Results 141 to 150 of about 103,607 (290)

Unsupervised Work Behavior Pattern Extraction Based on Hierarchical Probabilistic Model

IEEJ Transactions on Electrical and Electronic Engineering, EarlyView.
In this study, we address the challenge of analyzing worker behaviors in high‐mix, low‐volume production environments, where traditional supervised learning methods struggle owing to the lack of labeled data and task variability among workers. To overcome these issues, we propose a novel hierarchical approach for unsupervised behavior pattern ...
Issei Saito, Tomoaki Nakamura, Toshiyuki Hatta, Wataru Fujita, Shintaro Watanabe, Shotaro Miwa   +5 more
wiley   +1 more source

Portable Radar for Noncontact Heart Rate Monitoring and Estrus Detection in Dairy Cows

IEEJ Transactions on Electrical and Electronic Engineering, EarlyView.
This study introduces a portable radar system for real‐time monitoring of respiratory and heart rates in dairy cows. It uses millimeter‐wave Frequency Modulated Continuous Wave (FMCW) radar to perform noncontact physiological sensing, reducing behavioral disturbance. The radar system's design prioritizes portability, cost‐effectiveness, and robustness,
Yingxiu Li, Ranran Wang, Fuyang Tian, Yudao Li, Zhuolin Wang, Yuxin Yu, Liping Ma, Xin Lu   +7 more
wiley   +1 more source

Monitoring GPS‐collared moose by ground versus drone approaches: efficiency and disturbance effects

Wildlife Biology, EarlyView.
Efficient wildlife management requires precise monitoring methods, for example to estimate population density, reproductive success, and survival. Here, we compared the efficiency of drone (equipped with a RGB camera) and ground approaches to detect and observe GPS‐collared female moose Alces alces and their calves. We also quantified how drone (n = 42)
Martin Mayer, Erlend Furuhovde, Kristoffer Nordli, Giorgia Myriam Ausilio, Petter Wabakken, Ane Eriksen, Alina L. Evans, Karen Marie Mathisen, Barbara Zimmermann   +8 more
wiley   +1 more source

A Unified Framework for Recognizing Dynamic Hand Actions and Estimating Hand Pose from First-Person RGB Videos

Algorithms
Recognizing hand actions and poses from first-person RGB videos is crucial for applications like human–computer interaction. However, the recognition accuracy is often affected by factors such as occlusion and blurring.
Jiayi Yang, Jiao Liang, Huimin Pan, Yuting Cai, Quanli Gao, Xihan Wang   +5 more
doaj   +1 more source

Seasonal variations and challenges in estimating populations and identifying species of Korean ungulates using drone‐derived thermal orthomosaic maps

Wildlife Biology, EarlyView.
Drones equipped with thermal infrared (TIR) cameras offer significant time and labor savings in estimating wild ungulate populations. However, accurately monitoring forest‐dwelling ungulates remains challenging due to their elusive behavior and complex habitat.
Jinhwi Kim, Donggul Woo
wiley   +1 more source

Single Shot Detector CNN and Deep Dilated Masks for Vision-Based Hand Gesture Recognition From Video Sequences

IEEE Access
With an increasing number of people on the planet today, innovative human-computer interaction technologies and approaches may be employed to assist individuals in leading more fulfilling lives.
Fahmid Al Farid, Noramiza Hashim, Junaidi Bin Abdullah, Md. Roman Bhuiyan, Magzhan Kairanbay, Zulfadzli Yusoff, Hezerul Abdul Karim, Sarina Mansor, MD. Tanjil Sarker, Gobbi Ramasamy   +9 more
doaj   +1 more source

Monitoring wildlife using long‐endurance solar‐electric UAVs

Wildlife Biology, EarlyView.
This report discusses the effectiveness of using small solar‐electric UAV (uncrewed aerial vehicles) for aerial wildlife monitoring. We review four years of aerial wildlife monitoring missions using a 5.5‐m wingspan, solar‐electric UAV that was equipped with a gimballed IR/RGB camera.
Götz Bramesfeld, William Bissonnette, Maya Rahaman‐Noronha, Kanwar Johal   +3 more
wiley   +1 more source

Quantitative Gait Analysis from Single RGB Videos Using a Dual-Input Transformer-Based Network [PDF]

Huong Quynh Dinh, Son Thanh Le, Martin Than, Minh Tam Ho, Nicolas Vuillerme, Hieu Pham   +5 more
openalex   +1 more source

AML‐Net: Attention‐based multi‐scale lightweight model for brain tumour segmentation in internet of medical things

CAAI Transactions on Intelligence Technology, EarlyView.
Abstract Brain tumour segmentation employing MRI images is important for disease diagnosis, monitoring, and treatment planning. Till now, many encoder‐decoder architectures have been developed for this purpose, with U‐Net being the most extensively utilised. However, these architectures require a lot of parameters to train and have a semantic gap. Some
Muhammad Zeeshan Aslam, Basit Raza, Muhammad Faheem, Aadil Raza   +3 more
wiley   +1 more source

XTrack: Multimodal Training Boosts RGB-X Video Object Trackers [PDF]

Yuedong Tan, Zongwei Wu, Yuqian Fu, Zhuyun Zhou, Guolei Sun, Zamfi, Eduard, Chao Ma, Danda Pani Paudel, Luc Van Gool, Radu Timofte   +9 more
openalex   +1 more source