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Found 3 papers, 0 papers with code
Denoising random forests
A denoising autoencoder can be trained with indicator vectors produced from clean and noisy input samples, and non-leaf nodes where incorrect decisions are made can be identified by comparing the input and output of the trained denoising autoencoder.
Binary-decomposed DCNN for accelerating computation and compressing model without retraining
Our method replaces real-valued inner-product computations with binary inner-product computations in existing network models to accelerate computation of inference and decrease model size without the need for retraining.
Multiple-Hypothesis Affine Region Estimation With Anisotropic LoG Filters
We propose a method for estimating multiple-hypothesis affine regions from a keypoint by using an anisotropic Laplacian-of-Gaussian (LoG) filter.
