Memristive and nanoionic devices have recently emerged as leading candidates for
neuromorphic computing architectures. While top-down fabrication based on conventional …

With the rapid development of spectral imaging techniques, classification of hyperspectral
images (HSIs) has attracted great attention in various applications such as land survey and …

A multiple-feature-based adaptive sparse representation (MFASR) method is proposed for
the classification of hyperspectral images (HSIs). The proposed method mainly includes the …

In remote sensing, hyperspectral unmixing is very challenging inverse ill-posed problem
which does not have closed-form solution. Since more than three decades, several …

Spiking neural networks exploit spatiotemporal processing, spiking sparsity, and high
interneuron bandwidth to maximize the energy efficiency of neuromorphic computing. While …

Neural networks (NNs) are recognized as very effective techniques when facing complex
retrieval tasks in remote sensing. In this paper, the potential of NNs has been applied in …

A general self-aligned fabrication scheme is reported here for a diverse class of electronic
devices based on van der Waals materials and heterojunctions. In particular, self-alignment …

Ensembles of extreme learning machine (ELM) have been widely used for hyperspectral
image classification. The previous studies have shown that the goal of ensemble learning is …

El amplio uso de las redes neuronales en el campo del procesamiento de imágenes, motiva
a realizar una revisión de 200 artículos donde se documentan algoritmos que utilizan …

Remarkable advancements in the computational techniques and nanoelectronics have
attracted considerable interests for development of highly-sophisticated materials (Ms) …