Action recognition using optimized deep autoencoder and CNN for surveillance data streams of non-stationary environments
Action recognition is a challenging research area in which several convolutional neural
networks (CNN) based action recognition methods are recently presented. However, such …
networks (CNN) based action recognition methods are recently presented. However, such …
A Deep Bidirectional LSTM Model Enhanced by Transfer-Learning-Based Feature Extraction for Dynamic Human Activity Recognition
Dynamic human activity recognition (HAR) is a domain of study that is currently receiving
considerable attention within the fields of computer vision and pattern recognition. The …
considerable attention within the fields of computer vision and pattern recognition. The …
Enhancing human action recognition in videos through dense-level features extraction and optimized long short-term memory
Human action recognition (HAR) in videos is a field currently receiving considerable
attention in computer vision and pattern recognition. While numerous researchers have …
attention in computer vision and pattern recognition. While numerous researchers have …
Generalized zero-shot learning for action recognition with web-scale video data
Action recognition in surveillance video makes our life safer by detecting the criminal events
or predicting violent emergencies. However, efficient action recognition is not free of …
or predicting violent emergencies. However, efficient action recognition is not free of …
Spatiotemporal neural networks for action recognition based on joint loss
C Jing, P Wei, H Sun, N Zheng - Neural Computing and Applications, 2020 - Springer
Action recognition is a challenging and important problem in a myriad of significant fields,
such as intelligent robots and video surveillance. In recent years, deep learning and neural …
such as intelligent robots and video surveillance. In recent years, deep learning and neural …
Maize insects classification through endoscopic video analysis
AR de Geus, MA Batista, MN Rabelo… - Advances in Artificial …, 2019 - Springer
An early identification of insects in grains is of paramount importance to avoid losses.
Instead of sampling and visual/laboratory analysis of grains, we propose carrying out the …
Instead of sampling and visual/laboratory analysis of grains, we propose carrying out the …
Celia Z. Barcelos¹, and Sérgio F. da Silva² 1 Federal University of Uberlândia, Uberlândia, Brazil {geus. andre, celiazb}@ ufu. br 2 Federal University of Goiás, Catalão …
AR de Geus¹, MA Batista… - Advances in Artificial …, 2019 - books.google.com
An early identification of insects in grains is of paramount importance to avoid losses.
Instead of sampling and visual/laboratory analysis of grains, we propose carrying out the …
Instead of sampling and visual/laboratory analysis of grains, we propose carrying out the …