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Action recognition in video sequences using deep bi-directional LSTM with CNN features
Recurrent neural network (RNN) and long short-term memory (LSTM) have achieved great
success in processing sequential multimedia data and yielded the state-of-the-art results in …
success in processing sequential multimedia data and yielded the state-of-the-art results in …
Deep features-based speech emotion recognition for smart affective services
Emotion recognition from speech signals is an interesting research with several applications
like smart healthcare, autonomous voice response systems, assessing situational …
like smart healthcare, autonomous voice response systems, assessing situational …
Object detection based on multi-layer convolution feature fusion and online hard example mining
J Chu, Z Guo, L Leng - IEEE access, 2018 - ieeexplore.ieee.org
Object detection is a significant issue in visual surveillance. Faster region-based
convolutional neural network (R-CNN) is a typical object detection algorithm of deep …
convolutional neural network (R-CNN) is a typical object detection algorithm of deep …
Physics inspired methods for crowd video surveillance and analysis: a survey
X Zhang, Q Yu, H Yu - IEEE Access, 2018 - ieeexplore.ieee.org
Crowd analysis is very important for human behavior analysis, safety science, computational
simulation, and computer vision applications. One of the most popular applications is video …
simulation, and computer vision applications. One of the most popular applications is video …
Large-scale person re-identification for crowd monitoring in emergency
The task of associating photographs/videos of an individual obtained from the same camera
on various occasions or across cameras is called Person Re-identification (PRId). Computer …
on various occasions or across cameras is called Person Re-identification (PRId). Computer …
Review on recent advances in human action recognition in video data
A Baisware, B Sayankar, S Hood - 2019 9th International …, 2019 - ieeexplore.ieee.org
AI has achieved new heights in image recognition, human action recognition and NLP. It has
a vast area of implementations such as IoT, robotics, biosciences and surveillance. Video …
a vast area of implementations such as IoT, robotics, biosciences and surveillance. Video …
Video-based abnormal driving behavior detection via deep learning fusions
Video-based abnormal driving behavior detection is becoming more and more popular for
the time being, as it is highly important in ensuring safeties of drivers and passengers in the …
the time being, as it is highly important in ensuring safeties of drivers and passengers in the …
Person re-identification with features-based clustering and deep features
Person re-identification (ReID) is an imperative area of pedestrian analysis and has practical
applications in visual surveillance. In the person ReID, the robust feature representation is a …
applications in visual surveillance. In the person ReID, the robust feature representation is a …
Person re-identification: A taxonomic survey and the path ahead
Person re-identification (PRId) is one of the most challenging tasks in automated video
surveillance and has been an area of intense research spanning the past decade. PRId …
surveillance and has been an area of intense research spanning the past decade. PRId …
Multi-level feature network with multi-loss for person re-identification
H Wu, M **n, W Fang, HM Hu, Z Hu - IEEE Access, 2019 - ieeexplore.ieee.org
Person re-identification has become a challenging task due to various factors. One key to
effective person re-identification is the extraction of the discriminative features of a person's …
effective person re-identification is the extraction of the discriminative features of a person's …