PDS-Net: A novel point and depth-wise separable convolution for real-time object detection

Keyphrases

• MS COCO 100%
• Real-time Object Detection 100%
• Depthwise Separable Convolution 100%
• Feature Pyramid Network 66%
• VOCs 66%
• Spatial Features 66%
• PASCAL VOC 66%
• Convolutional Neural Network 33%
• Object Detection 33%
• Computational Cost 33%
• Object Classification 33%
• Transformer 33%
• Object Detector 33%
• Overfitting 33%
• Cost Efficiency 33%
• Computation Time 33%
• Low Performance 33%
• Realistic Scenario 33%
• Separable Convolution 33%
• Lightweight Model 33%
• Feature Fusion Module 33%
• Object Classifier 33%
• Level Characteristic Values 33%
• Low Efficiency 33%
• Multi-scale Features 33%
• Simultaneous Processing 33%
• Single GPU 33%
• Encoder-decoder 33%
• COCO Dataset 33%
• Efficient Architecture 33%
• Depth Feature 33%

Computer Science

• Object Detection 100%
• Convolutional Neural Network 50%
• Feature Fusion 50%
• Object Detector 50%
• Use Point 50%
• Object Classifier 50%
• Computational Cost 50%
• Computation Time 50%
• Graphics Processing Unit 50%