FBNet is a type of convolutional neural architectures discovered through DNAS neural architecture search. It utilises a basic type of image model block inspired by MobileNetv2 that utilises depthwise convolutions and an inverted residual structure (see components).
Source: FBNet: Hardware-Aware Efficient ConvNet Design via Differentiable Neural Architecture SearchPaper | Code | Results | Date | Stars |
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Task | Papers | Share |
---|---|---|
Image Classification | 3 | 18.75% |
Semantic Segmentation | 2 | 12.50% |
Meta-Learning | 1 | 6.25% |
Point Cloud Completion | 1 | 6.25% |
Autonomous Driving | 1 | 6.25% |
Image Segmentation | 1 | 6.25% |
Scene Segmentation | 1 | 6.25% |
Quantization | 1 | 6.25% |
Depth Estimation | 1 | 6.25% |