Applications of machine learning in animal behaviour studies

Cited by (504)

Items 401–500 of 504

  1. Applying an interpretable machine learning approach to assess intraspecific trait variation under landscape-scale population differentiation
    Sambadi Majumder, Chase M. Mason · 2023 · bioRxiv (Cold Spring Harbor Laboratory)
  2. Image Processing and Analysis for Biotechnology and Bioprocess Engineering
    Sang‐Kyu Jung · 2024 · Applied Sciences
  3. Fishes
    Sonia Rey, Carlos García de Leániz · 2024 · Wiley eBooks
  4. Sows experiencing more severe white line lesions and heel overgrowth and erosion had poorer farrowing performance, regardless of parity order, in Brazilian commercial herds
    Alan Klein, Ton Kramer, Alyssa S Cornelison, Christof Rapp, Stefan Langer, Mike T. Socha, Lucas Alves Rodrigues · 2024 · Research Square
  5. Screening by changes in stereotypical behavior during cell motility
    Luke Tweedy, Patrick Witzel, Doris Heinrich, Robert H. Insall, Robert G. Endres · 2019 · arXiv (Cornell University)
  6. Der Einfluss von Fortbewegung auf die sensorische Informationsverarbeitung und die zugrunde liegenden neuronalen Schaltkreise
    Laura Busse · 2018 · e-Neuroforum
  7. Desenvolvimento de classificador de conforto térmico para bovinos de leite utilizando modelagem computacional e termografia de infravermelho
    Verônica Madeira Pacheco · 2019
  8. Image Processing Features Extraction on Fish Behaviour
    Mohd Azraai Mohd Razman, Anwar P. P. Abdul Majeed, Rabiu Muazu Musa, Zahari Taha, Gian Antonio Susto, Yukinori Mukai · 2020 · SpringerBriefs in applied sciences and technology
  9. Construction of a statistical learning tool based on ordinary differential equations to model the digestive behaviour of ross chickens
    Nicolas Bloyet, Hélène Flourent, Emmanuel Frénod · 2020 · ESAIM Proceedings and Surveys
  10. A Digital Ecosystem for Animal Movement Science: Making animal movement datasets, data-linkage techniques, methods, and environmental layers easier to find, interpret, and analyze
    Hoover, Brendan, Gil Bohrer, Jerod A. Merkle · 2020 · arXiv (Cornell University)
  11. Exploratory Data Analysis Using Supervised Learning Techniques on Credit Card Default Data Set in Machine Learning
    K. Ulaga Priya, S. Pushpa · 2020 · Lecture notes in electrical engineering
  12. Multivariate Analysis of Open Field Exploration Identifies Latent Spatial and Social Behavioral Axes in Domestic Dogs
    Budhaditya Chowdhury, Moira J. van Staaden, Robert Huber · 2020 · Frontiers in Behavioral Neuroscience
  13. Machine learning for dairy cow behaviour classification
    Manod Williams · 2020
  14. Chapter 7 Data Science and Resilience
    Fred S. Roberts · 2021 · Lecture notes in computer science
  15. Learning spatial inequalities: an approach to support transportation planning.
    Juliana Siqueira Gay · 2018
  16. Intelligent Robust Base-Station Research in Harsh Outdoor Wilderness Environments for Wildsense
    Junho Ahn, Akshay Mysore, Kati Zybko, Caroline E. Krumm, Dohyeon Lee, Dahyeon Kim, Richard Y. Han, Shivakant Mishra, N. Thompson Hobbs · 2021 · KSII Transactions on Internet and Information Systems
  17. Why Do Animals Swirl and How Do They Group?
    Egor E. Nuzhin, Maxim Panov, Nikolai V. Brilliantov · 2021 · Research Square
  18. A CASE STUDY ON ANIMAL BEHAVIOR ANALYSIS USING GAMLSS
    Lineu Alberto Cavazani de Freitas, César Augusto Taconeli, José Luiz Padilha da Silva · 2021 · Brazilian Journal of Biometrics
  19. A deep neural network for multi-species fish detection using multiple acoustic cameras
    Guglielmo Fernandez Garcia, François Martignac, Marie Nevoux, Laurent Beaulaton, Thomas Corpetti · 2021 · arXiv (Cornell University)
  20. Exploring loss functions for optimising the accuracy of Siamese neural networks in re-identification applications
    Jonathan Eichild Schmidt, Oscar E. Mäkinen, Simon G. Nielsen, Anders Skaarup Johansen, Kamal Nasrollahi, Thomas Baltzer Moeslund · 2022 · International Conference on Machine Vision
  21. Paysage, biodiversité fonctionnelle et santé des plantes
    Philippe Tixier, Dominique Carval, Stefaniya Kamenova, Jean‐François Martin, Fabrice Vinatier, Adrien Rusch · 2019 · Éducagri éditions eBooks
  22. Saying Something New: The Hidden Patterns in Corpora
    Michael Hoey · 2005
  23. Smart structures
    Hassan Elahi, Marco Eugeni, Paolo Gaudenzi · 2022 · Elsevier eBooks
  24. Application of Geospatial Technology and R for the Wildlife Habitat Analysis in Mae Ping National Park, Thailand
    Baromasak Klanreungsang · 2022 · SSRN Electronic Journal
  25. Peer Review #1 of "Characterizing the suckling behavior by video and 3D-accelerometry in humpback whale calves on a breeding ground (v0.1)"
    2022 · PeerJ
  26. Peer Review #2 of "Characterizing the suckling behavior by video and 3D-accelerometry in humpback whale calves on a breeding ground (v0.1)"
    2022 · PeerJ
  27. Peer Review #3 of "Characterizing the suckling behavior by video and 3D-accelerometry in humpback whale calves on a breeding ground (v0.2)"
    2022 · PeerJ
  28. Peer Review #2 of "Characterizing the suckling behavior by video and 3D-accelerometry in humpback whale calves on a breeding ground (v0.2)"
    2022 · PeerJ
  29. Peer Review #3 of "Characterizing the suckling behavior by video and 3D-accelerometry in humpback whale calves on a breeding ground (v0.1)"
    2022 · PeerJ
  30. Unsupervised Machine Learning as a Tool for Exploratory Analysis of Acoustic Telemetry Data: A Case Study With Northern Pike in Toronto Harbour
    Adogbeji V. Agberien · 2021
  31. A Brief Overview of Applications of Machine Learning in Life Sciences
    Shyamasree Ghosh, Rathi Dasgupta · 2022 · Springer eBooks
  32. Effects of Maternal Nutrient Restriction and Melatonin Supplementation on Cardiomyocyte Cell Development Parameters Using Machine Learning Techniques
    Mitra Mazinani, Zully E Contreras-Correa, Vahid Behzadan, Shreya Gopal, Caleb Owens Lemley · 2022 · Animals
  33. Prototyping Artificial Intelligent Classifiers using Deep Learning
    Herman Njoroge Chege · 2022
  34. Rapid Prototyping of Species Classifiers using Deep Learning: A Guide for Non-Experts
    Herman Njoroge Chege · 2022
  35. Rapid Prototyping of Species Classifiers using Deep Learning
    Herman Njoroge Chege · 2022
  36. Multi-Channel Residual Learning for Marine Mammal Vocalization Classification
    Daniel T. Murphy, Elias Ioup, Christopher Michael · 2022 · IEEE International Geoscience and Remote Sensing Symposium (IGARSS)
  37. callsync: an R package for alignment and analysis of multi-microphone animal recordings
    Simeon Q. Smeele, Stephen A. Tyndel, Barbara C. Klump · 2023 · bioRxiv (Cold Spring Harbor Laboratory)
  38. 108. Application of machine learning algorithms to develop behavioural and stress phenotypes for sheep
    Hamideh Keshavarzi, Dana L. M. Campbell, Caroline Lee · 2022 · World Congress on Genetics Applied to Livestock Production (WCGALP)
  39. The Impact of Hard and Easy Negative Training Data on Vulnerability Prediction Performance
    Fahad Al Debeyan, Lech Madeyski, Tracy Hall · 2023 · SSRN Electronic Journal
  40. Hardy Weinberg Principle Automation : A Comparative study of Neural network and Fuzzy based accessibility model for the study of Evolution
    Karthika Balan, Michael J. Santora, Mariam Faied, Víctor D. Carmona-Galindo · 2022 · International Conference on Next Generation Intelligent Systems (ICNGIS)
  41. What acceleration data from wildlife collars and animal body mass tell us about seed dispersal
    Carsten M. Buchmann, Lukas Dreyling, Mihaela Constantin · 2023 · Animal Biotelemetry
  42. Prediction of Daily Nutritional Requirements of Gestating Sows Based on Sensors Data and Machine Learning Algorithms
    Maëva Durand, Christine Largouët, Louis Bonneau de Beaufort · 2023 · SSRN Electronic Journal
  43. Development and Validation of Machine-Learning Models for Monitoring Individual Behaviors in Group-Housed Broilers
    Victória R. Merenda, Venkat Umesh Chandra Bodempudi, Monique Danielle Pairis-Garcia, Guoming Li · 2023 · SSRN Electronic Journal
  44. iMOUSE - Reforming the Strategy of Refinement and Reduction for indispensable laboratory animal-based studies in translational research
    M.-A. Du Laz, Mirko Lampe, Isaac Connor, Dmytro Shestachuk, Marcel Ludwig, Ursula Müller, Oliver F. Strauch, Nadine Suendermann, Stefan Lüth, Janine Kah · 2023 · bioRxiv (Cold Spring Harbor Laboratory)
  45. Introduction to Machine Learning in Medicine
    Rossana Buongiorno, Claudia Caudai, Sara Colantonio, Danila Germanese · 2023 · Imaging informatics for healthcare professionals
  46. Developing an Interpretable Machine Learning Model for the Detection of Mimosa Grazing in Goats
    S. Paez Lama, Carlos Adrian Catania, Luana Ribeiro · 2023 · SSRN Electronic Journal
  47. Weakly electric fishes
    Mary Upshall · 2023 · Elsevier eBooks
  48. Unidade de alimentação inteligente para medir a força de bicagem em frangos de corte
    Rogério Torres Seber · 2022
  49. Padrões sequenciais de comportamento para avaliar o bem-estar de frangos de corte
    Tatiane Branco · 2021
  50. Tools for Measuring Behaviour
    Marc Naguib, Gretchen F. Wagner, Lysanne Snijders · 2023 · Springer eBooks
  51. Towards the next generation of species delimitation methods: an overview of Machine Learning applications
    Matheus Maciel Alcantara Salles, Fabrícius M. C. B. Domingos · 2023
  52. Algoritmos para explicação responsável de recomendações.
    Douglas Luan de Souza · 2023
  53. Technological innovation in the ambience of facilities for farm animals: Applications
    Gabriel Maurício Peruca de Melo, Liandra Maria Abaker Bertipaglia, Wanderley José de Melo · 2024 · Seven Editora eBooks
  54. Modelling Behavior of Crested Gecko (Correlophus Ciliatus) Using Classification Algorithms
    Jakub Pacoń, Barbara Kosińska-Selbi, Jarosław Wełeszczuk · 2024 · SSRN Electronic Journal
  55. First application of one‐class support vector machine algorithms for detecting abnormal behavior of marine medaka Oryzias javanicus exposed to the harmful alga Karenia mikimotoi
    Abrianna Elke Chairil, Yuki Takai, Yosuke KOBA · 2024 · Limnology and Oceanography Methods
  56. Enhanced Myocardial Infarction Prediction Using Machine Learning Algorithms and Gender-Specific Insights
    Nudrat Fatima · 2024 · Journal of Electrical Systems
  57. Optimization of Broiler Behavior Recognition Technology Based on Accelerometer
    Hui Fang Zhang, Hong Sheng Lin, Changsi Li · 2024 · International Conference on Computer Information Science and Application Technology (CISAT)
  58. Suitability of a commercial low-cost biologging system for monitoring movement, behaviour and heart rate of grazing dairy cows
    Salvatore Raniolo, Andrea Ceppatelli, Marco Berton, Nicolò Amalfitano, Enrico Sturaro, Maurizio Ramanzin · 2024 · Italian Journal of Animal Science
  59. An Agent-Based Model of Directional Multi-Herds
    Denys Grushchak, Jenna Kline, Danilo Pianini, Nicolas Farabegoli · 2024 · IEEE International Conference on Autonomic Computing and Self-Organizing Systems Companion (ACSOS-C)
  60. Editorial Note
    Brian D. Wisenden, Mariska Esther Kret · 2024 · Behaviour
  61. IVDETR: A Multi-Source Image Pig Detection Method Based on Cross-Domain Feature Fusion
    Rui Song, Hao Li, Mengzhen Huang · 2024 · International Conference on Pattern Recognition and Artificial Intelligence (PRAI)
  62. Automated Monitoring and Analysis of Avian Behavior and Hatching Success Using YOLOv8: A Case Study on Red-Wattled Lapwings
    Devinya Vidanage, Vijini Tennekoon, Isuru Ariyananda · 2024 · International Conference on Advancements in Computing (ICAC)
  63. Improved Pig Behavior Analysis Through Strategic Data Preprocessing Framework in Machine Learning
    Pranjal Ranjan, Sanjana Bharadwaj, Yingqi Pei, Kenan Burak Aydın, Dong Sam Ha, Gota Morota, Sook Shin · 2024 · IEEE International Conference on Tools with Artificial Intelligence (ICTAI)
  64. Review on Predictive Model for Forecast of Renewable Energy Output: a Case Study of National Orthopedic Hospital, Igbobi
    Olamide Omolara Olusanya, Olarinde Hakeem Olaiya, Folorunso A. Olugbenga · 2024
  65. Enhancing Bike Safety with Ultrasonic Dog Repellent
    Srikakulapu Subhakar, V Uma Sai Vara Prasad, Avanigadda Thanmai Sasidhar · 2025 · International Conference on Inventive Computation Technologies (ICICT)
  66. The Synergy of Artificial Intelligence and Animal Communication
    Arun Agrawal, Anuja Manoj Chavan, Swati Nilesh Pawar, Ashvini Arvind Todkar, Deepak Gupta, Deepak Sudhakar Dharrao, Rakhi Arora, Rajeev Kumar Singh · 2025 · Advances in computational intelligence and robotics book series
  67. Towards an improved analysis of bird species identification from real time images by comparing mobilenet with inception method
    C. Venkata Hari Prasad, U. Arul · 2025 · AIP conference proceedings
  68. Prediction of different physiological conditions of riverine buffaloes (Bubalus bubalis) based on their vocal cues through machine learning algorithms and a conventional statistical model
    Indu Devi, Naresh Kumar Dahiya, Anand Prakash Ruhil · 2025 · Journal of Dairy Research
  69. A First Approach to Investigate Characteristics of Piling Behaviour in Individual Laying Hens
    Ariane Stratmann, Alexander Kashev, Maxine Rice · 2025 · SSRN Electronic Journal
  70. New methods and technologies to record sheep behaviors
    Meng-Hua Li, Hosein Salehian-Dehkordi · 2025 · Elsevier eBooks
  71. Behavior Analysis, Rumination Analysis and Disease Prediction in Cattle Using 3-axis Accelerometers
    T. Tamura · 2023 · Japanese Journal of Large Animal Clinics
  72. Machine learning algorithm approaches for predicting body weight in tuis Huacaya alpacas
    Ali William Canaza-Cayo, Francisco Halley Rodríguez-Huanca, Maria Celeste Huanca-Ilaquijo · 2025 · Smart Agricultural Technology
  73. Predicting equine behavior from small datasets using machine learning with LLM-generated explanations
    Oleksandra Topal, Inna Novalija, Dunja Mladenić · 2025 · Applied Animal Behaviour Science
  74. Hybrid XGBoost-ELAM modelfor predicting fish movement trajectories in complex fishway geometries
    Zhang Qianxu, Junjun Tan, Xiaolong Chen, Wang Yuanyang, Weiming Li, Giri Kattel, Xiaotao Shi · 2025 · SSRN Electronic Journal
  75. Solar fields provide diurnal habitat for European hares (Lepus europaeus) within the intensive agricultural landscape
    Chloé Tavernier, Minke Mulder, Martijn J.A Weterings · 2026 · SSRN Electronic Journal
  76. Behavioral profile predicts ethanol preference in adolescent mice, but not in adults: A machine learning approach
    Liana Catarina Lima Portugal, Bruno da Silva Gonçalves, Emily de Assis Fagundes, Maria Fernandes Freire de Sá, Cláudio Carneiro Filgueiras, Ana Carolina Dutra-Tavares, Alex C. Manhães, Yael Abreu‐Villaça, Anderson Ribeiro‐Carvalho · 2026 · Alcoholism Clinical and Experimental Research
  77. AI-Empowered Data-Driven Agent-Based Modeling and Simulation: Challenges, Methodologies, and Future Perspectives
    Bhakti Stephan Onggo, He Zhou, Peng Lu · 2025 · Winter Simulation Conference
  78. Skeleton integrity: A method for the efficient fine-tuning of pose estimation models for pigs
    David Brunner, Marie Bordes, Elisabeth Mayrhuber, Stephan M. Winkler, Viktoria Dorfer, Maciej Oczak · 2026 · Biosystems Engineering
  79. A first approach to investigate characteristics of piling behaviour in individual laying hens
    A. Stratmann, Alexey V. Kashev, M. Rice, M. J. Toscano · 2026 · Applied Animal Behaviour Science
  80. Advances in intelligent animal pose tracking for neuro-behavioral integration
    Yuzhe Zhong, Lanjing Wang, Xiao-Yue Wang, Chong Sun, Jun Chen, Haitao Yang · 2026 · Neurocomputing
  81. Recognising dog movement with behaviour-specific machine learning models: bout length as a biologically relevant parameter for window size
    Gábor Csizmadia, Bálint Daróczy, Bence Ferdinandy, Balázs Nagy, Ádám Miklósi · 2026 · BMC Veterinary Research
  82. Multidimensional behavioral endpoints in zebrafish: Toward integrative neurotoxicity assessment under environmental stress
    Xinyue Liu, Chaoju Li, Yuanqiang Yang, Lan Li, Wenting Zeng, Zhiqiu Huang, Yi Huang, Yuhang Hong · 2026 · Neuroscience & Biobehavioral Reviews
  83. Étude des stratégies de mouvement chez les parasitoïdes du genre Trichogramma : apports des techniques d’analyse d’images automatiques
    Victor Burte · 2018
  84. Détection des modifications de l’organisation circadienne des activités des animaux en relation avec des états pré-pathologiques, un stress, ou un événement de reproduction
    Nicolas Wagner · 2020 · theses.fr (ABES)
  85. Uncertainty analysis, sensitivity analysis, and machine learning in cardiovascular biomechanics
    Robert Rapadamnaba · 2020 · theses.fr (ABES)
  86. Construction et analyse d'outils d'apprentissage statistique biomimétiques basés sur des systèmes d'équation aux dérivées partielles pour l'assimililation de données d'élevage
    Hélène Flourent · 2020 · theses.fr (ABES)
  87. Deep learning framework for sow posture classification from depth images: Comparison with data transformation techniques, models, and cross-validation
    Md Towfiqur Rahman, T. M. Brown-Brandl, Gary Alan Rohrer · 2026 · SSRN Electronic Journal
  88. Behavioral synchronization of wintering Tundra Swans ( Cygnus columbianus ) varies with spatial position, time of year, and habitat
    Zhiru Lu, Shilong Yu, Aping Zhu · 2026 · Current Zoology
  89. Segmentation and profile-based classification of movement strategies from animal tracking data
    Ivo Kadlec, Aleš Vorel, Martin Sládeček et al. · 2026 · bioRxiv (Cold Spring Harbor Laboratory)
  90. Climate change and the psychosomatic health of animals: Mechanisms, manifestations, and mitigation strategies
    Olha Shulko, R. Shahanenko, M. Chornozub, А. Емельяненко, Світлана Василівна Гуральська, Т. Ф. Кот, L. H. Yevtukh, A. Dubovyi, Олег Вікентійович Пінський, Т. С. Буднік et al. · 2026 · Regulatory Mechanisms in Biosystems
  91. Harnessing complexity may strangle it: what is a well-controlled experiment?
    Jutta Schickore, Sara Magalhães, Mariana Gómez-Schiavon · 2026 · Proceedings of the Royal Society B Biological Sciences
  92. Machine learning and its application in tribo-mechanical characterization of composites: A review
    Nikhil Mohan Vyas, Sanjay Katarey, Savita Dixit · 2026 · AIP conference proceedings
  93. Optimal deep learning activity recognition pipeline using animal bio‐logging data
    Jasper A.J. Eikelboom · 2026 · Methods in Ecology and Evolution
  94. Individual detachment–reintegration events in homing pigeon flocks and the dominance of directional adjustment in their kinematic features
    Yinggang Huang, Mengmeng Li, Zhigang Shang · 2026 · Journal of The Royal Society Interface
  95. Smart Sensing and Signal Processing: Revolutionizing Precision Agriculture for a Sustainable Future
    L. Abhishek, B. U. Shravya, K.R. Dasegowda · 2026 · Studies in computational intelligence
  96. Intelligent Methods in Behavioral Studies on Animal Models
    Yevheniia Babenko, Volodymyr Romanov · 2024 · International Workshop of IT-professionals on Artificial Intelligence (ProfIT AI)
  97. Deep learning framework for sow posture classification from depth images: Comparison with data transformation techniques, models, and cross-validation
    Md Towfiqur Rahman, T. M. Brown-Brandl, Gary A. Rohrer · 2026 · Smart Agricultural Technology
  98. Performance of multiple models under different test strategies in predicting the ingestive behavior of grazing cattle
    Lázaro Henrique da Silva, Caio Matheus Leite da Silva, Erick Galani Maziero · 2026 · Revista Brasileira de Zootecnia
  99. Duration-aware unsupervised segmentation reveals collective movement modes in homing flights of pigeon flocks
    Yinggang Huang, Mengmeng Li, Zhigang Shang, Lifang Yang · 2026 · Movement Ecology
  100. Segmentation and profile-based classification of movement strategies from animal tracking data
    Ivo Kadlec, Johannes Signer, Martin Sládeček et al. · 2026 · Research Square