Dilated spatial–temporal convolutional auto-encoders for human fall detection in surveillance videos
Although methods based on supervised learning have demonstrated remarkable performance on fall detection, these existing fall detection algorithms require a substantial quantity of manually labeled training data. In this paper, we combine dilated convolution and LSTM based on auto-encoder, which can...
Main Authors: | Suyuan Li, Xin Song, Siyang Xu, Haoyang Qi, Yanbo Xue |
---|---|
Format: | Article |
Language: | English |
Published: |
Elsevier
2023-08-01
|
Series: | ICT Express |
Subjects: | |
Online Access: | http://www.sciencedirect.com/science/article/pii/S240595952200100X |
Similar Items
-
Vision-Based Fall Detection With Multi-Task Hourglass Convolutional Auto-Encoder
by: Xi Cai, et al.
Published: (2020-01-01) -
Image Geo-Site Estimation Using Convolutional Auto-Encoder and Multi-Label Support Vector Machine
by: Arpit Jain, et al.
Published: (2023-01-01) -
A Stacked Multi-Granularity Convolution Denoising Auto-Encoder
by: Yun Yang, et al.
Published: (2019-01-01) -
A Gated Dilated Causal Convolution Based Encoder-Decoder for Network Traffic Forecasting
by: Xin Zhang, et al.
Published: (2020-01-01) -
Multiple Description Coding Based on Convolutional Auto-Encoder
by: Hongfei Li, et al.
Published: (2019-01-01)