Spatio-temporal self-attention network for fire detection and segmentation in video surveillance
M Shahid, JJ Virtusio, YH Wu, YY Chen… - Ieee …, 2021 - ieeexplore.ieee.org
Convolutional Neural Networks (CNNs) based approaches are popular for various
image/video related tasks due to their state-of-the-art performance. However, for problems …
image/video related tasks due to their state-of-the-art performance. However, for problems …
Deep learning for risk detection and trajectory tracking at construction sites
Y Zhao, Q Chen, W Cao, J Yang, J Xiong, G Gui - IEEE Access, 2019 - ieeexplore.ieee.org
This paper investigates deep learning for risk detection and trajectory tracking at
construction sites. Typically, safety officers are responsible for inspecting and verifying site …
construction sites. Typically, safety officers are responsible for inspecting and verifying site …
Headnet: An end-to-end adaptive relational network for head detection
Head detection plays an important role in localizing and identifying persons from visual data.
Most existing methods treat head detection as a specific form of object detection. Head …
Most existing methods treat head detection as a specific form of object detection. Head …
Non-blind image deblurring method by the total variation deep network
There are a lot of non-blind image deblurring methods, especially with the total variation
(TV) model-based method. However, how to choose the parameters adaptively for …
(TV) model-based method. However, how to choose the parameters adaptively for …
Object-level trajectories based fine-grained action recognition in visual IoT applications
The emerging computer vision and deep learning technologies are being applied to the
intelligent analysis of sports training videos. In this paper, a deep learning based fine …
intelligent analysis of sports training videos. In this paper, a deep learning based fine …
A fast cabac hardware design for accelerating the rate estimation in hevc
Y Cai, Y Fan, L Huang, X Zeng, H Yin… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
The latest High Efficiency Video Coding standard achieves twice the coding efficiency of the
H264 standard through a complex rate-distortion optimization (RDO). The coded bit-streams …
H264 standard through a complex rate-distortion optimization (RDO). The coded bit-streams …
SWNet: a deep learning based approach for splashed water detection on road
Adverse weather conditions seriously threaten the traffic safety, especially for rainy days with
the ponding water on the road surface, which potentially result in vehicle crashes, person …
the ponding water on the road surface, which potentially result in vehicle crashes, person …
CNN-based skip-gram method for improving classification accuracy of chinese text
W Xu, H Huang, J Zhang, H Gu, J Yang… - KSII Transactions on …, 2019 - koreascience.kr
Text classification is one of the fundamental techniques in natural language processing.
Numerous studies are based on text classification, such as news subject classification …
Numerous studies are based on text classification, such as news subject classification …
Weighting quantization matrices for HEVC/H. 265-coded RGB videos
In the HEVC/H. 265 video coding standard, weighting quantization matrices (WQMs) are
supported to take advantage of the characteristics of the human visual system (HVS) …
supported to take advantage of the characteristics of the human visual system (HVS) …
Joint optimization of transform and quantization for high efficiency video coding
M Wang, W Xie, J Xiong, D Wang, J Qin - IEEE access, 2019 - ieeexplore.ieee.org
In high efficiency video coding (HEVC), transformation and quantization are separately
performed to eliminate the perceptual redundancy of visual signals. However, a uniform …
performed to eliminate the perceptual redundancy of visual signals. However, a uniform …