{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,28]],"date-time":"2026-07-28T15:00:06Z","timestamp":1785250806939,"version":"3.55.0"},"reference-count":39,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2026,7,28]],"date-time":"2026-07-28T00:00:00Z","timestamp":1785196800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Vet. Sci."],"abstract":"<jats:sec>\n                    <jats:title>Introduction<\/jats:title>\n                    <jats:p>Continuous and reliable monitoring of dairy cow behaviors is a key component of data-driven herd management systems. Although wearable inertial sensors provide a practical alternative to camera-based monitoring, effectively representing complex motion patterns from raw inertial signals remains a challenge.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>This work presents an Inertial Measurement Unit (IMU)-based cow behavior recognition approach that emphasizes multi-scale motion representation using nose-mounted sensing. Acceleration data acquired from a nose-attached inertial measurement unit are utilized to capture characteristic head movement patterns associated with feeding, rumination, and locomotion activities. Instead of directly processing one-dimensional time-series signals, the inertial sequences are restructured into two-dimensional pseudo-color matrices through Gramian Angular Difference Field (GADF) transformation, allowing temporal correlations to be explicitly preserved. To exploit motion information at different levels of granularity, a multi-scale feature modeling network is developed, wherein complementary motion cues are extracted and integrated via a cross-attention-driven interaction mechanism.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>Experimental results demonstrate that the proposed framework achieves competitive recognition performance, with an overall accuracy of 90.12%, and maintains robustness across different behavioral categories.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Discussion<\/jats:title>\n                    <jats:p>These findings confirm that transforming inertial signals into GADF-based pseudo-color images, coupled with multi-scale feature modeling, offers an effective and robust solution for automated cow behavior recognition.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.3389\/fvets.2026.1872214","type":"journal-article","created":{"date-parts":[[2026,7,28]],"date-time":"2026-07-28T14:11:10Z","timestamp":1785247870000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["GADF-enhanced global\u2013local feature network for wearable sensor-based cow behavior recognition"],"prefix":"10.3389","volume":"13","author":[{"given":"Chunjie","family":"Wang","sequence":"first","affiliation":[{"name":"School of Computer and Software Engineering, Chengdu Jincheng College","place":["Chengdu, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1965","published-online":{"date-parts":[[2026,7,28]]},"reference":[{"key":"ref1","first-page":"165","article-title":"Cow behavior recognition based on image analysis and activities","volume":"10","author":"Jingqiu","year":"2017","journal-title":"Int J Agric Biol Eng"},{"key":"ref2","doi-asserted-by":"publisher","first-page":"105627","DOI":"10.1016\/j.compag.2020.105627","article-title":"Deep learning-based hierarchical cattle behavior recognition with spatio-temporal information","volume":"177","author":"Fuentes","year":"2020","journal-title":"Comput Electron Agric"},{"key":"ref3","doi-asserted-by":"publisher","first-page":"3033","DOI":"10.3390\/ani14203033","article-title":"CAMLLA-YOLOv8n: cow behavior recognition based on improved YOLOv8n","volume":"14","author":"Jia","year":"2024","journal-title":"Animals"},{"key":"ref4","doi-asserted-by":"publisher","first-page":"106889","DOI":"10.1016\/j.compag.2022.106889","article-title":"Basic motion behaviour recognition of dairy cows based on skeleton and hybrid convolution algorithms","volume":"196","author":"Li","year":"2022","journal-title":"Comput Electron Agric"},{"key":"ref5","doi-asserted-by":"publisher","first-page":"3033","DOI":"10.3390\/ani11113033","article-title":"Intelligent perception-based cattle lameness detection and behaviour recognition: a review","volume":"11","author":"Qiao","year":"2021","journal-title":"Animals"},{"key":"ref6","doi-asserted-by":"publisher","first-page":"17418","DOI":"10.1038\/s41598-023-40757-7","article-title":"A lightweight cow mounting behavior recognition system based on improved YOLOv5s","volume":"13","author":"Wang","year":"2023","journal-title":"Sci Rep"},{"key":"ref7","doi-asserted-by":"publisher","first-page":"18702","DOI":"10.1038\/s41598-024-65953-x","article-title":"A new dataset for video-based cow behavior recognition","volume":"14","author":"Li","year":"2024","journal-title":"Sci Rep"},{"key":"ref8","doi-asserted-by":"publisher","first-page":"2993","DOI":"10.3390\/ani14202993","article-title":"Research on cattle behavior recognition and multi-object tracking algorithm based on YOLO-BoT","volume":"14","author":"Tong","year":"2024","journal-title":"Animals"},{"key":"ref9","doi-asserted-by":"publisher","first-page":"1229","DOI":"10.1017\/S175907872400045X","article-title":"Multiband circularly-polarized stacked elliptical patch antenna with eye-shaped slot for GNSS applications","volume":"16","author":"Abdalrazik","year":"2024","journal-title":"Int J Microw Wirel Technol"},{"key":"ref10","first-page":"119","author":"Gomaa","year":"2024"},{"key":"ref11","doi-asserted-by":"publisher","first-page":"17493","DOI":"10.1038\/s41598-025-02111-x","article-title":"Real-time driver drowsiness detection using transformer architectures: a novel deep learning approach","volume":"15","author":"Hassan","year":"2025","journal-title":"Sci Rep"},{"key":"ref12","doi-asserted-by":"publisher","first-page":"466","DOI":"10.3390\/ani14030466","article-title":"Dynamic serpentine convolution with attention mechanism enhancement for beef cattle behavior recognition","volume":"14","author":"Li","year":"2024","journal-title":"Animals"},{"key":"ref13","doi-asserted-by":"publisher","first-page":"109399","DOI":"10.1016\/j.compag.2024.109399","article-title":"Motion focus global\u2013local network: combining attention mechanism with micro action features for cow behavior recognition","volume":"226","author":"Geng","year":"2024","journal-title":"Comput Electron Agric"},{"key":"ref14","doi-asserted-by":"publisher","first-page":"012031","DOI":"10.1088\/1757-899X\/799\/1\/012031","article-title":"Research on cow gesture recognition based on multi-label chain GBDT and LR fusion","volume":"799","author":"Zhao","year":"2020","journal-title":"IOP Conf Ser Mater Sci Eng"},{"key":"ref15","doi-asserted-by":"publisher","first-page":"12140","DOI":"10.3168\/jds.2019-17887","article-title":"Graduate student literature review: evaluating the appropriate use of wearable accelerometers in research to monitor lying behaviors of dairy cows","volume":"103","author":"Hendriks","year":"2020","journal-title":"J Dairy Sci"},{"key":"ref16","doi-asserted-by":"crossref","first-page":"012166","DOI":"10.1088\/1742-6596\/1693\/1\/012166","article-title":"Recognition method of dairy cow feeding behavior based on convolutional neural network","volume":"1693","author":"Chen","year":"2020","journal-title":"J Phys Conf Ser"},{"key":"ref17","doi-asserted-by":"publisher","first-page":"106500","DOI":"10.1016\/j.compag.2021.106500","article-title":"IoT device-based data acquisition system with on-board computation of variables for cow behaviour recognition","volume":"191","author":"Arcidiacono","year":"2021","journal-title":"Comput Electron Agric"},{"key":"ref18","doi-asserted-by":"publisher","first-page":"22933","DOI":"10.1109\/ACCESS.2020.2968495","article-title":"An explicable keystroke recognition algorithm for customizable ring-type keyboards","volume":"8","author":"Sha","year":"2020","journal-title":"IEEE Access"},{"key":"ref19","doi-asserted-by":"publisher","first-page":"20519","DOI":"10.1038\/s41598-023-45211-2","article-title":"X3DFast model for classifying dairy cow behaviors based on a two-pathway architecture","volume":"13","author":"Bai","year":"2023","journal-title":"Sci Rep"},{"key":"ref20","doi-asserted-by":"publisher","first-page":"e0203546","DOI":"10.1371\/journal.pone.0203546","article-title":"Development and validation of an ensemble classifier for real-time recognition of cow behavior patterns from accelerometer data and location data","volume":"13","author":"Wang","year":"2018","journal-title":"PLoS One"},{"key":"ref21","doi-asserted-by":"publisher","first-page":"127712","DOI":"10.1016\/j.eswa.2025.127712","article-title":"IoT-enabled recurrent spatio-temporal adaptive attention of temporal convolutional transformer with continual learning for dairy farming","volume":"282","author":"Kumar","year":"2025","journal-title":"Expert Syst Appl"},{"key":"ref22","doi-asserted-by":"publisher","first-page":"101531","DOI":"10.1016\/j.atech.2025.101531","article-title":"Advancing calving time prediction using tail acceleration data: comparative evaluation of transformer, hybrid CNN-transformer and LSTM-transformer models","volume":"12","author":"Zhao","year":"2025","journal-title":"Smart Agric Technol"},{"key":"ref23","doi-asserted-by":"publisher","first-page":"1187","DOI":"10.3390\/ani14081187","article-title":"Cow behavior recognition based on wearable nose rings","volume":"14","author":"Feng","year":"2024","journal-title":"Animals"},{"key":"ref24","doi-asserted-by":"publisher","first-page":"68","DOI":"10.1016\/j.jveb.2024.06.005","article-title":"Decoding cow behavior patterns from accelerometer data using deep learning","volume":"74","author":"Russel","year":"2024","journal-title":"J Vet Behav"},{"key":"ref25","doi-asserted-by":"publisher","first-page":"2350","DOI":"10.1109\/IGARSS52108.2023.10282550","article-title":"Detection of Earthquake-Induced Building Damages Using Remote Sensing Data and Deep Learning: A Case Study of Mashiki Town, Japan","author":"Salem","year":"2023","journal-title":"IGARSS 2023 - 2023 IEEE International Geoscience and Remote Sensing Symposium, Pasadena, CA, USA, 2023"},{"key":"ref26","doi-asserted-by":"crossref","first-page":"255","DOI":"10.3390\/wevj15060255","article-title":"Novel deep learning domain adaptation approach for object detection using semi-self building dataset and modified YOLOv4","volume":"15","author":"Tseng","year":"2024","journal-title":"World Electr Veh J"},{"key":"ref27","doi-asserted-by":"publisher","first-page":"15","DOI":"10.1186\/s40317-015-0045-8","article-title":"Classification of behaviour in housed dairy cows using an accelerometer-based activity monitoring system","volume":"3","author":"V\u00e1zquez Diosdado","year":"2015","journal-title":"Anim Biotelem"},{"key":"ref28","doi-asserted-by":"publisher","first-page":"1630083","DOI":"10.3389\/fvets.2025.1630083","article-title":"A dataset for detecting walking, grazing, and resting behaviors in free-grazing cattle using IoT collar IMU signals","volume":"12","author":"Morales-Vargas","year":"2025","journal-title":"Front Vet Sci"},{"key":"ref29","doi-asserted-by":"publisher","first-page":"32","DOI":"10.1016\/j.applanim.2009.03.005","article-title":"Cow behaviour pattern recognition using a three-dimensional accelerometer and support vector machines","volume":"119","author":"Martiskainen","year":"2009","journal-title":"Appl Anim Behav Sci"},{"key":"ref30","doi-asserted-by":"publisher","first-page":"1351","DOI":"10.3168\/jds.2022-22350","article-title":"Classification of cow behavior patterns using inertial measurement units and a fully convolutional network model","volume":"106","author":"Liu","year":"2023","journal-title":"J Dairy Sci"},{"key":"ref31","doi-asserted-by":"crossref","first-page":"105178","DOI":"10.1016\/j.compag.2019.105178","article-title":"Dam behavior patterns in Japanese black beef cattle prior to calving: automated detection using LSTM-RNN","volume":"169","author":"Peng","year":"2020","journal-title":"Comput Electron Agric"},{"key":"ref32","doi-asserted-by":"publisher","first-page":"1911","DOI":"10.3390\/s22051911","article-title":"Wearable sensor-based human activity recognition with transformer model","volume":"22","author":"Lupt\u00e1kov\u00e1","year":"2022","journal-title":"Sensors (Basel)"},{"key":"ref33","doi-asserted-by":"publisher","first-page":"19947","DOI":"10.1109\/JSEN.2025.3560812","article-title":"GaitFormer: two-stream transformer gait recognition using wearable IMU sensors in the context of industry 5.0","volume":"25","author":"Lu","year":"2025","journal-title":"IEEE Sensors J"},{"key":"ref34","doi-asserted-by":"publisher","first-page":"12592","DOI":"10.3390\/app152312592","article-title":"Attention-based CNN-BiGRU-transformer model for human activity recognition","volume":"15","author":"Miao","year":"2025","journal-title":"Appl Sci"},{"key":"ref35","doi-asserted-by":"publisher","first-page":"3779","DOI":"10.1007\/s11276-022-03093-8","article-title":"A wide axial-ratio beamwidth circularly-polarized oval patch antenna with sunlight-shaped slots for GNSS and WiMAX applications","volume":"28","author":"Abdalrazik","year":"2022","journal-title":"Wirel Netw"},{"key":"ref36","first-page":"211","author":"Gomaa","year":"2024"},{"key":"ref37","first-page":"222","author":"Gomaa","year":"2018"},{"key":"ref38","doi-asserted-by":"publisher","first-page":"26023","DOI":"10.1007\/s11042-020-09242-5","article-title":"Efficient vehicle detection and tracking strategy in aerial videos by employing morphological operations and feature points motion analysis","volume":"79","author":"Gomaa","year":"2020","journal-title":"Multimed Tools Appl"},{"key":"ref39","first-page":"522","author":"Gomaa","year":"2025"}],"container-title":["Frontiers in Veterinary Science"],"original-title":[],"link":[{"URL":"https:\/\/www.frontiersin.org\/articles\/10.3389\/fvets.2026.1872214\/full","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,7,28]],"date-time":"2026-07-28T14:11:11Z","timestamp":1785247871000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.frontiersin.org\/articles\/10.3389\/fvets.2026.1872214\/full"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,7,28]]},"references-count":39,"alternative-id":["10.3389\/fvets.2026.1872214"],"URL":"https:\/\/doi.org\/10.3389\/fvets.2026.1872214","relation":{},"ISSN":["2297-1769"],"issn-type":[{"value":"2297-1769","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,7,28]]},"article-number":"1872214"}}