Zobrazeno 1 - 10
of 17
pro vyhledávání: '"Haiming Gan"'
Publikováno v:
Animals, Vol 12, Iss 16, p 2142 (2022)
Deep learning dominates automated animal activity recognition (AAR) tasks due to high performance on large-scale datasets. However, constructing centralised data across diverse farms raises data privacy issues. Federated learning (FL) provides a dist
Externí odkaz:
https://doaj.org/article/5fe8a8d9b7694ee293ff293634a3d76c
Cross-Modality Interaction Network for Equine Activity Recognition Using Imbalanced Multi-Modal Data
Publikováno v:
Sensors, Vol 21, Iss 17, p 5818 (2021)
With the recent advances in deep learning, wearable sensors have increasingly been used in automated animal activity recognition. However, there are two major challenges in improving recognition performance—multi-modal feature fusion and imbalanced
Externí odkaz:
https://doaj.org/article/b3c2de0aa15a4503ba9f41eae98c748d
Publikováno v:
Biosystems Engineering. 217:102-114
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::abf438036b94888fad2ae7790736e631
https://doi.org/10.1016/j.biosystemseng.2022.03.005
https://doi.org/10.1016/j.biosystemseng.2022.03.005
Autor:
Haiming Gan, Jingfeng Guo, Kai Liu, Xinru Deng, Hui Zhou, Dehuan Luo, Shiyun Chen, Tomas Norton, Yueju Xue
Publikováno v:
Computers and Electronics in Agriculture. 210:107877
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::25dff95282d48697a1bddcd0d40d0abb
https://doi.org/10.1016/j.compag.2023.107877
https://doi.org/10.1016/j.compag.2023.107877
Publikováno v:
Interdisciplinary Conference on Mechanics, Computers & Electrics (ICMECE); Oct2022, p309-313, 5p
Cross-Modality Interaction Network for Equine Activity Recognition Using Imbalanced Multi-Modal Data
Publikováno v:
Sensors, Vol 21, Iss 5818, p 5818 (2021)
Sensors (Basel, Switzerland)
Sensors
Volume 21
Issue 17
Sensors (Basel, Switzerland)
Sensors
Volume 21
Issue 17
With the recent advances in deep learning, wearable sensors have increasingly been used in automated animal activity recognition. However, there are two major challenges in improving recognition performance—multi-modal feature fusion and imbalanced
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::81f49373dabb191c0a41d5be284a675a
https://www.mdpi.com/1424-8220/21/17/5818
https://www.mdpi.com/1424-8220/21/17/5818
Autor:
Haiming Gan, Mingqiang Ou, Chengpeng Li, Xiarui Wang, Jingfeng Guo, Axiu Mao, Maria Camila Ceballos, Thomas D. Parsons, Kai Liu, Yueju Xue
Publikováno v:
Computers and Electronics in Agriculture. 199:107162
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::d7e46deb87f739de101c3616770dc0d7
https://doi.org/10.1016/j.compag.2022.107162
https://doi.org/10.1016/j.compag.2022.107162
Publikováno v:
Computers and Electronics in Agriculture. 189:106384
Automated detection of sow nursing behavior is beneficial to the health, welfare, and productivity of sows and piglets in the commercial swine industry. We proposed a fast and accurate detection method for sow nursing behavior using CNN-based optical
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::53099231ada055db6ce142a09c695ccf
https://doi.org/10.1016/j.compag.2021.106384
https://doi.org/10.1016/j.compag.2021.106384
Autor:
Thomas D. Parsons, Yueju Xue, Maria Camila Ceballos, Kai Liu, Haiming Gan, Axiu Mao, Endai Huang
Publikováno v:
Computers and Electronics in Agriculture. 189:106417
Counting nursing piglets is an essential task on commercial sow farms and provides a core parameter for evaluating sow reproductive performance. As a current management practice, piglets in farrowing pens are usually manually counted by caretakers se
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::658015890646be134d79280a8e8b19d0
https://doi.org/10.1016/j.compag.2021.106417
https://doi.org/10.1016/j.compag.2021.106417
Autor:
Endai Huang, Yueju Xue, Mingqiang Ou, Jiping Li, Shiqing Li, Kai Liu, Chengguo Xu, Haiming Gan
Publikováno v:
Computers and Electronics in Agriculture. 188:106357
In the pig industry, the social behaviors of preweaning piglets are critical indicators of their liveability, growth, health, and welfare status. In this study, we developed a novel method based on convolutional neural networks (CNNs) that extracts h
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::3dd4bcd40c4c75807a2f487032b9357d
https://doi.org/10.1016/j.compag.2021.106357
https://doi.org/10.1016/j.compag.2021.106357