Results 91 to 100 of about 54,995 (246)

YOLO-Granada: a lightweight attentioned Yolo for pomegranates fruit detection

Scientific Reports
Pomegranate is an important fruit crop that is usually managed manually through experience. Intelligent management systems for pomegranate orchards can improve yields and address labor shortages. Fast and accurate detection of pomegranates is one of the key technologies of this management system, crucial for yield and scientific management.
Jifei Zhao, Chenfan Du, Yi Li, Mohammed Mudhsh, Dawei Guo, Yuqian Fan, Xiaoying Wu, Xinfa Wang, Rolla Almodfer   +8 more
openaire   +4 more sources

Performance Analysis of YOLO, Faster R-CNN, and DETR for Automated Personal Protective Equipment Detection

Journal of Applied Informatics and Computing
Automated monitoring of Personal Protective Equipment (PPE) is crucial for enhancing safety in high-risk environments like construction sites, yet selecting the optimal detection model requires careful evaluation of accuracy versus efficiency trade-offs.
Rihan Naufaldihanif, Dedy Kurniawan, Ken Ditha Tania   +2 more
doaj   +1 more source

A UAV‐based deep learning pipeline for intertidal macrobenthos monitoring: Behavioral and age classification in Tachypleus tridentatus

Remote Sensing in Ecology and Conservation, EarlyView.
The endangered tri‐spine horseshoe crab (Tachypleus tridentatus), a “living fossil” crucial to coastal ecology and biomedical research, is experiencing severe population declines. Effective conservation requires efficient monitoring, which traditional methods cannot deliver at scale. We develop an integrated UAV deep learning framework tailored to this
Xiaohai Chen, Yuyuan Bao, Ziwei Ying, Mujiao Xie, Ting Li, Jixing Zou, Jun Shi, Xiaoyong Xie   +7 more
wiley   +1 more source

From snapshots to continuous estimates: Augmenting citizen science with computer vision for fish monitoring

Remote Sensing in Ecology and Conservation, EarlyView.
This study presents an end‐to‐end computer‐vision pipeline for monitoring fish migration using underwater video. We integrate field camera deployment, annotation, model training and automated in‐season counting to generate continuous, high‐resolution data on river herring spawning migration.
Zhongqi Chen, Timm Haucke, Sara Beery, Keven Bennett, Austin Powell, Lydia Zuehsow, Robert Vincent, Linda Deegan   +7 more
wiley   +1 more source

Smart Waste, Smarter World: Exploring Waste Types, Trends, and Tech‐Driven Valorization Through Artificial Intelligence, Internet of Things, and Blockchain

Sustainable Development, EarlyView.
ABSTRACT Global municipal solid waste generation is projected to exceed 3.8 billion tonnes annually by 2050. This makes the need for smart, inclusive, and scalable waste valorization systems more urgent than ever. This review critically explores the shift from conventional waste management to intelligent, technology‐driven solutions aligned with ...
Segun E. Ibitoye, Amit K. Ball, Raul V. Rodriguez, Olalekan A. Olayemi, Peplluis Esteva, Peter O. Omoniyi, Isaac K. Adegun, Rasheedat M. Mahamood, Esther T. Akinlabi   +8 more
wiley   +1 more source

The performance of drones and artificial intelligence for monitoring sage‐grouse at leks

Wildlife Biology, EarlyView.
Accurately monitoring sage‐grouse populations is critical for conservation, yet traditional ground‐based visual surveys face challenges in scalability and consistency, prompting the exploration of innovative drone‐based methodologies enhanced by artificial intelligence.
Lance B. McNew, Jason Hanlon, Ilya Buzytsky   +2 more
wiley   +1 more source

Species Conservation on a Working Landscape: The Joint Production of Wildlife and Crops in the Yolo Bypass Floodplain [PDF]

Replaced with revised version of paper 07/19/11.Crop Production/Industries, Resource /Energy Economics and Policy,
Garnache, Cloe, Howitt, Richard E.
core   +1 more source

Evaluating machine learning models for multi‐species wildlife detection and identification on remote sensed nadir imagery in South African savanna

Wildlife Biology, EarlyView.
This research paper investigates the efficacy of leading machine learning (ML) models for detecting and identifying ungulate species in African savanna using nadir imagery from unmanned aerial vehicles (UAVs). Traditional aerial counting methods, while widely used, suffer from significant limitations in accuracy and precision, in part due to human ...
Paul Allin, Fadel Seydou, Radloff Frans, Andrew Davies, Alison Leslie   +4 more
wiley   +1 more source

Brain‐RetinaNet: Detection of Brain Tumour Using an Improved RetinaNet in Magnetic Resonance Imaging

CAAI Transactions on Intelligence Technology, EarlyView.
ABSTRACT Brain tumours disrupt the normal functioning of the brain and, if left untreated, can invade surrounding tissues, blood vessels, and nerves, posing a severe threat. Consequently, early detection is crucial to prevent tragic outcomes. Distinguishing brain tumours through manual detection poses a significant challenge given their diverse ...
Rashid Iqbal, Rabbia Mahum, Mohamed Sharaf, Javed Ali Khan   +3 more
wiley   +1 more source

Real-Time Pose Estimation of Preterm Infants Using Depth Images

Current Directions in Biomedical Engineering
Early diagnosis of neurodevelopmental disorders in infants relies on accurate analysis of spontaneous movements. Achieving this requires fast and precise pose estimation methods tailored to infant-specific anatomy and motion. This study evaluates several
Vogelsang Tobias, Fahlbusch Fabian B., Behr Anna-Lena, Zaunseder Sebastian   +3 more
doaj   +1 more source