Results 141 to 150 of about 2,335 (188)

FOD detection research using BSM-YOLO during construction without air service suspension. [PDF]

Sci Rep
Chu G, Ye K.
europepmc   +1 more source

Research on intelligent recognition method of mechanical parts with high feature similarity in industrial field environment. [PDF]

Sci Rep
Lu C, Ye X, Wu J, Wu F.
europepmc   +1 more source

An improved YOLOv8n model for in-field detection of pests and diseases in pakchoi. [PDF]

Front Plant Sci
Zhu Y, Han Y, Yin Y, Zhao S, Lan Y, Huang D.   +5 more
europepmc   +1 more source

Target detection for remote sensing based on the enhanced YOLOv4 with improved BiFPN

Egyptian Journal of Remote Sensing and Space Science, 2023
To solve problems for false detection, inadequate regression performance of anchor frames, and the inability to detect small targets in traditional multiscale target detection methods based on YOLOv4, we propose a novel target detection framework named as Enhanced YOLOv4.
Jingyi Cui, Guoxin Liu
exaly   +4 more sources

Enhanced YOLOv8 with BiFPN-SimAM for Precise Defect Detection in Miniature Capacitors

Applied Sciences (Switzerland)
In the domain of automatic visual inspection for miniature capacitor quality control, the task of accurately detecting defects presents a formidable challenge. This challenge stems primarily from the small size and limited sample availability of defective micro-capacitors, which leads to issues such as reduced detection accuracy and increased false ...
Zhihua Zhou, Chunming Gao
exaly   +4 more sources

A New Target Detection Method of Ferrography Wear Particle Images Based on ECAM-YOLOv5-BiFPN Network

Sensors, 2023
For mechanical equipment, the wear particle in the lubrication system during equipment operation can reflect the lubrication condition, wear mechanism, and severity of wear between equipment friction pairs.
Lei He, Qixuan Wang
exaly   +2 more sources

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Improved YOLOv5 with BiFPN on PCB Defect Detection

2021 2nd International Conference on Artificial Intelligence and Computer Engineering (ICAICE), 2021
Xiaoqi Wang, Xiangyu Zhang, Ning Zhou
exaly   +2 more sources

BiFPN-KPointNet-CBAM: Application of 3D Point Cloud Technology Based on Deep Learning in Measuring Vegetation

Electronics (Switzerland)
The results of traditional vegetation-measuring methods are mostly two-dimensional data, which can only convey limited information. The greening situation of many cities or regions in the world cannot be fully assessed by these results.
Jianmin Jiang, Fang Zou
exaly   +2 more sources

A Robust YOLOv5 Model with SE Attention and BIFPN for Jishan Jujube Detection in Complex Agricultural Environments

Agriculture (Switzerland)
This study presents an improved detection model based on the YOLOv5 (You Only Look Once version 5) framework to enhance the accuracy of Jishan jujube detection in complex natural environments, particularly with varying degrees of occlusion and dense ...
Hao Chen, Weiyi Mu, Gang Hu
exaly   +2 more sources

BiFPN-YOLO: One-stage object detection integrating Bi-Directional Feature Pyramid Networks [PDF]

Pattern Recognition
Object detection is a key component in computer vision research, allowing a system to determine the location and type of object within any given scene.
Nazmul Siddique
exaly   +2 more sources