Hyperspectral unmixing aims at decomposing a hyperspectral image (HSI) into a number of constituted materials and associated proportions. Recently, nonnegative tensor factorization (NTF) based methods ...

Hyperspectral imagery (HSI) denoising is an important preprocessing step for real-world applications. Recently, sparse representation and low-rank representation based methods are proven effective in ...

Suite of tools for deploying and training deep learning models using the JVM. Highlights include model import for keras, tensorflow, and onnx/pytorch, a modular and tiny c++ library for running math ...

adaptive-learning tensor-factorization missing-data online-learning tensor-decomposition cp-decomposition tensor-networks tensor-train parafac hosvd tensor-analysis tucker-decomposition ...