Optimized Temporal Convolutional Networks with Multi-Stage Attention for Efficient Human Action Recognition

Deepthi Reddy Sama; Pranay Goud Pulimamidi; Nikhileshwar Reddy Japa; Bhanu Prasad Andraju

doi:10.1109/ictcs65341.2025.10989290

ScienceGate Book Chapters

JOURNAL ARTICLE

Optimized Temporal Convolutional Networks with Multi-Stage Attention for Efficient Human Action Recognition

Deepthi Reddy Sama Pranay Goud Pulimamidi Nikhileshwar Reddy Japa Bhanu Prasad Andraju

Year: 2025 Pages: 78-81

DOI: 10.1109/ictcs65341.2025.10989290

Get Full-Text PDF Get Analytical Report

Keywords:

Computer science Action recognition Action (physics) Convolutional neural network Artificial intelligence Pattern recognition (psychology) Speech recognition Physics

Metrics

Cited By

0.00

FWCI (Field Weighted Citation Impact)

Refs

0.14

Citation Normalized Percentile

Is in top 1%

Is in top 10%

Topics

Human Pose and Action Recognition

Physical Sciences → Computer Science → Computer Vision and Pattern Recognition

Anomaly Detection Techniques and Applications

Physical Sciences → Computer Science → Artificial Intelligence

Gait Recognition and Analysis

Physical Sciences → Engineering → Biomedical Engineering

Optimized Temporal Convolutional Networks with Multi-Stage Attention for Efficient Human Action Recognition

Metrics

Topics

Related Documents

MULTI-Stream Graph Convolutional Networks with Efficient spatial-temporal Attention for Skeleton-based Action Recognition

Human Action Recognition in Multi-Level Convolutional Temporal Attention Network

AMC-OA: Adaptive Multi-Scale Convolutional Networks with Optimized Attention for Temporal Action Localization

Multi-stage Temporal Graph Convolutional Networks for Skeleton-Based Action Recognition

Enhancing Video Action Recognition with Spatial–Temporal Convolutional Attention Networks