RAM adopts RNNs and reinforcement learning (RL) to make the network learn where to pay attention.
Source: Recurrent Models of Visual AttentionPaper | Code | Results | Date | Stars |
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Task | Papers | Share |
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Image Classification | 10 | 8.33% |
Quantization | 6 | 5.00% |
Semantic Segmentation | 6 | 5.00% |
Edge-computing | 5 | 4.17% |
Retrieval | 3 | 2.50% |
Federated Learning | 3 | 2.50% |
Self-Supervised Learning | 2 | 1.67% |
Image Segmentation | 2 | 1.67% |
Object Detection | 2 | 1.67% |
Component | Type |
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🤖 No Components Found | You can add them if they exist; e.g. Mask R-CNN uses RoIAlign |