Results 71 to 80 of about 14,166 (237)

Edge Device Detection of Tea Leaves with One Bud and Two Leaves Based on ShuffleNetv2-YOLOv5-Lite-E

Agronomy, 2023
In order to solve the problem of an accurate recognition of tea picking through tea picking robots, an edge device detection method is proposed in this paper based on ShuffleNetv2-YOLOv5-Lite-E for tea with one bud and two leaves.
Shihao Zhang, Hekai Yang, Chunhua Yang, Wenxia Yuan, Xinghui Li, Xinghua Wang, Yinsong Zhang, Xiaobo Cai, Yubo Sheng, Xiujuan Deng, Wei Huang, Lei Li, Junjie He, Baijuan Wang   +13 more
doaj   +1 more source

Deep Learning‐Assisted Classification of Urinary Red Blood Cell Morphology for Glomerular Hematuria Screening: A Pilot Study

Journal of Clinical Laboratory Analysis, EarlyView.
This retrospective pilot study developed a YOLOv5l‐based deep learning system to detect and classify urinary red blood cells as isomorphic, dysmorphic, or unknown in urine sediment images. The model achieved a precision of 0.84, recall of 0.69, and F1‐score of 0.76 for dysmorphic RBCs, while sample‐level morphology scoring showed preliminary ...
Yih‐Lon Lin, Jung‐Sheng Chen, Ya‐Fan Chuang, Siang‐Ru Huang, Chien‐Sen Liao   +4 more
wiley   +1 more source

Mycotoxin management in the cereal supply chain: Advanced detection, detoxification, and smart packaging strategies

Journal of the Science of Food and Agriculture, EarlyView.
Abstract Mycotoxins remain a persistent threat to the safety and quality of cereal grains and other agricultural products, and their impact on human health continues to raise global concerns. In many situations, the practices traditionally used to control these toxins are no longer sufficiently effective. They can be costly, difficult to implement on a
Abolfazl Asqardokht‐Aliabadi, Dipendra Kumar Mahato, Jafar Mohammadzadeh Milani   +2 more
wiley   +1 more source

Comparative analysis of YOLOv5 and MobileNetV3 models for real-time image recognition

Вісник Харківського національного університету імені В.Н. Каразіна. Серія: Математичне моделювання, інформаційні технології, автоматизовані системи управління
Relevance: With the growing need for fast and accurate real-time object recognition, especially for mobile and embedded systems, the question of choosing the optimal AI models arises.
Ярослав Ясінський, Ніна Бакуменко   +1 more
doaj   +1 more source

Formation Control With Obstacle Avoidance of Underwater Swarms Based on Relative Visual Feedback

Journal of Field Robotics, EarlyView.
ABSTRACT Underwater multi‐robot and swarm systems require advanced methodologies for controlling collective behavior. Conventional single‐robot techniques, such as tethering, sonar imaging, and acoustic localization, are not scalable or effective for swarm applications.
Andrea Infanti, Saverio Iacoponi, Saif Alameri, Mohamed El Hanbaly, Mohammed Tarnini, Cesare Stefanini, Giulia De Masi, Federico Renda   +7 more
wiley   +1 more source

Helmet detection method based on improved YOLOv5

工程科学学报
To address the challenge of low detection accuracy in existing safety helmet detection algorithms, particularly in scenarios with small targets, dense environments, and complex surroundings like construction sites, tunnels, and coal mines, we introduce ...
Gongyu HOU, Qinhuang CHEN, Zhenhua YANG, Youwen ZHANG, Danyang ZHANG, Haoxiang LI   +5 more
doaj   +1 more source

Deep learning‐based super‐resolution reconstruction and improved YOLOv9 for efficient benthos detection: a case study at Lake Hamana, Japan

Remote Sensing in Ecology and Conservation, EarlyView.
This study presents a UAV‐based framework that integrates deep learning‐based super‐resolution reconstruction and an enhanced YOLO detector to improve centimetre‐scale benthic organism monitoring. Using hermit crabs in Lake Hamana, a coastal lagoon in Japan, as a case study, the method substantially enhanced small‐object detection performance ...
Fan Zhao, Bangzhang Ma, Dianhan Xi, Jiaqi Wang, Yijia Chen, Yongying Liu, Xinlei Shao, Mowen Zhang, Guocheng Zhang, Jundong Chen, Katsunori Mizuno   +10 more
wiley   +1 more source

PQD recognition using two-dimensional time-frequency spectrograms and an improved YOLOv5

Zhejiang dianli
As the penetration rate of renewable energy sources increases in new-type power systems， so too does the complexity of the grid structure， leading to more diverse and complex power quality disturbance （PQD）. To accurately identify power quality， a method
LI Xin, LYU Ganyun, GONG Yu, BI Ruihua, YE Jiaxing, LIU Xiaohong, YU Xiangyi   +6 more
doaj   +1 more source

Aerial military target detection algorithm based on multi-feature cross fusion and cross-layer concatenation

Xibei Gongye Daxue Xuebao, 2023
The precise detection of military targets under complex conditions is a key factor to enhance the ability of war situation generation and prediction. The current technology can not overcome the problems of smoke and occlusion interference, target height ...
GAO Wuqi, YANG Ting, LI Liangliang
doaj   +1 more source

Detecting Plateau Zokor (Eospalax baileyi) Mounds in UAV Imagery of Alpine Meadows Using Deep Learning Algorithms

Remote Sensing in Ecology and Conservation, EarlyView.
We developed PZM‐YOLO to automatically detect plateau zokor mounds in UAV imagery of alpine meadows. The model achieved reliable detection of small and densely distributed mounds under complex backgrounds, outperforming the baseline YOLOv5s. This framework supports mound counting, mound position, rodent impact assessment, and grassland restoration ...
Yang Yang, Limin Hua, Lianguo Wang, Jiazhen Li, Rui Dong, Siwei Yang   +5 more
wiley   +1 more source