DetNASNet is a convolutional neural network designed to be an object detection backbone and discovered through DetNAS architecture search. It uses ShuffleNet V2 blocks as its basic building block.
Source: DetNAS: Backbone Search for Object DetectionPaper | Code | Results | Date | Stars |
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Task | Papers | Share |
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General Classification | 1 | 33.33% |
Image Classification | 1 | 33.33% |
Object Detection | 1 | 33.33% |
Component | Type |
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Batch Normalization
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Normalization | |
Convolution
|
Convolutions | |
ReLU
|
Activation Functions | |
ShuffleNet V2 Block
|
Image Model Blocks |