Applications of machine learning in animal behaviour studies

Cited by (504)

Items 101–200 of 504

1. A standardised biologging approach to infer parturition: An application in large herbivores across the hider‐follower continuum
   Pascal Marchand, Mathieu Garel, Nicolas Morellet · 2021 · Methods in Ecology and Evolution
2. Digging into the behaviour of an active hunting predator: arctic fox prey caching events revealed by accelerometry
   Jeanne Clermont, Sasha Woodward-Gagné, Dominique Berteaux · 2021 · Movement Ecology
3. Behavioral variation across the days and lives of honey bees
   Michael Larrey Smith, Jacob D. Davidson, Benjamin Wild · 2022 · iScience
4. Fully Convolutional Neural Network: A solution to infer animal behaviours from multi-sensor data
   Lorène Jeantet, Vincent Vigon, Sébastien Geiger · 2021 · Ecological Modelling
5. Intelligent Systems Using Sensors and/or Machine Learning to Mitigate Wildlife–Vehicle Collisions: A Review, Challenges, and New Perspectives
   Irene Nandutu, Marcellin Atemkeng, Patrice Okouma · 2022 · Sensors
6. Literature Review on Technological Applications to Monitor and Evaluate Calves’ Health and Welfare
   Flávio G. Silva, Cristina Conceição, Alfredo Manuel Franco Pereira, J. O. L. Cerqueira, Severiano R. Silva · 2023 · Animals
7. How honeybees respond to heat stress from the individual to colony level
   Jitesh Jhawar, Jacob D. Davidson, Anja Weidenmüller · 2023 · Journal of The Royal Society Interface
8. replicAnt: a pipeline for generating annotated images of animals in complex environments using Unreal Engine
   Fabian Plum, René Bulla, Hendrik K. Beck, Natalie Imirzian, David Labonte · 2023 · Nature Communications
9. Improved 3D tracking and automated classification of rodents’ behavioral activity using depth-sensing cameras
   Ana Gerós, Ana Magalhães, Paulo Aguiar · 2020 · Behavior Research Methods
10. Animal social networks: an introduction for complex systems scientists
    Josefine Bohr Brask, Samuel Ellis, Darren Paul Croft · 2021 · Journal of Complex Networks
11. From Soundwave to Soundscape: A Guide to Acoustic Research in Captive Animal Environments
    Fay E. Clark, Jacob Charles Dunn · 2022 · Frontiers in Veterinary Science
12. Assessing the utility and limitations of accelerometers and machine learning approaches in classifying behaviour during lactation in a phocid seal
    Courtney R. Shuert, Patrick P. Pomeroy, Sean D. Twiss · 2018 · Animal Biotelemetry
13. How Approaches to Animal Swarm Intelligence Can Improve the Study of Collective Intelligence in Human Teams
    Lisa R. O’Bryan, Margaret E. Beier, Eduardo Salas A · 2020 · Journal of Intelligence
14. Development and validation of machine-learning models for monitoring individual behaviors in group-housed broiler chickens
    Victória R. Merenda, Venkat Umesh Chandra Bodempudi, Monique Danielle Pairis-Garcia, Guoming Li · 2024 · Poultry Science
15. Automatic posture change analysis of lactating sows by action localisation and tube optimisation from untrimmed depth videos
    Chan Zheng, Xiaofan Yang, Xunmu Zhu, Changxin Chen, Lina Wang, Shuqin Tu, Aqing Yang, Yueju Xue · 2020 · Biosystems Engineering
16. Identification of immune signatures predictive of clinical protection from malaria
    John Joseph Valletta, Mario Recker · 2017 · PLoS Computational Biology
17. Automatic Monitoring of Relevant Behaviors for Crustacean Production in Aquaculture: A Review
    Daoliang Li, Chang Liu, Zhaoyang Song · 2021 · Animals
18. Disease detection in pigs based on feeding behaviour traits using machine learning
    Alper T. Kavlak, Matti Pastell, Pekka Uimari · 2023 · Biosystems Engineering
19. Estimating the Feeding Time of Individual Broilers via Convolutional Neural Network and Image Processing
    Amin Nasiri, Ahmad Amirivojdan, Yang Zhao · 2023 · Animals
20. Understanding collective behaviors in reinforcement learning evolutionary games via a belief-based formalization
    Jiqiang Zhang, Siping Zhang, Li Chen, Xudong Liu · 2020 · Physical review. E
21. Phenotyping spontaneous locomotor activity in inbred and outbred mouse strains by using Digital Ventilated Cages
    Sara Fuochi, Mara Rigamonti, Fabio Iannello, Marcello Raspa, Ferdinando Scavizzi, Paolo de Girolamo, Livia D’Angelo · 2021 · Lab Animal
22. Individual vocal signatures show reduced complexity following invasion
    Grace Smith‐Vidaurre, Valeria Pérez-Marrufo, Timothy F. Wright · 2020 · Animal Behaviour
23. AcousticIA, a deep neural network for multi-species fish detection using multiple models of acoustic cameras
    Guglielmo Fernandez Garcia, Thomas Corpetti, Marie Nevoux, Laurent Beaulaton, François Martignac · 2023 · Aquatic Ecology
24. Variable segmentation and ensemble classifiers for predicting dairy cow behaviour
    Manod Williams, Wiliam Penri James, Michael T. Rose · 2018 · Biosystems Engineering
25. Anomaly Detection in Biological Early Warning Systems Using Unsupervised Machine Learning
    Aleksandr N. Grekov, Aleksey A. Kabanov, Elena V. Vyshkvarkova, В. В. Трусевич · 2023 · Sensors
26. Automatic acoustic recognition of pollinating bee species can be highly improved by Deep Learning models accompanied by pre-training and strong data augmentation
    Alef Iury Siqueira Ferreira, Nádia Félix Felipe da Silva, Fernanda Neiva Mesquita, Thierson Couto Rosa, Víctor Hugo Monzón, José Neiva Mesquita Neto · 2023 · Frontiers in Plant Science
27. The spatiotemporal distribution patterns and impact factors of bird species richness: A case study of urban built-up areas in Beijing, China
    Zheran Zhai, Siyao Liu, Zimeng Li, Ruijie Ma, Xiaoyu Ge, Haidong Feng, Yang Shi, Chen Juan Gu · 2024 · Ecological Indicators
28. Efficient phenotypic sex classification of zebrafish using machine learning methods
    Shahrbanou Hosseini, Henner Simianer, Jens Tetens · 2019 · Ecology and Evolution
29. Artificial neuronal networks are revolutionizing entomological research
    Manfred Hartbauer · 2024 · Journal of Applied Entomology
30. Learning about spatial inequalities: Capturing the heterogeneity in the urban environment
    Juliana Siqueira‐Gay, Mariana Giannotti, Monika Sester · 2019 · Journal of Cleaner Production
31. Early identification of Alzheimer's disease in mouse models: Application of deep neural network algorithm to cognitive behavioral parameters
    Stephanie Sutoko, Akira Masuda, Akihiko Kandori, Hiroki Sasaguri, Takashi Saito, Takaomi C. Saido, Tsukasa Funane · 2021 · iScience
32. A machine learning framework to classify Southeast Asian echolocating bats
    Natalie Yoh, Tigga Kingston, E. Durant McArthur, Oliver E. Aylen, Joe Chun‐Chia Huang, Emy Ritta Jinggong, Faisal Ali Anwarali Khan, Benjamin P. Y.‐H. Lee, Simon L. Mitchell, Jake Emmerson Bicknell et al. · 2022 · Ecological Indicators
33. A review of supervised learning methods for classifying animal behavioural states from environmental features
    Silas R. Bergen, Manuela Huso, Adam E. Duerr, Melissa A. Braham, Sara Schmuecker, Tricia A. Miller, Todd E. Katzner · 2022 · Methods in Ecology and Evolution
34. Machine learning methods for genomic prediction of cow behavioral traits measured by automatic milking systems in North American Holstein cattle
    Victor Breno Pedrosa, Shiyi Chen, Leonardo Siqueira Glória, Jarrod S. Doucette, Jacquelyn P. Boerman, Guilherme J. M. Rosa, Luiz F. Brito · 2024 · Journal of Dairy Science
35. RETRACTED: Modern Virtual Fencing Application: Monitoring and Controlling Behavior of Goats Using GPS Collars and Warning Signals
    Azamjon Muminov, Daeyoung Na, Cheolwon Lee · 2019 · Sensors · Retracted
36. Pet Owner Perception of Ferret Boredom and Consequences for Housing, Husbandry, and Environmental Enrichment
    Alice M. M. Dancer, María Díez‐León, Jennifer K. Bizley, Charlotte C. Burn · 2022 · Animals
37. Instance segmentation of pigs in infrared images based on INPC model
    Ge Wang, Yong Ma, Jun Huang · 2024 · Infrared Physics & Technology
38. A benchmark for computational analysis of animal behavior, using animal-borne tags
    Benjamin Hoffman, Maddie Cusimano, Vittorio Baglione, Daniela Canestrari, Damien Chevallier, Dominic L. DeSantis, Lorène Jeantet, Monique Ladds, Takuya Maekawa, Vicente Mata‐Silva et al. · 2024 · Movement Ecology
39. The influence of locomotion on sensory processing and its underlying neuronal circuits
    Laura Busse · 2018 · e-Neuroforum
40. Automating the analysis of fish grazing behaviour from videos using image classification and optical flow
    Ellen M. Ditria, Eric L. Jinks, Rod M. Connolly · 2021 · Animal Behaviour
41. Improving the workflow to crack Small, Unbalanced, Noisy, but Genuine (SUNG) datasets in bioacoustics: The case of bonobo calls
    Vincent Arnaud, François Pellegrino, Sumir Keenan, Xavier St-Gelais, Nicolas Mathevon, Florence Levréro, Christophe Coupé · 2023 · PLoS Computational Biology
42. Applications and Considerations of Artificial Intelligence in Veterinary Sciences: A Narrative Review
    Hesameddin Akbarein, Mohammad Hussein Taaghi, Mahyar Mohebbi, Parham Soufizadeh · 2025 · Veterinary Medicine and Science
43. Fine-scale body and head movements allow to determine prey capture events in the Magellanic Penguin (Spheniscus magellanicus)
    Monserrat Del Caño, Flavio Quintana, Ken Yoda, Giacomo Dell’Omo, Gabriela S. Blanco, Agustina Gómez‐Laich · 2021 · Marine Biology
44. From human wellbeing to animal welfare
    Lisa A. Williams · 2021 · Neuroscience & Biobehavioral Reviews
45. Tracking and Analysis of the Movement Behavior of European Seabass (Dicentrarchus labrax) in Aquaculture Systems
    Dimitra G. Georgopoulou, Orestis Stavrakidis‐Zachou, Nikos Mitrizakis, Nikos Papandroulakis · 2021 · Frontiers in Animal Science
46. A review of precision technologies in pasture-based dairying systems
    Shalloo, L., Byrne, T., Leso, L., Ruelle, E., Starsmore, K., Geoghegan, A., Werner, J., O’Leary, N. · 2021 · Irish Journal of Agricultural and Food Research
47. WATB: Wild Animal Tracking Benchmark
    Fasheng Wang, Cao Ping, Fu Li, Xing Wang, Bing He, Fuming Sun · 2022 · International Journal of Computer Vision
48. Unveiling the frontiers of deep learning: Innovations shaping diverse domains
    Shams Forruque Ahmed, Md. Sakib Bin Alam, Maliha Kabir, Shaila Afrin, Sabiha Jannat Rafa, Aanushka Mehjabin, Amir H. Gandomi · 2025 · Applied Intelligence
49. Disentangling data dependency using cross-validation strategies to evaluate prediction quality of cattle grazing activities using machine learning algorithms and wearable sensor data
    Leonardo Augusto Coelho Ribeiro, Tiago Bresolin, Guilherme J. M. Rosa · 2021 · Journal of Animal Science
50. The effects of exploratory behavior on physical activity in a common animal model of human disease, zebrafish (Danio rerio)
    Cairsty DePasquale, Kristina Franklin, Zhaohan Jia, Kavya Jhaveri, Frances E. Buderman · 2022 · Frontiers in Behavioral Neuroscience
51. LoTE-Animal: A Long Time-span Dataset for Endangered Animal Behavior Understanding
    Dan Liu, Jin Hou, Shaoli Huang, Jing Liu, Yuxin He, Bochuan Zheng, Jifeng Ning, Jindong Zhang · 2023 · IEEE/CVF International Conference on Computer Vision (ICCV)
52. Finding Meanings in Low Dimensional Structures: Stochastic Neighbor Embedding Applied to the Analysis of Indri indri Vocal Repertoire
    Daria Valente, Chiara De Gregorio, Valeria Torti · 2019 · Animals
53. The time frame of home‐range studies: from function to utilization
    Guillaume Péron · 2019 · Biological Reviews of The Cambridge Philosophical Society
54. “Micropersonality” traits and their implications for behavioral and movement ecology research
    Joseph D. Bailey, Andrew J. King, Edward A. Codling, Ashley M. Short, Gemma I. Johns, Ines Fürtbauer · 2021 · Ecology and Evolution
55. Otolith identification using a deep hierarchical classification model
    Michiel Stock, Bac Nguyen, Wouter Courtens, Hilbran Verstraete, Eric W. M. Stienen, Bernard De Baets C · 2020 · Computers and Electronics in Agriculture
56. Why animals swirl and how they group
    Egor E. Nuzhin, Maxim Panov, Nikolai V. Brilliantov · 2021 · Scientific Reports
57. AnimalAccML: An open-source graphical user interface for automated behavior analytics of individual animals using triaxial accelerometers and machine learning
    Guoming Li, Lilong Chai · 2023 · Computers and Electronics in Agriculture
58. Quantifying allo-grooming in wild chacma baboons ( Papio ursinus ) using tri-axial acceleration data and machine learning
    Charlotte Christensen, Anna M. Bracken, Mannus Justin O'Riain, Gaëlle Fehlmann, Mark D. Holton, Phil W. Hopkins, Andrew J. King, Ines Fürtbauer · 2023 · Royal Society Open Science
59. A hierarchical machine learning framework for the analysis of large scale animal movement data
    Colin J. Torney, Juan M. Morales, Dirk Husmeier A · 2021 · Movement Ecology
60. Assessment of Machine Learning Models to Identify Port Jackson Shark Behaviours Using Tri-Axial Accelerometers
    Julianna Kadar, Monique Ladds, Joanna Day, Brianne Lyall, Culum Brown · 2020 · Sensors
61. Deep learning‐based pose estimation for African ungulates in zoos
    Max Hahn‐Klimroth, Tobias Kapetanopoulos, Jennifer Gübert, Paul Wilhelm Dierkes · 2021 · Ecology and Evolution
62. Computational modeling of animal behavior in T-mazes: Insights from machine learning
    Ali Turab, Wutiphol Sintunavarat, Farhan Ullah, Shujaat Ali Zaidi, Andrés Montoyo, Josué Antonio Nescolarde‐Selva · 2024 · Ecological Informatics
63. Vocal convergence and social proximity shape the calls of the most basal Passeriformes, New Zealand Wrens
    Ines G. Moran, Yen Yi Loo, S. Louca, Nick Young, Annabel Whibley, Sarah J. Withers, P. M. Salloum, Michelle L. Hall, Margaret C. Stanley, K. Cain · 2024 · Communications Biology
64. The Use of Selected Machine Learning Methods in Dairy Cattle Farming: A Review
    Wilhelm Grzesiak, Daniel Zaborski, Marcin Pluciński, Magdalena Jędrzejczak-Silicka, Renata Pilarczyk, Piotr Sablik · 2025 · Animals
65. Deep learning for visual animal monitoring (detection, tracking, pose estimation, and behavior classification): A comprehensive review
    Rial Arifin Rajagukguk, Se-yeon Lee, Ji-yeon Park, Kehinde Favour Daniel, Chae-rin Lee, Zheng Chen, Dong Liu, Tomás Norton, Jinseon Park, Se-Woon Hong · 2025 · Smart Agricultural Technology
66. Analysis of Dogs’ Sleep Patterns Using Convolutional Neural Networks
    Anna Zamansky, Aleksandr Sinitca, Dmitrii Kaplun · 2019 · Lecture notes in computer science
67. Analysis of Cattle Social Transitional Behaviour: Attraction and Repulsion
    Haocheng Xu, Shenghong Li, Caroline Lee · 2020 · Sensors
68. Deep inference of seabird dives from GPS-only records: Performance and generalization properties
    Amédée Roy, Sophie Bertrand, Ronan Fablet · 2022 · PLoS Computational Biology
69. Learned components of courtship: A focus on postural displays, choreographies and construction abilities
    Giovanni Spezie, Cliodhna Quigley, Leonida Fusani · 2022 · Advances in the study of behavior
70. Long Short-Term Memory (LSTM)-Based Dog Activity Detection Using Accelerometer and Gyroscope
    Ali Hussain, Khadija Begum, Tagne Poupi Theodore Armand · 2022 · Applied Sciences
71. Comparison of machine learning models for bluetongue risk prediction: a seroprevalence study on small ruminants
    Hagar Fathi Gouda, Fardos A.M. Hassan, Eman E. El-Araby, Sherif A. Moawed · 2022 · BMC Veterinary Research
72. Behaviour‐specific spatiotemporal patterns of habitat use by sea turtles revealed using biologging and supervised machine learning
    Jenna L. Hounslow, Sabrina Fossette, Wei Chong, Randa Bali, Anton D. Tucker, Scott D. Whiting, Adrian C. Gleiss · 2023 · Journal of Applied Ecology
73. Quantifying mating behaviour using accelerometry and machine learning: challenges and opportunities
    Anne E. Aulsebrook, Rowan Jacques-Hamilton, Bart Kempenaers · 2023 · Animal Behaviour
74. Development of a Novel Classification Approach for Cow Behavior Analysis Using Tracking Data and Unsupervised Machine Learning Techniques
    Jiefei Liu, Derek W. Bailey, Huiping Cao, Tran Cao Son, Colin T. Tobin · 2024 · Sensors
75. A New Method of Aquatic Animal Personality Analysis Based on Machine Learning (PAML): Taking Swimming Crab Portunus trituberculatus as an Example
    Chao Yang, Xianpeng Su, Dapeng Liu, Zhongwen Guo, Fang Wang, Yunliang Lu · 2020 · Frontiers in Marine Science
76. The Philosophy of Outliers: Reintegrating Rare Events Into Biological Science
    Chelsea N. Cook, Angela R. Freeman, James C. Liao, Lisa A. Mangiamele · 2021 · Integrative and Comparative Biology
77. Exploiting deep neural network and long short-term memory method-ologies in bioacoustic classification of LPC-based features
    Cihun‐Siyong Alex Gong, Chih-Hui Simon Su, Kuo-Wei Chao · 2021 · PLoS ONE
78. Predicting the growth performance of growing-finishing pigs based on net energy and digestible lysine intake using multiple regression and artificial neural networks models
    Li Wang, Qile Hu, Lu Wang, Huangwei Shi, Changhua Lai, Shuai Zhang · 2022 · Journal of Animal Science and Biotechnology/Journal of animal science and biotechnology
79. Sensory collectives in natural systems
    Hannah J. Williams, Vivek H. Sridhar, Edward Hurme, Gabriella E. C. Gall, Natalia Borrego, Genevieve E. Finerty, Iain D. Couzin, C. Giovanni Galizia, Nathaniel Jay Dominy, Hannah M. Rowland et al. · 2023 · eLife
80. Description and classification of echolocation clicks of Indian Ocean humpback (Sousa plumbea) and Indo-Pacific bottlenose (Tursiops aduncus) dolphins from Menai Bay, Zanzibar, East Africa
    Liangliang Yang, Matt Sharpe, Andrew J. Temple · 2020 · PLoS ONE
81. Automatic synthesis of insects bioacoustics using machine learning: a systematic review
    Henry Kyalo, Henri E. Z. Tonnang, James Peter Egonyu, John Olukuru, Chrysantus Mbi Tanga, Kennedy Senagi · 2025 · International Journal of Tropical Insect Science
82. Live Weight Prediction in Norduz Sheep Using Machine Learning Algorithms
    Cihan Çakmakçı · 2022 · Turkish Journal of Agriculture - Food Science and Technology
83. Categorizing the geometry of animal diel movement patterns with examples from high-resolution barn owl tracking
    Ludovica Luisa Vissat, Shlomo Cain, Ran Nathan, Sivan Toledo, Orr Spiegel, Wayne Marcus Getz · 2023 · Movement Ecology
84. Sonic enrichment at the zoo
    Rébecca Kleinberger · 2023 · Interaction Studies Social Behaviour and Communication in Biological and Artificial Systems
85. Accuracy of early pregnancy diagnosis and determining pregnancy loss using different biomarkers and machine learning applications in dairy cattle
    Priscila Assis Ferraz, Diego Angelo Schmidt Poit, Leonardo Marin Ferreira Pinto · 2024 · Theriogenology
86. Identifying animal behaviours from accelerometers: Improving predictive accuracy of machine learning by refining the variables selected, data frequency, and sample duration
    Carolyn E. Dunford, Nikki J. Marks, Rory Paul Wilson, David Michael Scantlebury · 2024 · Ecology and Evolution
87. Nighttime wildlife object detection based on YOLOv8‐night
    Tianyu Wang, Siyu Ren, Haiyan Zhang · 2024 · Electronics Letters
88. Parameters influencing queen body mass and their importance as determined by machine learning in honey bees (Apis mellifera carnica)
    Janez Prešern, Maja Ivana Smodiš Škerl · 2019 · Apidologie
89. Video Recording and Analysis of Avian Movements and Behavior: Insights from Courtship Case Studies
    Judith Janisch, Clémentine Mitoyen, Elisa Perinot, Giovanni Spezie, Leonida Fusani, Cliodhna Quigley · 2021 · Integrative and Comparative Biology
90. Computer Vision for Detection of Body Posture and Behavior of Red Foxes
    Anne K. Schütz, Eike Tobias Krause, Mareike Fischer, Thomas Müller, Conrad M. Freuling, Franz J. Conraths, Timo Homeier‐Bachmann, Hartmut H. K. Lentz · 2022 · Animals
91. Mind the Queue: A Case Study in Visualizing Heterogeneous Behavioral Patterns in Livestock Sensor Data Using Unsupervised Machine Learning Techniques
    Catherine McVey, Fushing Hsieh, Diego Manríquez, Pablo J Pinedo, Kristina Horback · 2020 · Frontiers in Veterinary Science
92. A guide to sampling design for GPS-based studies of animal societies
    Peng Ju He, James A. Klarevas‐Irby, Danai Papageorgiou · 2022 · bioRxiv (Cold Spring Harbor Laboratory)
93. Sources and Translational Relevance of Heterogeneity in Maternal Immune Activation Models
    Urs Meyer · 2022 · Current topics in behavioral neurosciences
94. Leveraging big data to uncover the eco-evolutionary factors shaping behavioural development
    Sean M. Ehlman, Ulrike Scherer, David Bierbach, Fritz A. Francisco, Kate L. Laskowski, Jens Krause, Max Wolf · 2023 · Proceedings of the Royal Society B Biological Sciences
95. Invited Review: Applications of unsupervised machine learning in livestock behavior: Case studies in recovering unanticipated behavioral patterns from precision livestock farming data streams
    Catherine McVey, Fushing Hsieh, Diego Manríquez · 2023 · Applied Animal Science
96. Leptin deficiency-caused behavioral change – A comparative analysis using EthoVision and DeepLabCut
    Daniel Bühler, Nicole Power Guerra, Luisa Müller, Olaf Wolkenhauer A, Martin Düffer, Brigitte Vollmar, Angela Kuhla, Markus Wolfien · 2023 · Frontiers in Neuroscience
97. Wildlife tourism has little energetic impact on the world's largest predatory shark
    Adrienne Gooden, Thomas M. Clarke, Lauren Meyer, Charlie P.M. Huveneers · 2023 · Animal Behaviour
98. Consistency of behavioral profiles in zebrafish: A machine learning approach to bold and shy individual differences
    João Paulo Medeiros Mamede, Heloysa Araujo‐Silva, Maria Clara Galvão-Pereira · 2024 · Applied Animal Behaviour Science
99. Dog and owner characteristics predict training success
    Jeffrey R. Stevens, London M. Wolff, Megan Bosworth, Jill Morstad · 2021 · Animal Cognition
100. Use of machine learning approaches for body weight prediction in Peruvian Corriedale Sheep
     Ali William Canaza-Cayo, Roxana Churata-Huacani, Cihan Çakmakçı · 2024 · Smart Agricultural Technology