Spectral Images (SI) are acquired at multiple wavelengths across the electromagnetic spectrum, providing information that enhances performance in tasks such as material segmentation and classification by resolving ambiguities inherent in RGB images. …
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 …
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 …
Drone detection under high-illumination conditions remains a critical challenge due to sensor saturation, which degrades visual information and limits the performance of conventional detection models. A promising alternative to overcome this issue is …
Image acquisition in low-light environments is fundamentally challenging due to the photon-limited nature of the scene, which results in severe noise and incomplete color information. Imaging sensors operating under such conditions require robust …