Results 181 to 190 of about 23,891 (225)

Bidirectional Feature Pyramid Siamese Anomaly Detection Network With Cellular Anomaly Generation for Container Marking

IEEE Transactions on Instrumentation and Measurement
Container marking anomaly detection (CMAD) aims to identify markings that deviate from a standard reference image. Currently, the manual execution of CMAD is inefficient and susceptible to errors.
Yikui Zhai, Wenfeng Pan, Yanyang Liang   +2 more
exaly   +3 more sources

An Insulator defect detection network combining bidirectional feature pyramid network and attention mechanism in unmanned aerial vehicle images

Engineering Applications of Artificial Intelligence
Xiaoxia Yang, Ronghao Yang
exaly   +3 more sources

A New Feature Pyramid Network With Bidirectional Jump Connection Network for Small Defect Detection on Solar PV Wafer

IEEE Sensors Journal
Photovoltaic (PV) wafers are the core component of solar cells, and detection of their surface defects is critical to improving the reliability of solar cell. The intricacies inherent of wafer production process give rise to numerous small defects on the
Jianan Wei, Long Wen, Shihang Fan
exaly   +3 more sources

Construction Vehicle Detection Model Based on Bidirectional-path Cosine Self-attention Feature Pyramid Network

2024 8th International Symposium on Computer Science and Intelligent Control (ISCSIC)
The safety of power grid is easy to be influenced by the mobile operation of construction vehicles under overhead transmission lines. Detection of construction vehicles around transmission channels can effectively ensure the safety of power supply.
Haiyan Feng
exaly   +3 more sources

CB-FPN: object detection feature pyramid network based on context information and bidirectional efficient fusion

Pattern Analysis and Applications, 2023
Zhibo Liu, Liu Zhibo, Cheng Jian
exaly   +3 more sources

Bidirectional Feature Pyramid Network with Recurrent Attention Residual Modules for Shadow Detection

European Conference on Computer Vision, 2018
This paper presents a network to detect shadows by exploring and combining global context in deep layers and local context in shallow layers of a deep convolutional neural network (CNN). There are two technical contributions in our network design. First, we formulate the recurrent attention residual (RAR) module to combine the contexts in two adjacent ...
Lei Zhu, Zijun Deng, Xiaowei Hu, Chi-Wing Fu, Xuemiao Xu, J. Qin, P. Heng   +6 more
semanticscholar   +2 more sources

Research on Small-Target Detection of Flax Pests and Diseases in Natural Environment by Integrating Similarity-Aware Activation Module and Bidirectional Feature Pyramid Network Module Features

Agronomy
In the detection of the pests and diseases of flax, early wilt disease is elusive, yellow leaf disease symptoms are easily confusing, and pest detection is hampered by issues such as diversity in species, difficulty in detection, and technological ...
Manxi Zhong, Yue Li, Yuhong Gao
semanticscholar   +2 more sources

Siamese network with bidirectional feature pyramid for small target tracking

Journal of Electronic Imaging, 2021
. To address the tracking challenges such as weak feature expression ability of small targets and susceptibility to interference by similar objects in complex backgrounds, we use the principle of feature enhancement in the field of small target detection
Lei Liu, Guangqian Kong, Xun Duan, Yun Wu, Huiyun Long   +4 more
semanticscholar   +2 more sources

An Effective Object Tracking Using Yolov3 with Bidirectional Feature Pyramid Network on Video Surveillance

2023 3rd International Conference on Mobile Networks and Wireless Communications (ICMNWC), 2023
Deep learning enhances precision and efficiency in object tracking, enabling applications in autonomous vehicles and surveillance while adapting to dynamic environments.
Hassan M. Al-Jawahry, M. Alkhafaji, Gobinath Ravindran, P. S, A. H. A. Hussein   +4 more
semanticscholar   +2 more sources

An embedded feature pyramid network enables bidirectional information flow for object detection and instance segmentation

Neurocomputing
Lian-Zhi Huo, Shengjiang Chang, Zhiqing Zhang   +2 more
exaly   +3 more sources