Images generated by artificial intelligence (AI) are often almost indistinguishable from real images to the human eye.

Scientists in Tokyo have developed a groundbreaking, label-free method to identify aging human cells using electric fields.

A new technical paper titled “Domain Adaptation for Image Classification of Defects in Semiconductor Manufacturing” was ...

Recently, text-based image generation models can automatically create high-resolution, high-quality images solely from ...

ABSTRACT: Convolutional auto-encoders have shown their remarkable performance in stacking deep convolutional neural networks for classifying image ... autoencoder. Although it is an unsupervised ...

Abstract: This article introduces a two-phase learning approach for hyperspectral image (HSI) classification using few-shot learning (FSL). For the first phase, we present a novel spatiospectral ...

self-supervised learning has become an effective method for hyperspectral image classification. The core idea of self-supervised learning is to define a pretext task, which helps to train the model ...

This paper is a valuable step in multi-subject behavioral modeling using an extension of the Variational Autoencoder (VAE ... of four different mice. A. Image reconstruction result for an example ...

One possible alternative direction for using DL techniques in psychiatric neuroimaging studies may be diagnostic label-free feature extraction. In the current study, we focus on an autoencoder ... the ...