Optokinetic Nystagmus (OKN) is a natural reflexive eye movement in oculomotor studies, reflecting the health status of the visual system. Through accurate eye center annotation, physicians can observe ...

Abstract: Deep convolutional neural networks can use hierarchical information to progressively extract structural information to recover high-quality images. However, preserving the effectiveness of ...

CNN in deep learning is a special type of neural network that can understand images and visual information. It works just like human vision: first it detects edges, lines and then recognizes faces and ...

Hyperspectral images (HSIs) have very high dimensionality and typically lack sufficient labeled samples, which significantly challenges their processing and analysis. These challenges contribute to ...

Abstract: Image Super-Resolution (SR) has emerged as a critical task in various domains, allowing low-resolution (LR) photographs to be improved into their high-resolution (HR) equivalents. This study ...

Deep learning-based image steganalysis has progressed in recent times, with efforts more concerted toward prioritizing detection accuracy over lightweight frameworks. In the context of AI-driven ...

A group of scientists led by researchers from the University of New South Wales (UNSW) in Australia has developed a novel deep-learning method for denoising outdoor electroluminescence (EL) images of ...

If you find FDSSC useful in your research, please consider citing. Chicago/Turabian Style: Wang, Wenju; Dou, Shuguang; Jiang, Zhongmin; Sun, Liujie. 2018. "A Fast Dense Spectral–Spatial Convolution ...