Results 41 to 50 of about 8,823 (191)

YOLOv5-DCN: An Effective Improvement Based on YOLOv5 Detector

International Journal of Computer Science and Information Technology
Urine sediment detection is of great significance for the diagnosis and monitoring of kidney diseases, urinary tract infections, stones, etc. This study aims to propose fast, high-precision and lightweight Urinary particles detection model based on YOLOv5, deformable convolution, and evaluate its performance in Urinary particles detection tasks.
Xiaoxia Qi, Md Gapar Md Johar, Ali Khatibi, Jacquline Tham, Long Cheng   +4 more
openaire   +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

Automatic insect identification, counting, and monitoring techniques: a review

Pest Management Science, EarlyView.
Automated insect monitoring increasingly integrates optical, acoustic, infrared, radar, electrostatic, and biosensing technologies with artificial intelligence. No single approach is universally optimal; reliable deployment depends on task‐specific validation, representative datasets, robustness under field conditions, energy autonomy, connectivity ...
Mariano González García, Juan Carlos Noguera Polania, Rosana González Combarros, José Ignacio López Sánchez   +3 more
wiley   +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

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

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

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

Implementasi Algoritma Convolutional Neural Network untuk Pendeteksi Objek dalam Rumah pada Mata Rabun

Jurnal Saintekom, 2023
The increased use of laptops and smartphones during the COVID-19 pandemic has led to an increase in the number of people suffering from nearsightedness. Convolutional Neural Network (CNN) is a class of deep learning that is capable of recognizing images ...
Pramadika Egamo, Arief Hermawan
doaj   +1 more source

Fusion or Confusion? Assessing the Impact of Visible‐Thermal Image Fusion for Automated Wildlife Detection

Remote Sensing in Ecology and Conservation, EarlyView.
This study evaluates the performances of synchronous aerial visible (VIS) and thermal infrared (TIR) imagery for detecting great blue heron (Ardea herodias) nests and individuals using a YOLO11n model. VIS and TIR images were automatically aligned using deep learning, and both early and late fusion approaches were tested.
Camille Dionne‐Pierre, Samuel Foucher, Jérôme Théau, Jérôme Lemaître, Patrick Charbonneau, Maxime Brousseau, Mathieu Varin   +6 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