Deep Learning

Lightweight unrolled deep network with self-supervised adaptation for high dynamic range recovery from modulo measurements.

A computational correction strategy for eye aberrations, specifically targeting astigmatism, is proposed. This method computationally designs a transformed image that allows individuals with astigmatism to perceive the original scene with improved …

Self-supervised image reconstruction and denoising framework extending recorrupted-to-recorrupted beyond Gaussian noise.

Object detection precision is crucial for ensuring the safety and efficacy of autonomous driving systems. The quality of acquired images directly influences the ability of autonomous driving systems to correctly recognize and respond to other …

Overview of data-driven and end-to-end deep optical coding design in computational imaging.

Deep learning framework for joint non-linear representation and compressive spectral reconstruction.

This study presents an automated system for classifying the fermentation levels of cocoa beans using convolutional neural networks, specifically employing YOLO-based object detection models. RGB images of cocoa beans, which were cut using a …