Results 71 to 80 of about 2,448 (190)

An Improved YOLOv11 Method With Mamba Module for Multiscale Tea Disease Detection

Journal of Electrical and Computer Engineering, Volume 2026, Issue 1, 2026.
Deep network–based models have been widely applied in smart agriculture, including tea disease detection tasks. However, the inference of existing deep models requires a large amount of computing resources and storage space, making it difficult to effectively deploy on mobile devices.
Yun Pan, Deepali
wiley   +1 more source

CASPNet++: Joint Multi-Agent Motion Prediction

, 2023
The prediction of road users' future motion is a critical task in supporting advanced driver-assistance systems (ADAS). It plays an even more crucial role for autonomous driving (AD) in enabling the planning and execution of safe driving maneuvers. Based
Kummert, Anton, Schäfer, Maximilian, Zhao, Kun   +2 more
core  

A Detection Method of Pine Wilt Disease Based on Improved YOLOv11 With UAV Remote Sensing Images

Ecology and Evolution, Volume 15, Issue 12, December 2025.
The proposed YOLOv11‐OC model enhances detection performance in PWD‐infected trees in two main ways. On one hand, the omni‐dimensional dynamic convolution (ODConv) module improves the C3K2 by using a multi‐dimensional attention mechanism to adaptively adjust the convolution kernel weights, thereby enhancing the model's ability to extract features from ...
Hua Shi, Zhenhui Zhu, Xiaozhou Feng, Yufen Xie, Hui Guo, Pengxiang Xue, Yonghang Wang   +6 more
wiley   +1 more source

Improved Tomato Leaf Disease Recognition Based on the YOLOv5m with Various Soft Attention Module Combinations

Agriculture
To reduce production costs, environmental effects, and crop losses, tomato leaf disease recognition must be accurate and fast. Early diagnosis and treatment are necessary to cure and control illnesses and ensure tomato output and quality. The YOLOv5m was
Yong-Suk Lee, Maheshkumar Prakash Patil, Jeong Gyu Kim, Seong Seok Choi, Yong Bae Seo, Gun-Do Kim   +5 more
doaj   +1 more source

Multi-task learning in Computer Vision [PDF]

, 2020
With modern computer vision algorithms, it is possible to solve many different kinds of problems, such as object detection, image classification, and image segmentation.
Kutvonen, Konsta
core  

PSH‐YOLO: A Detection Method for Small‐Target Thermal Defects in Porcelain Insulators

Energy Science &Engineering, Volume 13, Issue 12, Page 6253-6265, December 2025.
It clearly presents the differences between You Only Look Once v8 (YOLOv8) and the improved Porcelain insulator Small‐target Heating defect detection You Only Look Once (PSH‐YOLO) in each core module of the network structure in a comparative form, intuitively demonstrating the algorithm improvement logic.
Pei Shaotong, Tian Xu, Wang Weiqi, Li Keyu, Hu Chenlong   +4 more
wiley   +1 more source

End‐to‐end instance segmentation framework for automated pavement distress assessment using unmanned aerial vehicle‐derived digital orthophoto maps

Computer-Aided Civil and Infrastructure Engineering, Volume 40, Issue 24, Page 4055-4075, 6 October 2025.
Abstract This study presents a novel framework for automated detection and segmentation of pavement distresses using high‐resolution digital orthophoto maps captured by unmanned aerial vehicles (UAVs). While recent UAV‐based research often relies on manual measurements from rasterized digital models, only a few studies have employed automated methods ...
Zia U. A. Zihan, Omar Smadi, Inya Nlenanya   +2 more
wiley   +1 more source

BCM‐YOLO: An improved YOLOv8‐based lightweight porcelain insulator defect detection model

High Voltage, Volume 10, Issue 4, Page 876-889, August 2025.
Abstract Porcelain insulator is an important component of power transmission systems, and its condition detection is essential to ensure safe operation of the power grid. Nevertheless, it is difficult for existing detection models to effectively solve the contradiction between detection accuracy and resource consumption.
Feng Bin, Fan Hou, Da Chen, Kang Qiu, Xiaofeng Lu, Qiuqin Sun   +5 more
wiley   +1 more source

VB-SOLO: Single-Stage Instance Segmentation of Overlapping Epithelial Cells

IEEE Access
The instance segmentation of overlapping cells in smear images of epithelial cells is challenging due to the significant overlap and adhesion between the cells’ translucent cytoplasm.
Lichuan Li, Wei Chen, Jie Qi
doaj   +1 more source

The DCN-BiFPN Object Detection Algorithm based on YOLOv8

Abstract Aiming at the problems of traditional target detection algorithms such as high demand for model equipment, low detection accuracy, high leakage rate of overlapping targets, and repeated detection of the same target, we propose an improved multilayer deformable convolution as well as a method for fusing attention mechanisms, and use ...
Bo Yu, Shun Li, Wei Wang, Yuanze Meng, Dongying Liu   +4 more
openaire   +1 more source