Abstract: In this article, we propose a minimum simplex convolutional network (MiSiCNet) for deep hyperspectral unmixing. Unlike all the deep learning-based unmixing methods proposed in the literature ...

Yaxin Hou, Jun Ma, Hanyang Li, Bo Han, Jie Yu, Yuheng Jia, Beyond Distribution Estimation: Simplex Anchored Structural Inference Towards Universal Semi-Supervised Learning, International Conference on ...

We consider the problem of fitting a reinforcement learning (RL) model to some given behavioral data under a multi-armed bandit environment. These models have received much attention in recent years ...

TSFitPy is a pipeline designed to determine stellar abundances and atmospheric parameters through the use of Nelder-Mead (simplex algorithm) minimization. It calculates model spectra "on the fly" ...

CJ Blossom Park, CJ BIO Research Institute, 55, Gwanggyo-ro 42beon-gil, Yeongtong-gu, Suwon-Si, Gyeonggi-do 16495, Republic of Korea ...

With the recent explosion in the amount, the variety, and the dimensionality of available data, identifying, extracting, and exploiting their underlying structure has become a problem of fundamental ...

Abstract: In this article, we introduce a deep learning-based technique for the linear hyperspectral unmixing problem. The proposed method contains two main steps. First, the endmembers are extracted ...