A review of deep learning with special emphasis on architectures, applications and recent trends
Deep learning (DL) has solved a problem that a few years ago was thought to be intractable—
the automatic recognition of patterns in spatial and temporal data with an accuracy superior …
the automatic recognition of patterns in spatial and temporal data with an accuracy superior …
Transformer meets remote sensing video detection and tracking: A comprehensive survey
Transformer has shown excellent performance in remote sensing field with long-range
modeling capabilities. Remote sensing video (RSV) moving object detection and tracking …
modeling capabilities. Remote sensing video (RSV) moving object detection and tracking …
A survey of the recent architectures of deep convolutional neural networks
Abstract Deep Convolutional Neural Network (CNN) is a special type of Neural Networks,
which has shown exemplary performance on several competitions related to Computer …
which has shown exemplary performance on several competitions related to Computer …
Global second-order pooling convolutional networks
Abstract Deep Convolutional Networks (ConvNets) are fundamental to, besides large-scale
visual recognition, a lot of vision tasks. As the primary goal of the ConvNets is to characterize …
visual recognition, a lot of vision tasks. As the primary goal of the ConvNets is to characterize …
Channel-attention-based DenseNet network for remote sensing image scene classification
Remote sensing image scene classification has been widely applied and has attracted
increasing attention. Recently, convolutional neural networks (CNNs) have achieved …
increasing attention. Recently, convolutional neural networks (CNNs) have achieved …
Densely attention mechanism based network for COVID-19 detection in chest X-rays
Automatic COVID-19 detection using chest X-ray (CXR) can play a vital part in large-scale
screening and epidemic control. However, the radiographic features of CXR have different …
screening and epidemic control. However, the radiographic features of CXR have different …
Deep learning approaches on defect detection in high resolution aerial images of insulators
Q Wen, Z Luo, R Chen, Y Yang, G Li - Sensors, 2021 - mdpi.com
By detecting the defect location in high-resolution insulator images collected by unmanned
aerial vehicle (UAV) in various environments, the occurrence of power failure can be timely …
aerial vehicle (UAV) in various environments, the occurrence of power failure can be timely …
Spanet: Spatial pyramid attention network for enhanced image recognition
Attention mechanism has shown great success in computer vision. In this paper, we
introduce Spatial Pyramid Attention Network (SPANet) to investigate the role of attention …
introduce Spatial Pyramid Attention Network (SPANet) to investigate the role of attention …
Extracting raft aquaculture areas from remote sensing images via an improved U-net with a PSE structure
B Cui, D Fei, G Shao, Y Lu, J Chu - Remote Sensing, 2019 - mdpi.com
Remote sensing has become a primary technology for monitoring raft aquaculture products.
However, due to the complexity of the marine aquaculture environment, the boundaries of …
However, due to the complexity of the marine aquaculture environment, the boundaries of …
Image steganalysis using deep learning: a systematic review and open research challenges
Image steganography involves the process of concealing sensitive information in the cover
image to achieve secret communication. The counterpart of steganography is image …
image to achieve secret communication. The counterpart of steganography is image …