Download or read book Computer Vision and Deep Learning Methods for Measuring and Modeling Animal Behavior written by Jacob M. Graving and published by . This book was released on 2021 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Efficient Computer Vision and Machine Learning Methods for Automating Large scale Analysis of Collective Animal Behavior written by Tristan Leonard Walter and published by . This book was released on 2022 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Methods of Behavior Analysis in Neuroscience written by Jerry J. Buccafusco and published by CRC Press. This book was released on 2000-08-29 with total page 341 pages. Available in PDF, EPUB and Kindle. Book excerpt: Using the most well-studied behavioral analyses of animal subjects to promote a better understanding of the effects of disease and the effects of new therapeutic treatments on human cognition, Methods of Behavior Analysis in Neuroscience provides a reference manual for molecular and cellular research scientists in both academia and the pharmaceutic
Download or read book Interpretable Machine Learning written by Christoph Molnar and published by Lulu.com. This book was released on 2020 with total page 320 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is about making machine learning models and their decisions interpretable. After exploring the concepts of interpretability, you will learn about simple, interpretable models such as decision trees, decision rules and linear regression. Later chapters focus on general model-agnostic methods for interpreting black box models like feature importance and accumulated local effects and explaining individual predictions with Shapley values and LIME. All interpretation methods are explained in depth and discussed critically. How do they work under the hood? What are their strengths and weaknesses? How can their outputs be interpreted? This book will enable you to select and correctly apply the interpretation method that is most suitable for your machine learning project.
Download or read book Neural Networks and Animal Behavior written by Magnus Enquist and published by Princeton University Press. This book was released on 2013-12-03 with total page 256 pages. Available in PDF, EPUB and Kindle. Book excerpt: How can we make better sense of animal behavior by using what we know about the brain? This is the first book that attempts to answer this important question by applying neural network theory. Scientists create Artificial Neural Networks (ANNs) to make models of the brain. These networks mimic the architecture of a nervous system by connecting elementary neuron-like units into networks in which they stimulate or inhibit each other's activity in much the same way neurons do. This book shows how scientists can employ ANNs to analyze animal behavior, explore the general principles of the nervous systems, and test potential generalizations among species. The authors focus on simple neural networks to show how ANNs can be investigated by math and by computers. They demonstrate intuitive concepts that make the operation of neural networks more accessible to nonspecialists. The first chapter introduces various approaches to animal behavior and provides an informal introduction to neural networks, their history, and their potential advantages. The second chapter reviews artificial neural networks, including biological foundations, techniques, and applications. The following three chapters apply neural networks to such topics as learning and development, classical instrumental condition, and the role of genes in building brain networks. The book concludes by comparing neural networks to other approaches. It will appeal to students of animal behavior in many disciplines. It will also interest neurobiologists, cognitive scientists, and those from other fields who wish to learn more about animal behavior.
Download or read book Machine Learning for Vision Based Motion Analysis written by Liang Wang and published by Springer. This book was released on 2010-11-23 with total page 372 pages. Available in PDF, EPUB and Kindle. Book excerpt: Techniques of vision-based motion analysis aim to detect, track, identify, and generally understand the behavior of objects in image sequences. With the growth of video data in a wide range of applications from visual surveillance to human-machine interfaces, the ability to automatically analyze and understand object motions from video footage is of increasing importance. Among the latest developments in this field is the application of statistical machine learning algorithms for object tracking, activity modeling, and recognition. Developed from expert contributions to the first and second International Workshop on Machine Learning for Vision-Based Motion Analysis, this important text/reference highlights the latest algorithms and systems for robust and effective vision-based motion understanding from a machine learning perspective. Highlighting the benefits of collaboration between the communities of object motion understanding and machine learning, the book discusses the most active forefronts of research, including current challenges and potential future directions. Topics and features: provides a comprehensive review of the latest developments in vision-based motion analysis, presenting numerous case studies on state-of-the-art learning algorithms; examines algorithms for clustering and segmentation, and manifold learning for dynamical models; describes the theory behind mixed-state statistical models, with a focus on mixed-state Markov models that take into account spatial and temporal interaction; discusses object tracking in surveillance image streams, discriminative multiple target tracking, and guidewire tracking in fluoroscopy; explores issues of modeling for saliency detection, human gait modeling, modeling of extremely crowded scenes, and behavior modeling from video surveillance data; investigates methods for automatic recognition of gestures in Sign Language, and human action recognition from small training sets. Researchers, professional engineers, and graduate students in computer vision, pattern recognition and machine learning, will all find this text an accessible survey of machine learning techniques for vision-based motion analysis. The book will also be of interest to all who work with specific vision applications, such as surveillance, sport event analysis, healthcare, video conferencing, and motion video indexing and retrieval.
Download or read book Computer Vision Systems written by Henrik I. Christensen and published by Springer Nature. This book was released on 2023-09-20 with total page 466 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume LNCS 14253 constitutes the refereed proceedings of the 14th International Conference, ICVS 2023, in Vienna, Austria, in September 2023.. The 37 full papers presented were carefully reviewed and selected from 74 submissions. The conference focuses on Humans and Hands; Medical and Health Care; Farming and Forestry; Automation and Manufacturing; Mobile Robotics and Autonomous Systems; and Performance and Robustness.
Download or read book Computer Vision and Machine Learning Applications for Dairy Farming written by Rafael Ehrich Pontes Ferreira and published by . This book was released on 2024 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: With recent advancements in precision livestock farming (PLF) and machine learning (ML) techniques, computer vision systems (CVS) have gained popularity as powerful tools for individual animal monitoring. These systems can capture phenotypes from multiple animals simultaneously in an automated and non-intrusive manner. Individual animal identification is crucial for matching animals with their predicted phenotypes, which can be achieved through external identification systems or computer vision-based animal identification algorithms. While previous studies have focused on using computer vision techniques for identifying dairy cows based on unique coat color patterns, these methods are limited to specific breeds that present such patterns. Furthermore, there is a lack of research on the long-term applicability of these methods, considering visual changes due to growth or physiological states. Chapter 1 discusses current applications of computer vision for animal identification, while Chapter 2 explores methods using 3-dimensional representations of the dorsal surface of dairy calves for identification without relying on coat color patterns. These methods are evaluated on calves during their growth stage, accounting for changes in body shape and size. In Chapter 3, the potential of pseudo-labeling is assessed for improving the performance of neural networks for animal identification. The results show promising performance with a fraction of annotated data compared to traditional methods. Chapters 4 and 5 focus on developing machine learning pipelines for phenotype prediction, specifically early detection of postpartum subclinical ketosis (SCK) using prepartum data exclusively. Various techniques are explored for extracting features from image, text, genotype, and cow behavior and historical data. Data fusion techniques are explored to integrate those features into the machine learning pipelines, and a cloud computing-based framework is proposed to automate data processing, feature extraction, and phenotype prediction. Overall, this dissertation highlights the potential of machine learning and computer vision in guiding data-driven management decisions in dairy farming. By automating processes and integrating data from multiple sources and modalities, these techniques offer opportunities for improving farm profitability, productivity, and animal welfare, particularly through individual animal monitoring and early detection of health issues.
Download or read book Animal Movement written by Mevin B. Hooten and published by CRC Press. This book was released on 2017-03-16 with total page 306 pages. Available in PDF, EPUB and Kindle. Book excerpt: The study of animal movement has always been a key element in ecological science, because it is inherently linked to critical processes that scale from individuals to populations and communities to ecosystems. Rapid improvements in biotelemetry data collection and processing technology have given rise to a variety of statistical methods for characterizing animal movement. The book serves as a comprehensive reference for the types of statistical models used to study individual-based animal movement. Animal Movement is an essential reference for wildlife biologists, quantitative ecologists, and statisticians who seek a deeper understanding of modern animal movement models. A wide variety of modeling approaches are reconciled in the book using a consistent notation. Models are organized into groups based on how they treat the underlying spatio-temporal process of movement. Connections among approaches are highlighted to allow the reader to form a broader view of animal movement analysis and its associations with traditional spatial and temporal statistical modeling. After an initial overview examining the role that animal movement plays in ecology, a primer on spatial and temporal statistics provides a solid foundation for the remainder of the book. Each subsequent chapter outlines a fundamental type of statistical model utilized in the contemporary analysis of telemetry data for animal movement inference. Descriptions begin with basic traditional forms and sequentially build up to general classes of models in each category. Important background and technical details for each class of model are provided, including spatial point process models, discrete-time dynamic models, and continuous-time stochastic process models. The book also covers the essential elements for how to accommodate multiple sources of uncertainty, such as location error and latent behavior states. In addition to thorough descriptions of animal movement models, differences and connections are also emphasized to provide a broader perspective of approaches.
Download or read book Modern Methods in Neuroethology written by Bart R. H. Geurten and published by Frontiers Media SA. This book was released on 2022-07-12 with total page 290 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Deep Learning Based Computer Vision for Animal Re Identification written by Stefan Schneider and published by . This book was released on 2020 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Animal re-identification (re-ID) is fundamental to our understanding of community ecology, population dynamics and ethological analyses. Recent advances in the area of deep learning for computer vision offer a promising solution to improve upon the current methodologies for animal re-ID. The success of deep learning methods for human re-ID is well documented when ample training images are available for each individual. Despite this success, little has been done utilizing their capabilities for animal re-ID. In order to implement animal re-ID systems in practice, deep learning systems must be able to accomplish a variety of computer vision objectives. These include: quantifying the number of animals in an image, classifying the animal species within an image, localizing and extracting animal individuals within an image, and lastly re-identifying animal individuals. This work begins with a review of computer vision methods for animal re-ID (Chapter 2). I explore the quantification of animal individuals from images considering fish and dolphin counts in the Amazon River (Chapter 3). I then demonstrate the success of deep learning methods considering species identification, strategies for handling class imbalance, and quantifying performance when testing on background locations that are included/excluded from training (Chapter 4). I demonstrate the ability of deep learning systems to classify and localize animal species from camera trap images considering three global environments (Chapter 5). I then utilize five animal individual data sets to compare the success and generality of similarity comparison deep learning methods for animal re-ID (Chapter 6). Finally, I demonstrate these techniques in combination to successfully implement animal re-ID for an entirely novel study of Octopus tetricus social behaviour (Chapter 7). This work describes the complete animal re-ID pipeline for ecologists to follow in practice, outlining expected accuracies and guidelines for best practices. It imprints results to the machine learning research community considering tasks relative to the under represented task of animal re-ID. This work provides details on the necessary components required to achieve real-time camera trap survey systems. Lastly, this work encourages the progress of interdisciplinary areas of science.
Download or read book Computational Methods of Feature Selection written by Huan Liu and published by CRC Press. This book was released on 2007-10-29 with total page 437 pages. Available in PDF, EPUB and Kindle. Book excerpt: Due to increasing demands for dimensionality reduction, research on feature selection has deeply and widely expanded into many fields, including computational statistics, pattern recognition, machine learning, data mining, and knowledge discovery. Highlighting current research issues, Computational Methods of Feature Selection introduces the
Download or read book Nutrient Requirements of Dairy Cattle written by National Research Council and published by National Academies Press. This book was released on 2001-02-09 with total page 406 pages. Available in PDF, EPUB and Kindle. Book excerpt: This widely used reference has been updated and revamped to reflect the changing face of the dairy industry. New features allow users to pinpoint nutrient requirements more accurately for individual animals. The committee also provides guidance on how nutrient analysis of feed ingredients, insights into nutrient utilization by the animal, and formulation of diets to reduce environmental impacts can be applied to productive management decisions. The book includes a user-friendly computer program on a compact disk, accompanied by extensive context-sensitive "Help" options, to simulate the dynamic state of animals. The committee addresses important issues unique to dairy science-the dry or transition cow, udder edema, milk fever, low-fat milk, calf dehydration, and more. The also volume covers dry matter intake, including how to predict feed intake. It addresses the management of lactating dairy cows, utilization of fat in calf and lactation diets, and calf and heifer replacement nutrition. In addition, the many useful tables include updated nutrient composition for commonly used feedstuffs.
Download or read book Bioinformatics in Agriculture written by Pradeep Sharma and published by Academic Press. This book was released on 2022-04-28 with total page 707 pages. Available in PDF, EPUB and Kindle. Book excerpt: Bioinformatics in Agriculture: Next Generation Sequencing Era is a comprehensive volume presenting an integrated research and development approach to the practical application of genomics to improve agricultural crops. Exploring both the theoretical and applied aspects of computational biology, and focusing on the innovation processes, the book highlights the increased productivity of a translational approach. Presented in four sections and including insights from experts from around the world, the book includes: Section I: Bioinformatics and Next Generation Sequencing Technologies; Section II: Omics Application; Section III: Data mining and Markers Discovery; Section IV: Artificial Intelligence and Agribots. Bioinformatics in Agriculture: Next Generation Sequencing Era explores deep sequencing, NGS, genomic, transcriptome analysis and multiplexing, highlighting practices forreducing time, cost, and effort for the analysis of gene as they are pooled, and sequenced. Readers will gain real-world information on computational biology, genomics, applied data mining, machine learning, and artificial intelligence. This book serves as a complete package for advanced undergraduate students, researchers, and scientists with an interest in bioinformatics. - Discusses integral aspects of molecular biology and pivotal tool sfor molecular breeding - Enables breeders to design cost-effective and efficient breeding strategies - Provides examples ofinnovative genome-wide marker (SSR, SNP) discovery - Explores both the theoretical and practical aspects of computational biology with focus on innovation processes - Covers recent trends of bioinformatics and different tools and techniques
Download or read book Proceedings of the 9th International Conference on Computational Science and Technology written by Dae-Ki Kang and published by Springer Nature. This book was released on 2023-04-26 with total page 685 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book gathers the proceedings of the 9th International Conference on Computational Science and Technology (ICCST 2022), held in Johor Bahru, Malaysia, on August 27–28, 2022. The respective contributions offer practitioners and researchers a range of new computational techniques and solutions, identify emerging issues, and outline future research directions, while also showing them how to apply the latest large-scale, high-performance computational methods.
Download or read book Trend of livestock written by and published by . This book was released on 1925 with total page 16 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Animal Social Networks written by Dr. Jens Krause and published by Oxford University Press. This book was released on 2015 with total page 279 pages. Available in PDF, EPUB and Kindle. Book excerpt: The scientific study of networks - computer, social, and biological - has received an enormous amount of interest in recent years. However, the network approach has been applied to the field of animal behaviour relatively late compared to many other biological disciplines. Understanding social network structure is of great importance for biologists since the structural characteristics of any network will affect its constituent members and influence a range of diverse behaviours. These include finding and choosing a sexual partner, developing and maintaining cooperative relationships, and engaging in foraging and anti-predator behavior. This novel text provides an overview of the insights that network analysis has provided into major biological processes, and how it has enhanced our understanding of the social organisation of several important taxonomic groups. It brings together researchers from a wide range of disciplines with the aim of providing both an overview of the power of the network approach for understanding patterns and process in animal populations, as well as outlining how current methodological constraints and challenges can be overcome. Animal Social Networks is principally aimed at graduate level students and researchers in the fields of ecology, zoology, animal behaviour, and evolutionary biology but will also be of interest to social scientists.
