Abstract Human Action Recognition (HAR) involves human activity monitoring task in
different areas of medical, education, entertainment, visual surveillance, video retrieval, as …

Tool condition monitoring and machine tool diagnostics are performed using advanced
sensors and computational intelligence to predict and avoid adverse conditions for cutting …

This is a survey paper that aims to give reviews about that finest architectures of machine
learning, the use of algorithms and the applications of the system and speech and vision …

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 …

Detecting actions in untrimmed videos is an important yet challenging task. In this paper, we
present the structured segment network (SSN), a novel framework which models the …

Person re-identification (re-ID) has become increasingly popular in the community due to its
application and research significance. It aims at spotting a person of interest in other …

In this paper, we address self-supervised representation learning from human skeletons for
action recognition. Previous methods, which usually learn feature presentations from a …

This survey presents a review of state-of-the-art deep neural network architectures,
algorithms, and systems in speech and vision applications. Recent advances in deep …

Every moment counts in action recognition. A comprehensive understanding of human
activity in video requires labeling every frame according to the actions occurring, placing …

The convolutional neural network architecture has different components like convolution and
pooling. The pooling is crucial component placed after the convolution layer. It plays a vital …