CRRN: Multi-scale guided concurrent reflection removal network
Removing the undesired reflections from images taken through the glass is of broad
application to various computer vision tasks. Non-learning based methods utilize different …
application to various computer vision tasks. Non-learning based methods utilize different …
A composite model of wound segmentation based on traditional methods and deep neural networks
F Li, C Wang, X Liu, Y Peng… - Computational intelligence …, 2018 - Wiley Online Library
Wound segmentation plays an important supporting role in the wound observation and
wound healing. Current methods of image segmentation include those based on traditional …
wound healing. Current methods of image segmentation include those based on traditional …
CoRRN: Cooperative reflection removal network
Removing the undesired reflections from images taken through the glass is of broad
application to various computer vision tasks. Non-learning based methods utilize different …
application to various computer vision tasks. Non-learning based methods utilize different …
DFNet: Discriminative feature extraction and integration network for salient object detection
Despite the powerful feature extraction capability of Convolutional Neural Networks, there
are still some challenges in saliency detection. In this paper, we focus on two aspects of …
are still some challenges in saliency detection. In this paper, we focus on two aspects of …
OR-Skip-Net: Outer residual skip network for skin segmentation in non-ideal situations
Skin segmentation is one of the most important tasks for human activity recognition, video
monitoring, face detection, hand gesture recognition, content-based detection, adult content …
monitoring, face detection, hand gesture recognition, content-based detection, adult content …
Convolutional neural networks and training strategies for skin detection
This paper presents two convolutional neural networks (CNN) and their training strategies
for skin detection. The first CNN, consisting of 20 convolution layers with 3× 3 filters, is a kind …
for skin detection. The first CNN, consisting of 20 convolution layers with 3× 3 filters, is a kind …
Reduction of video compression artifacts based on deep temporal networks
It has been shown that deep convolutional neural networks (CNNs) reduce JPEG
compression artifacts better than the previous approaches. However, the latest video …
compression artifacts better than the previous approaches. However, the latest video …
Design of cyber-physical-social systems with forensic-awareness based on deep learning
B Yang, H Guo, E Cao - Advances in Computers, 2021 - Elsevier
Cyber-physical-social systems (CPSSs) contain integrated cyber parts, including computing,
communication, and physical parts; it uses computations and communication embedded in …
communication, and physical parts; it uses computations and communication embedded in …
Target attention deep neural network for infrared image enhancement
The inherent high background radiation and low contrast of infrared images severely cripple
the precision of target detection and recognition. However, existing infrared image …
the precision of target detection and recognition. However, existing infrared image …
NU-LiteNet: Mobile landmark recognition using convolutional neural networks
C Termritthikun, S Kanprachar… - arXiv preprint arXiv …, 2018 - arxiv.org
The growth of high-performance mobile devices has resulted in more research into on-
device image recognition. The research problems are the latency and accuracy of automatic …
device image recognition. The research problems are the latency and accuracy of automatic …