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Found 4 papers, 1 papers with code
FSD: Fully-Specialized Detector via Neural Architecture Search
Most generic object detectors are mainly built for standard object detection tasks such as COCO and PASCAL VOC.
Scale Calibrated Training: Improving Generalization of Deep Networks via Scale-Specific Normalization
Experiment results show that SCT improves accuracy of single Resnet-50 on ImageNet by 1. 7% and 11. 5% accuracy when testing on image sizes of 224 and 128 respectively.
SSN: Learning Sparse Switchable Normalization via SparsestMax
Unlike $\ell_1$ and $\ell_0$ constraints that impose difficulties in optimization, we turn this constrained optimization problem into feed-forward computation by proposing SparsestMax, which is a sparse version of softmax.
A Main/Subsidiary Network Framework for Simplifying Binary Neural Network
To reduce memory footprint and run-time latency, techniques such as neural network pruning and binarization have been explored separately.
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