Human action recognition using attention based LSTM network with dilated CNN features
Human action recognition in videos is an active area of research in computer vision and
pattern recognition. Nowadays, artificial intelligence (AI) based systems are needed for …
pattern recognition. Nowadays, artificial intelligence (AI) based systems are needed for …
Deep image-to-video adaptation and fusion networks for action recognition
Existing deep learning methods for action recognition in videos require a large number of
labeled videos for training, which is labor-intensive and time-consuming. For the same …
labeled videos for training, which is labor-intensive and time-consuming. For the same …
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 …
A Swarm Intelligence Assisted IoT-Based Activity Recognition System for Basketball Rookies
Recent years have witnessed many applications of wearable sensor technology and
machine learning on smart sports training, eg, basketball. For rookie players, the …
machine learning on smart sports training, eg, basketball. For rookie players, the …
Behavior recognition based on the improved density clustering and context-guided Bi-LSTM model
T Zhou, A Tao, L Sun, B Qu, Y Wang… - Multimedia Tools and …, 2023 - Springer
Context information is vital to research video human behavior recognition. Under the LSTM
together with CNN of the framework, a novel action recognition method, which extracts …
together with CNN of the framework, a novel action recognition method, which extracts …
Self-updatable database system based on human motion assessment framework
Recently, human motion-centric videos have been attracting attention in the field of
computer vision. Observing and detecting human motion in intelligent surveillance camera …
computer vision. Observing and detecting human motion in intelligent surveillance camera …
A context-aware capsule network for multi-label classification
Abstract Recently proposed Capsule Network is a brain inspired architecture that brings a
new paradigm to deep learning by modelling input domain variations through vector based …
new paradigm to deep learning by modelling input domain variations through vector based …
Understanding Long Videos in One Multimodal Language Model Pass
Large Language Models (LLMs), known to contain a strong awareness of world knowledge,
have allowed recent approaches to achieve excellent performance on Long-Video …
have allowed recent approaches to achieve excellent performance on Long-Video …
Task activity recognition and workspace extraction for nursing care assistance in intelligent space
K Sakotani, S Kato, M Niitsuma… - 2020 IEEE/SICE …, 2020 - ieeexplore.ieee.org
With the rapid increase in the elderly population, there is a shortage of caregivers in Japan.
Consequently, the workload per caregiver has increased, which is now a major social issue …
Consequently, the workload per caregiver has increased, which is now a major social issue …
Pose identification for task recognition in care work
In Japan, the number of caregivers is not increasing with the same rate as the aging of the
population, resulting in an increased workload per caregiver, which has become a social …
population, resulting in an increased workload per caregiver, which has become a social …