Fine-Tuned Temporal Dense Sampling with 1D Convolutional Neural Network for Human Action Recognition

Computer Science

• Classification Accuracy 33%
• Convolutional Neural Network 100%
• human action recognition 100%
• Image Sequence 33%
• Learning Technique 33%
• Representation Learning 66%
• Residual Neural Network 33%
• Visual Appearance 33%

Keyphrases

• Fixed-length Representation 25%
• Unpredictable Variation 25%