56Fe/Nearest-Neighbour-Search-Neural-Networks-Product-Quantization: Code for: Ferro, D., Gripon, V. and Jiang, X., 2016, July. Nearest neighbour search using binary neural networks. In 2016 International Joint Conference on Neural Networks (IJCNN) (pp. 5106-5112). IEEE. The code finds nearest neighbours in terms of Euclidean distance, and uses it for classification. The search is optimized by combining Product Quantization (PQ) and binary neural associative memories (Willshaw Neural Networks). DOI

Download data from MNIST handwritten digits

(http://yann.lecun.com/exdb/mnist/)

and store all of the following in this folder:

../MNIST/Data/t10k-images.idx3-ubyte
../MNIST/Data/t10k-images-bw.bin
../MNIST/Data/t10k-labels.idx1-ubyte
../MNIST/Data/train-images.idx3-ubyte
../MNIST/Data/train-images-bw.bin
../MNIST/Data/train-labels.idx1-ubyte

readme-data.md 355 B Пермалинк Историја Download

readme-data.md 355 B

Пермалинк Историја Download