identify and monitor, in a preventive manner, the problems of Health; therefore, it seeks to understand how to recognize, reduce or avoid artifices to that social reality is submitted daily, so, in the pedagogical order has three purposes: must know (knowledge), must know how to do: (skills) and must know how to coexist: (values): Its results will be specified in the follow-up of the research from the development of a strategy with the same ends. Keywords: community intervention, school context, community practice, work community and prevention.

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Vailland, Guillaume, Yoren Gaffary, Louise Devigne, Valérie Gouranton, Bruno Arnaldi, and Marie Babel. "Power Wheelchair Virtual Reality Simulator with Vestibular Feedback." Modelling, Measurement and Control C 81, no. 1-4 (December 31, 2020): 35–42. http://dx.doi.org/10.18280/mmc_c.811-407.

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Autonomy and the ability to maintain social activities can be challenging for people with disabilities experiencing reduced mobility. In the case of disabilities that impact mobility, power wheelchairs can help such people retain or regain autonomy. Nonetheless, driving a power wheelchair is a complex task that requires a combination of cognitive, visual and visuo-spatial abilities. In practice, people need to pass prior ability tests and driving training before being prescribed a power wheelchair by their therapist. Still, conventional training in occupational therapy can be insufficient for some people with severe cognitive and/or visio-spatial functions. As such, these people are often prevented from obtaining a power wheelchair prescription from their therapist due to safety concerns. In this context, driving simulators might be efficient and promising tools to provide alternative, adaptive, flexible, and safe training. In previous work, we proposed a Virtual Reality (VR) driving simula-integrating vestibular feedback to simulate wheelchair motion sensations. The performance and acceptability of a VR simulator rely on satisfying user Quality of Experience (QoE). Therefore, our simulator is designed to give the user a high Sense of Presence (SoP) and low Cyber-sickness. This paper presents a pilot study assessing the impact of the vestibular feedback provided on user QoE. Participants were asked to perform a driving task whilst in the simulator under two conditions: with and without vestibular feedback. User QoE is assessed through subjective questionnaires measuring user SoP and cyber-sickness. The results show that vestibular feedback activation increases SoP and decreases cyber-sickness. This study constitutes a mandatory step before clinical trials and, as such, only enrolled people without disabilities.

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Ríos Garit, Jesús, Yanet Pérez Surita, Aurelio Olmedilla Zafra, and Verónica Gómez-Espejo. "Psicología y lesiones deportivas: Un estudio en lanzadores de beisbol." Cuadernos de Psicología del Deporte 21, no. 1 (January 1, 2021): 102–18. http://dx.doi.org/10.6018/cpd.416351.

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Las lesiones constituyen uno de los principales problemas en el deporte debido a las repercusiones negativas sobre la salud y el rendimiento del deportista. Su etiología multifactorial requiere que sean abordadas también desde lo psicológico para comprender su comportamiento de manera integral y lograr mayores impactos en su prevención. La presente investigación se realizó con los lanzadores de béisbol de primera categoría de la provincia de Villa Clara, Cuba, con el propósito de determinar la relación entre las variables psicológicas asociadas al rendimiento del deportista y las lesiones. Se estudiaron un total de 48 lanzadores constituyendo una población heterogénea, integrada por deportistas noveles y de mayor experiencia competitiva. Se aplicó el Cuestionario de Aspectos Deportivos y Lesiones, el Inventario de Ansiedad Rasgo-Estado, el Inventario de Ansiedad Estado en Competición y el Inventario Psicológico de Ejecución Deportiva. Los resultados obtenidos muestran que los lanzadores estudiados presentan una baja percepción de la relación entre variables psicológicas y lesiones, constatando además que en la competición aparecen más lesiones que en los entrenamientos y que los deportistas con antecedentes de lesiones presentan diferencias significativas en el estado de determinadas variables psicológicas en comparación con los lanzadores que no se han lesionado. Estas diferencias se observan en la ansiedad estado en competición, la autoconfianza, el control del afrontamiento negativo, el control de la atención y el control visual e imaginativo. Injuries are one of the main problems in sport due to the negative impact on the health and performance of the athlete. Their multi-causal etiology requires that they also be approached from the psychological to understand their behavior in an integral way and achieve greater impacts in its prevention. The present investigation was carried out with the first category Baseball pitchers of the province of Villa Clara, Cuba, with the purpose of determining the relationship between the psychological variables associated with the athlete's performance and the injuries. A total of 48 pitchers were studied, constituting a heterogeneous population, made up of new athletes with greater competitive experience. The Sports Aspects and Injuries Questionnaire, the Trait-State Anxiety Inventory, the Competing State Anxiety Inventory and the Psychological Inventory of Sports Execution were applied. The results obtained show that the pitchers studied have a low perception of the relationship between psychological variables and injuries, also confirming that in the competition there are more injuries than in training. In addition, the results are displaying that athletes with a history of injuries and within these, the ones that most injuries have suffered, present significant differences in the status of certain psychological variables compared to pitchers who have not been injured. This difference can be observed in competition state anxiety, self-confidence, negative coping control, attention control, and visual and imaginative control. Le lesioni sono uno dei principali problemi negli sport a causa dell'impatto negativo sulla salute e sulle prestazioni dell'atleta. La loro eziologia multifattoriale richiede che vengano affrontati anche dal punto di vista psicologico per comprendere il loro comportamento in modo integrale e ottenere maggiori impatti nella sua prevenzione. La presente indagine è stata condotta con i lanciatori di baseball di prima categoria della provincia di Villa Clara con lo scopo di determinare la relazione tra le variabili psicologiche associate alla prestazione dell'atleta e le lesioni. Sono stati studiati un totale di 48 lanciatori, costituendo una popolazione eterogenea, composta da nuovi atleti con una maggiore esperienza competitiva. Sono stati applicati il questionario sugli aspetti sportivi e sugli infortuni, l'inventario dell'ansia trait-state, l'inventario dell'ansia di stato in competizione e l'inventario psicologico dell'esecuzione sportiva. I risultati ottenuti mostrano che i lanciatori studiati hanno una bassa percezione del rapporto tra variabili psicologiche e infortuni, confermando anche che nella competizione ci sono più infortuni che in allenamento e che gli atleti con una storia di infortuni e al loro interno, quelli che più le lesioni hanno sofferto, presentano differenze significative nello stato di alcune variabili psicologiche rispetto ai lanciatori che non sono stati feriti. Questa differenza può essere osservata in variabili come; l'ansia era in competizione, la fiducia in se stessi, il controllo del coping negativo, il controllo dell'attenzione e il controllo visivo e immaginativo. As lesões são um dos principais problemas do esporte devido ao impacto negativo na saúde e no desempenho do atleta. Sua etiologia multifatorial exige que eles também sejam abordados do ponto de vista psicológico para entender seu comportamento de maneira integral e obter maiores impactos em sua prevenção. A presente investigação foi realizada com a primeira categoria de lançadores de basebol da província de Villa Clara, Cuba, com o objetivo de determinar a relação entre as variáveis psicológicas associadas ao desempenho do atleta e as lesões. Foram estudados 48 lançadores, constituindo uma população heterogênea, composta por novos atletas com maior experiência competitiva. Foram aplicados o Questionário de Aspectos e Lesões Esportivas, o Inventário de Ansiedade Traço-Estado, o Inventário de Ansiedade Estado Competente e o Inventário Psicológico de Execução Esportiva. Os resultados obtidos mostram que os lançadores estudados têm uma baixa percepção da relação entre variáveis psicológicas e lesões, confirmando também que na competição há mais lesões do que nos treinos e que atletas com histórico de lesões e dentro delas, as que mais lesões sofridas apresentam diferenças significativas no status de certas variáveis psicológicas em comparação com lançadores que não foram feridos. Essa diferença pode ser observada na ansiedade do estado de competição, autoconfiança, controle negativo de enfrentamento, controle da atenção e controle visual e imaginativo.

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Przybył, Krzysztof, Piotr Boniecki, Krzysztof Koszela, Łukasz Gierz, and Mateusz Łukomski. "Computer vision and artificial neural network techniques for classification of damage in potatoes during the storage process." Czech Journal of Food Sciences 37, No. 2 (May 10, 2019): 135–40. http://dx.doi.org/10.17221/427/2017-cjfs.

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The research methodology consists of several stages to develop a noninvasive method of identifying the turgor of potato tubers during the storage. During the first stage, a graphic database (set of training data) has been created for selected varieties of potatoes. As a next step, special proprietary software called ’PID system’ was used together with a commercial MATLAB package to extract parameters defining the digital image descriptors. This included: hue space models, shape coefficient and image texture. Thirdly, Artificial Neural Network (ANN) training was conducted with the use of Statistica and MATLAB tools. As a result of the analysis, a neural model has been obtained, which had the greatest classification features.

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Jing Li, Jing Li, and Xueping Luo Jing Li. "Malware Family Classification Based on Vision Transformer." 電腦學刊 34, no. 1 (February 2023): 087–99. http://dx.doi.org/10.53106/199115992023023401007.

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<p>Cybersecurity worries intensify as Big Data, the Internet of Things, and 5G technologies develop. Based on code reuse technologies, malware creators are producing new malware quickly, and new malware is continually endangering the effectiveness of existing detection methods. We propose a vision transformer-based approach for malware picture identification because, in contrast to CNN, Transformer’s self-attentive process is not constrained by local interactions and can simultaneously compute long-range mine relationships. We use ViT-B/16 weights pre-trained on the ImageNet21k dataset to improve model generalization capability and fine-tune them for the malware image classification task. This work demonstrates that (i) a pure attention mechanism applies to malware recognition, and (ii) the Transformer can be used instead of traditional CNN for malware image recognition. We train and assess our models using the MalImg dataset and the BIG2015 dataset in this paper. Our experimental evaluation found that the recognition accuracy of transfer learning-based ViT for MalImg samples and BIG2015 samples is 99.14% and 98.22%, respectively. This study shows that training ViT models using transfer learning can perform better than CNN in malware family classification.</p> <p> </p>

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Su, Chen, Ao Chai, Xikai Tu, Hongyu Zhou, Haiqiang Wang, Zufang Zheng, Jingyan Cao, and Jiping He. "Passive and Active Control Strategies of a Leg Rehabilitation Exoskeleton Powered by Pneumatic Artificial Muscles." International Journal of Pattern Recognition and Artificial Intelligence 31, no. 10 (March 9, 2017): 1759021. http://dx.doi.org/10.1142/s0218001417590212.

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Nerve injury can cause lower limb paralysis and gait disorder. Currently lower limb rehabilitation exoskeleton robots used in the hospitals need more power to correct abnormal motor patterns of stroke patients’ legs. These gait rehabilitation robots are powered by cumbersome and bulky electric motors, which provides a poor user experience. A newly developed gait rehabilitation exoskeleton robot actuated by low-cost and lightweight pneumatic artificial muscles (PAMs) is presented in this research. A model-free proxy-based sliding mode control (PSMC) strategy and a model-based chattering mitigation robust variable control (CRVC) strategy were developed and first applied in rehabilitation trainings, respectively. As the dynamic response of PAM due to the compressed air is low, an innovative intention identification control strategy was taken in active trainings by the use of the subject’s intention indirectly through the estimation of the interaction force between the subject’s leg and the exoskeleton. The proposed intention identification strategy was verified by treadmill-based gait training experiments.

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CAILLAULT, EMILIE, and CHRISTIAN VIARD-GAUDIN. "MIXED DISCRIMINANT TRAINING OF HYBRID ANN/HMM SYSTEMS FOR ONLINE HANDWRITTEN WORD RECOGNITION." International Journal of Pattern Recognition and Artificial Intelligence 21, no. 01 (February 2007): 117–34. http://dx.doi.org/10.1142/s0218001407005338.

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Online handwritten word recognition systems usually rely on Hidden Markov Models (HMMs), which are effective under many circumstances, but suffer some major limitations in real world applications. Artificial neural networks (ANN) appear to be a promising alternative, however they failed to model sequence data such as online handwriting due to their variable lengths. As a consequence, by combining HMMs and ANN, we can expect to take advantage of the robustness and flexibility of the HMMs generative models and of the discriminative power of the ANN. Training such a hybrid system is not straightforward, this is why so few attempts are encountered in literature. We compare several different training schemes: maximum likelihood (ML) and maximum mutual information (MMI) criteria in the framework of online handwriting recognition with a global optimization approach defined at the word level. A new generic criterion mixing generative model and discriminant trainings is proposed, it allows to train a multistate TDNN-HMM system directly at the word level. This architecture is based on an analytical approach with an implicit segmentation. To control the implicit segmentation and to initialize correctly the system without bootstrapping with another recognition system, we have defined a process that constraints the segmentation path and a measure called Average Segmentation Rate (ASR). Recognition experiments on the online IRONOFF database demonstrated the interest of the generic training criterion and the control of the implicit segmentation.

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Chen, Berlin, Shih-Hung Liu, and Fang-Hui Chu. "Training data selection for improving discriminative training of acoustic models." Pattern Recognition Letters 30, no. 13 (October 2009): 1228–35. http://dx.doi.org/10.1016/j.patrec.2009.05.009.

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Shang, Huanan. "TARGET TRACKING IN COMPLEX SCENES BASED ON COMPUTER VISION." Revista Brasileira de Medicina do Esporte 28, no. 5 (October 2022): 436–39. http://dx.doi.org/10.1590/1517-8692202228052021_0532.

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ABSTRACT Objective: Use the deep learning network model to identify key content in videos. Methodology: After reviewing the literature on computer vision, the feature extraction of the target video from the network using deep learning with the time-series data enhancement method was performed. The preprocessing method for data augmentation and Spatio-temporal feature extraction on the video based on LI3D network was explained. Accuracy rate, precision, and recall were used as indices. Results: The three indicators increased from 0.85, 0.88, and 0.84 to 0.89, 0.90, and 0.88, respectively. This shows that the LI3D network model maintains a high recall rate accompanied by high accuracy after data augmentation. The accuracy and loss function curves of the training phase show that the accuracy of the network is greatly improved compared to I3D. Conclusion: The experiment proves that the LI3D model is more stable and has faster convergence. By comparing the accuracy curve and loss function curve during LI3D, LI3D-LSTM, and LI3D-BiLSTM training, it is found that the LI3D-BiLSTM model converges faster. Level of evidence II; Therapeutic studies - investigation of treatment results.

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PIATER, JUSTUS H., EDWARD M. RISEMAN, and PAUL E. UTGOFF. "INTERACTIVELY TRAINING PIXEL CLASSIFIERS." International Journal of Pattern Recognition and Artificial Intelligence 13, no. 02 (March 1999): 171–93. http://dx.doi.org/10.1142/s0218001499000112.

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For typical classification tasks, all training data are prepared in advance and are supplied to the classifier all at once. This is unnecessarily expensive and incurs overfitting problems, since the individual contributions of the training instances to the classifier are not known. We address this by proposing an interactive incremental framework for image classifier construction, where small numbers of training examples are supplied at each user interaction. After incorporating new training instances, the classifier immediately reclassifies the image to provide the user with instant feedback. This allows the user to choose additional informative training pixels from among the currently misclassified ones. Using a realistic terrain classification task, we demonstrate the potential of our method to generate small and accurate decision tree classifiers from surprisingly few training examples while avoiding overspecialization. We also briefly discuss the novel concept of hierarchical classification, where higher-level classifiers take as input the output of lower-level classifiers. We present preliminary results indicating that within our interactive framework, this is a practical approach to exploiting spatial relationships for classification.

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Klisarić, Dragan. "The influence of external and internal factors on the squat jump height." Fizicka kultura 74, no. 1 (2020): 19–29. http://dx.doi.org/10.5937/fizkul2001019k.

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Squat jump is an important tool - an exercise that determines power of kinetic chain muscle groups which leads to jump height. Science and practice registered numerous factors that influence the squat jump height, the most important are set out and described. The aim of this article was to describe and explain the influence of external and internal factors on the squat jump height. The paper compares and comments on the results of available domestic and foreign scientific research. The analysis of the researched sources concluded that the greatest influence on the squat jump height among the external factors has the way of performance, while the greatest influence among internal factors has growth. The results of this article can be used to improve the quality of directing and abilities testing as well as the training process to achieve the best in sports and sports branches.

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Li, Wanwan, Haikun Huang, Tomay Solomon, Behzad Esmaeili, and Lap-Fai Yu. "Synthesizing Personalized Construction Safety Training Scenarios for VR Training." IEEE Transactions on Visualization and Computer Graphics 28, no. 5 (May 2022): 1993–2002. http://dx.doi.org/10.1109/tvcg.2022.3150510.

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Kim, SungYe, Ross Maciejewski, Karl Ostmo, Edward J. Delp, Timothy F. Collins, and David S. Ebert. "Mobile Analytics for Emergency Response and Training." Information Visualization 7, no. 1 (February 14, 2008): 77–88. http://dx.doi.org/10.1057/palgrave.ivs.9500168.

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During emergency response events, situational awareness is critical in effectively managing and safe-guarding civilians and in-field personnel. To better support both command center controllers and in-field operators, we have developed a mobile visual analytics tool to help enhance situational awareness and support rapid decision making. Our mobile visual analytics tool consists of a 2D/3D visualization component, which shows personnel-related information, situational and static scene-related information, integrated multi media playback functionality for personnel outfitted with cameras, and fast-forward/rewind capabilities for reviewing events. Our current system has been employed in the evaluation of two different scenarios: a simulated evacuation of The Station nightclub fire that occurred in Rhode Island during 2003 and a testing exercise for a rescue operation in an elementary school. Our system has been deployed on a Dell Axim X51v PDA, an OQO 02, and on a Sprint PCS Vision SM smart device PPC-6700.

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Galvez-Johnson, Myrna. "Media education in Iberoamerica: the vision of the experts." Comunicar 12, no. 24 (March 1, 2005): 35–40. http://dx.doi.org/10.3916/c24-2005-06.

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In the Iberoamerican context the need for the mass media integration in formal education and teacher training is increasing. This paper presents and analyzes the main results of the diagnosis stage of the research «Towards an iberoamerican curriculum of media education». The research purpose is to generate a framework for the situation of media education in some countries based on twenty six experts´ opinions. En el contexto iberoamericano se hace cada vez más necesaria la integración de los medios de comunicación en la educación formal y en la formación docente. El presente artículo da cuenta y analiza los principales resultados de la etapa de diagnóstico de la investigación «Hacia un currículo iberoamericano de educación en medios» que tuvo la finalidad de generar un marco de referencia respecto a la situación de la educación en medios en diferentes países a partir de las opiniones de 26 expertos en el área.

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Kataoka, Hirokatsu, Kazushige Okayasu, Asato Matsumoto, Eisuke Yamagata, Ryosuke Yamada, Nakamasa Inoue, Akio Nakamura, and Yutaka Satoh. "Pre-Training Without Natural Images." International Journal of Computer Vision 130, no. 4 (February 24, 2022): 990–1007. http://dx.doi.org/10.1007/s11263-021-01555-8.

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AbstractIs it possible to use convolutional neural networks pre-trained without any natural images to assist natural image understanding? The paper proposes a novel concept, Formula-driven Supervised Learning (FDSL). We automatically generate image patterns and their category labels by assigning fractals, which are based on a natural law. Theoretically, the use of automatically generated images instead of natural images in the pre-training phase allows us to generate an infinitely large dataset of labeled images. The proposed framework is similar yet different from Self-Supervised Learning because the FDSL framework enables the creation of image patterns based on any mathematical formulas in addition to self-generated labels. Further, unlike pre-training with a synthetic image dataset, a dataset under the framework of FDSL is not required to define object categories, surface texture, lighting conditions, and camera viewpoint. In the experimental section, we find a better dataset configuration through an exploratory study, e.g., increase of #category/#instance, patch rendering, image coloring, and training epoch. Although models pre-trained with the proposed Fractal DataBase (FractalDB), a database without natural images, do not necessarily outperform models pre-trained with human annotated datasets in all settings, we are able to partially surpass the accuracy of ImageNet/Places pre-trained models. The FractalDB pre-trained CNN also outperforms other pre-trained models on auto-generated datasets based on FDSL such as Bezier curves and Perlin noise. This is reasonable since natural objects and scenes existing around us are constructed according to fractal geometry. Image representation with the proposed FractalDB captures a unique feature in the visualization of convolutional layers and attentions.

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DONG, JIAN-XIONG, CHING Y. SUEN, and ADAM KRZYŻAK. "A FAST SVM TRAINING ALGORITHM." International Journal of Pattern Recognition and Artificial Intelligence 17, no. 03 (May 2003): 367–84. http://dx.doi.org/10.1142/s0218001403002423.

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A fast support vector machine (SVM) training algorithm is proposed under SVM's decomposition framework by effectively integrating kernel caching, digest and shrinking policies and stopping conditions. Kernel caching plays a key role in reducing the number of kernel evaluations by maximal reusage of cached kernel elements. Extensive experiments have been conducted on a large handwritten digit database MNIST to show that the proposed algorithm is much faster than Keerthi et al.'s improved SMO, about nine times. Combined with principal component analysis, the total training for ten one-against-the-rest classifiers on MNIST took less than an hour. Moreover, the proposed fast algorithm speeds up SVM training without sacrificing the generalization performance. The 0.6% error rate on MNIST test set has been achieved. The promising scalability of the proposed scheme paves a new way to solve more large-scale learning problems in other domains such as data mining.

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Han, Yan, Soumava Kumar Roy, Lars Petersson, and Mehrtash Harandi. "Discrepant collaborative training by Sinkhorn divergences." Image and Vision Computing 112 (August 2021): 104213. http://dx.doi.org/10.1016/j.imavis.2021.104213.

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Tarabrina, Natal`ya. "Peculiarities of physiological fitness of differently skilled football referees." SCIENCE AND SPORT: current trends 7, no. 3 (September 2019): 58–65. http://dx.doi.org/10.36028/2308-8826-2019-7-3-58-65.

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The goal: comparative analysis of psycho-physiological fitness of football players and differently skilled football referees. Research materials and methods. We studied indicators of psychomotor status, the level of development of speed and volitional qualities, subject-activity and communicative aspects of temperament of 15 football players aged 19-21, with the experience of sport training from 10 to 13 years, and 25 football referees of the first rank aged 25-32, with the experience of refereeing from 5 to 9 years. We compared the outcomes to identify the trend of convergence of the level of studied indicators. Research results and discussion. The study has demonstrated that about 50% of all subjects have a medium-weak type of nervous system, but there are referees with a strong type (16%). We have revealed that football players and referees have no significant difference in the period of implementation of the audio-motor reaction. Visio-motor reaction of football players is 16.44 ± 0.45 msec, which is faster than the reaction of referees by 10.6% (p <0.05). Repeated sprint ability of referees and players was not significantly different, average indicator at 40 m intervals was 5.63 sec. for referees and 5.25 sec. for players. Football referees demonstrate a very high work pace - 10.3 ± 0.32 c.u., life pace, activity, high rhythm of operations. Emotional background of players at work and in social communication was 6.0±0,59 c.u. and of 6.80 c.u. respectively, and it was twice higher than the indicators of referees (p< 0.001). Vitality indicators were the same for both groups. Conclusion. Modern football requires that a referee should obtain a new, higher level of physical and psychological training. Most of the quantitative indicators of the studied parameters of players and referees did not have significant difference, while the moral-volitional and emotional components differed significantly.

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Mohandes, M., S. Rehman, H. Nuha, M. S. Islam, and F. H. Schulze. "Accuracy of wind speed predictability with heights using Recurrent Neural networks." FME Transactions 49, no. 4 (2021): 908–18. http://dx.doi.org/10.5937/fme2104908m.

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Accurate prediction of wind speed in future time domain is critical for wind power integration into the grid. Wind speed is usually measured at lower heights while the hub heights of modern wind turbines are much higher in the range of 80-120m. This study attempts to better understand the predictability of wind speed with height. To achieve this, wind data was collected using Laser Illuminated Detection and Ranging (LiDAR) system at 20m, 40m, 50m, 60m, 80m, 100m, 120m, 140m, 160m, and 180m heights. This hourly averaged data is used for training and testing a Recurrent Neural Network (RNN) for the prediction of wind speed for each of the future 12 hours, using 48 previous values. Detailed analyses of short-term wind speed prediction at different heights and future hours show that wind speed is predicted more accurately at higher heights.For example, the mean absolute percent error decreases from 0.19 to 0.16as the height increase from 20m to 180m, respectively for the 12 th future hour prediction. The performance of the proposed method is compared with Multilayer Perceptron (MLP) method. Results show that RNN performed better than MLP for most of the cases presented here at the future 6th hour.

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Etchegaray Pezo, Paulo, Gema Pascual Hoyuelos, and Olga Calderón Aedo. "Teaching of generic competences in general training courses of a Chilean university: The vision of students and teachers." Revista Internacional de Investigación en Ciencias Sociales 14, no. 1 (July 30, 2018): 77–88. http://dx.doi.org/10.18004/riics.2018.julio.077-088.

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Li, Ziqiang, Mingtian Zhou, Hao Lin, and Haibo Pu. "A two stages sparse SVM training." International Journal of Machine Learning and Cybernetics 5, no. 3 (July 3, 2013): 425–34. http://dx.doi.org/10.1007/s13042-013-0181-5.

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Petra, Hlaváčková, Slováčková Hana, Březina David, and Michal Jakub. "Comparison of results of visitor arrival monitoring using regression analysis." Journal of Forest Science 64, No. 7 (August 1, 2018): 303–12. http://dx.doi.org/10.17221/20/2018-jfs.

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Monitoring of visitor arrivals is one of the tools which help to ensure good-quality and suitable management of the respective area. This paper is aimed at the monitoring of visitor arrivals when the visitors are counted automatically using a field counting device, namely a pyroelectric sensor. In 2015, visitor arrival monitoring using a pyro sensor was conducted on the selected forest roads in the Křtiny Training Forest Enterprise of Masaryk Forest. Since this method should be employed in another project, it was necessary to find out whether the pyroelectric sensor is a reliable tool and whether it can be used for further research. The aim of this paper is to perform a regression analysis of the data collected at the selected site in order to determine whether the pyroelectric sensor provides relevant information. Two data sets acquired during the first week of the monitoring of visitor arrivals at the single site will be compared. The one set includes data obtained by automatic monitoring using the pyro sensor, the other set contains data gained by means of manual counting by students of the Faculty of Forestry and Wood Technology. Two directions of visitor flows were monitored – in and out. The data were statistically processed using the ADSTAT software. Results of the regression analysis show that the results of the visitor arrival monitoring carried out using a pyro sensor differ just slightly from those gained by manual counting.

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Clausner, Christian, Apostolos Antonacopoulos, and Stefan Pletschacher. "Efficient and effective OCR engine training." International Journal on Document Analysis and Recognition (IJDAR) 23, no. 1 (October 30, 2019): 73–88. http://dx.doi.org/10.1007/s10032-019-00347-8.

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Abstract We present an efficient and effective approach to train OCR engines using the Aletheia document analysis system. All components required for training are seamlessly integrated into Aletheia: training data preparation, the OCR engine’s training processes themselves, text recognition, and quantitative evaluation of the trained engine. Such a comprehensive training and evaluation system, guided through a GUI, allows for iterative incremental training to achieve best results. The widely used Tesseract OCR engine is used as a case study to demonstrate the efficiency and effectiveness of the proposed approach. Experimental results are presented validating the training approach with two different historical datasets, representative of recent significant digitisation projects. The impact of different training strategies and training data requirements is presented in detail.

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Guo, Zhizhi, Qianxiang Zhou, Zhongqi Liu, and Chunhui Liu. "Training‐based head pose estimation under monocular vision." IET Computer Vision 10, no. 8 (June 30, 2016): 798–805. http://dx.doi.org/10.1049/iet-cvi.2015.0457.

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Le, T. Hoang Ngan, Khoa Luu, Chenchen Zhu, and Marios Savvides. "Semi self-training beard/moustache detection and segmentation simultaneously." Image and Vision Computing 58 (February 2017): 214–23. http://dx.doi.org/10.1016/j.imavis.2016.07.009.

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Licsár, Attila, and Tamás Szirányi. "User-adaptive hand gesture recognition system with interactive training." Image and Vision Computing 23, no. 12 (November 2005): 1102–14. http://dx.doi.org/10.1016/j.imavis.2005.07.016.

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Cootes, T. F., C. J. Taylor, D. H. Cooper, and J. Graham. "Active Shape Models-Their Training and Application." Computer Vision and Image Understanding 61, no. 1 (January 1995): 38–59. http://dx.doi.org/10.1006/cviu.1995.1004.

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Choi, Woonjae, and Bummo Ahn. "A Flexible Sensor for Suture Training." IEEE Robotics and Automation Letters 4, no. 4 (October 2019): 4539–46. http://dx.doi.org/10.1109/lra.2019.2933995.

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Fischer, Asja, and Christian Igel. "Training restricted Boltzmann machines: An introduction." Pattern Recognition 47, no. 1 (January 2014): 25–39. http://dx.doi.org/10.1016/j.patcog.2013.05.025.

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Li, Hongzhu, and Weiqiang Wang. "Reinterpreting CTC training as iterative fitting." Pattern Recognition 105 (September 2020): 107392. http://dx.doi.org/10.1016/j.patcog.2020.107392.

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Torres-Barrán, Alberto, Carlos M. Alaíz, and José R. Dorronsoro. "Faster SVM training via conjugate SMO." Pattern Recognition 111 (March 2021): 107644. http://dx.doi.org/10.1016/j.patcog.2020.107644.

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Negnevitsky, Michael, and Martin J. Ringrose. "Fuzzy Control of Back-Propagation Training." Journal of Advanced Computational Intelligence and Intelligent Informatics 4, no. 6 (November 20, 2000): 408–11. http://dx.doi.org/10.20965/jaciii.2000.p0408.

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A fuzzy logic controller for updating training parameters in the error back-propagation algorithm is presented. The controller is based on heuristic rules for speeding up the convergence of training process, incorporating both learning rate and momentum constant changes.

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Bloomfield, Aaron, and Norman I. Badler. "Virtual Training via Vibrotactile Arrays." Presence: Teleoperators and Virtual Environments 17, no. 2 (April 1, 2008): 103–20. http://dx.doi.org/10.1162/pres.17.2.103.

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What is often missing from many virtual worlds and training simulations is a physical sense of the confinement and constraint of the virtual environment. We present a method for providing localized cutaneous vibratory feedback to the user's right arm. We created a sleeve of tactors linked to a real-time human model; the tactors activate to apply sensation to the corresponding body area. The hypothesis is that vibrotactile feedback to body areas provides the wearer sufficient guidance to assume correct body configurations and ascertain the existence and physical realism of access paths. We present the results of human subject experiments that study both explicit and implicit training of skills using vibrotactile arrays. Implicitly, collision awareness is achieved by activating the appropriate tactor when a body part collides with the scene; thus, the user will attempt to correct his or her body configuration. Explicitly, we use the tactors to guide the body into the proper configuration. The results of human subject experiments clearly show that the use of full arm vibrotactile feedback improves performance over purely visual feedback for navigating the virtual environment, as well as allowing easy acquisition of new skills. These results validate the empirical performance of this concept.

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Gan, Zhe, Linjie Li, Chunyuan Li, Lijuan Wang, Zicheng Liu, and Jianfeng Gao. "Vision-Language Pre-Training: Basics, Recent Advances, and Future Trends." Foundations and Trends® in Computer Graphics and Vision 14, no. 3–4 (2022): 163–352. http://dx.doi.org/10.1561/0600000105.

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GALES, M. J. F. "Training Augmented Models Using SVMs." IEICE Transactions on Information and Systems E89-D, no. 3 (March 1, 2006): 892–99. http://dx.doi.org/10.1093/ietisy/e89-d.3.892.

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Wang, Zhijie, Wei Zhang, Xuewen Rong, and Yibin Li. "Salient object detection with adversarial training." IET Image Processing 13, no. 14 (December 12, 2019): 2859–65. http://dx.doi.org/10.1049/iet-ipr.2018.6581.

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YU, CHANGHUA, MICHAEL T. MANRY, and JIANG LI. "EFFECTS OF NONSINGULAR PREPROCESSING ON FEEDFORWARD NETWORK TRAINING." International Journal of Pattern Recognition and Artificial Intelligence 19, no. 02 (March 2005): 217–47. http://dx.doi.org/10.1142/s0218001405004022.

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In the neural network literature, many preprocessing techniques, such as feature de-correlation, input unbiasing and normalization, are suggested to accelerate multilayer perceptron training. In this paper, we show that a network trained with an original data set and one trained with a linear transformation of the original data will go through the same training dynamics, as long as they start from equivalent states. Thus preprocessing techniques may not be helpful and are merely equivalent to using a different weight set to initialize the network. Theoretical analyses of such preprocessing approaches are given for conjugate gradient, back propagation and the Newton method. In addition, an efficient Newton-like training algorithm is proposed for hidden layer training. Experiments on various data sets confirm the theoretical analyses and verify the improvement of the new algorithm.

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Ng, Wing W. Y., Yuxi Tuo, Jianjun Zhang, and Sam Kwong. "Training error and sensitivity-based ensemble feature selection." International Journal of Machine Learning and Cybernetics 11, no. 10 (April 13, 2020): 2313–26. http://dx.doi.org/10.1007/s13042-020-01120-8.

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42

Aghababaei, Somayyeh, and Masoud Makrehchi. "Interpolative self-training approach for link prediction." Intelligent Data Analysis 23, no. 6 (November 8, 2019): 1379–95. http://dx.doi.org/10.3233/ida-184390.

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43

Mutlu, Uras, and Ethem Alpaydın. "Training bidirectional generative adversarial networks with hints." Pattern Recognition 103 (July 2020): 107320. http://dx.doi.org/10.1016/j.patcog.2020.107320.

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Zhu, Fangming, and Steven Guan. "Ordered incremental training for GA-based classifiers." Pattern Recognition Letters 26, no. 14 (October 2005): 2135–51. http://dx.doi.org/10.1016/j.patrec.2005.04.001.

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45

Gupta, Lalit, Jiesheng Wang, Alain Charles, and Paul Kisatsky. "Prototype selection rules for neural network training." Pattern Recognition 25, no. 11 (November 1992): 1401–8. http://dx.doi.org/10.1016/0031-3203(92)90152-9.

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46

Hu, Jinglu, Kotaro Hirasawa, and Junichi Murata. "RasID - Random Search for Neural Network Training." Journal of Advanced Computational Intelligence and Intelligent Informatics 2, no. 4 (August 20, 1998): 134–41. http://dx.doi.org/10.20965/jaciii.1998.p0134.

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This paper presents a novel random search, RasID, for neural network training, that introduces a sophisticated probability density function (PDF) in a random search for generating search vectors. The PDF provides two parameters to control local search ranges and directions efficiently. This realizes an intensified search where it is easy to find good solutions locally or a diversified search to escape local minima based on success-failure of past searches. Local gradients, if available, and trend information on the criterion function surface are used to improve search performance. The proposed scheme is applied to layered neural network training and is benchmarked against deterministic and nondeterministic methods.

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Akiyama, Hidehisa, Daisuke Katagami, and Katsumi Nitta. "Training of Agent Positioning Using Human’s Instruction." Journal of Advanced Computational Intelligence and Intelligent Informatics 11, no. 8 (October 20, 2007): 998–1006. http://dx.doi.org/10.20965/jaciii.2007.p0998.

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In the real-world multiagent/multirobot problems, a position of each agent is an important factor to affect agents’ performance. In the real-world problem such as soccer, the agent(player)’s position should be changed based on the current environmental state. Because the real-world problem is generally dynamic and continuous, assigning the most desirable position for any state is not possible. We formalize this issue as a map from a focal point like a ball position in a soccer field to a desirable position of each agent. We conducted experiments showing that agent positioning are acquired efficiently through intuitive human operation and function approximation models using supervised learning, and conducted performance evaluation experiments to determine the most suitable model. In performance evaluation experiments, we evaluated the generalization capability for each model with datasets which several data are randomly removed from original dataset and dataset which several specific data are intentionally removed from original dataset. Experiment results showed that our proposed function approximation model combining Delaunay triangulation and linear interpolation produced the highest performance.

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48

Sher, David B., and Chris Y. Cheung. "Constructing noise-reducing operators from training images." Pattern Recognition Letters 15, no. 4 (April 1994): 357–63. http://dx.doi.org/10.1016/0167-8655(94)90084-1.

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49

Bilmes, J. A., and K. Kirchhoff. "Generalized rules for combination and joint training of classifiers." Pattern Analysis & Applications 6, no. 3 (December 1, 2003): 201–11. http://dx.doi.org/10.1007/s10044-002-0188-0.

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GENOV, ROMAN, SHANTANU CHAKRABARTTY, and GERT CAUWENBERGHS. "SILICON SUPPORT VECTOR MACHINE WITH ON-LINE LEARNING." International Journal of Pattern Recognition and Artificial Intelligence 17, no. 03 (May 2003): 385–404. http://dx.doi.org/10.1142/s0218001403002472.

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Training of support vector machines (SVMs) amounts to solving a quadratic programming problem over the training data. We present a simple on-line SVM training algorithm of complexity approximately linear in the number of training vectors, and linear in the number of support vectors. The algorithm implements an on-line variant of sequential minimum optimization (SMO) that avoids the need for adjusting select pairs of training coefficients by adjusting the bias term along with the coefficient of the currently presented training vector. The coefficient assignment is a function of the margin returned by the SVM classifier prior to assignment, subject to inequality constraints. The training scheme lends efficiently to dedicated SVM hardware for real-time pattern recognition, implemented using resources already provided for run-time operation. Performance gains are illustrated using the Kerneltron, a massively parallel mixed-signal VLSI processor for kernel-based real-time video recognition.

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