Over the past years, computer scientists have introduced increasingly sophisticated generative AI models that can produce ...

To address low detection accuracy in SAR images due to complex backgrounds, large scale variations, and small targets, an improved algorithm SRA-DETR based on RT-DETR is proposed. It uses repBlock on ...

To address the shortcomings of classical chaotic time series in image encryption algorithms in terms of low complexity, fewer control parameters, and limited range of value domains, this paper ...

An Efficient Encoding Spectral Information in Hyperspectral Images for Transfer Learning of Mask R-CNN for Instance Segmentation of Tomato Sepals ...

The models currently used for polarimetric synthetic aperture radar (PolSAR) image classification tasks have problems, such as complex network structures, poor distinction of detailed features, and ...

Image semantic segmentation based on deep learning has made great progress in recent years. This paper summarizes the application and development of convolutional neural network (CNN), full ...

With the rapid advancement of multi-source imaging technology, image fusion has become crucial in image processing. This technique combines data from various modalities to produce rich fused images ...

After trying to conceive for 18 years, one couple is now pregnant with their first child thanks to the power of artificial intelligence. The couple had undergone several rounds of in vitro ...

Deterministic processing time are no longer applicable under realistic circumstances because of the uncertainties involved in manufacturing and production processes. The present study aims to address ...

Early recognition of plant diseases is important to crop losses and ensure agricultural yields. Traditional manual methods are difficult,time-consuming, and unreliable, especially on large farms. This ...

In the present days, Image Captioning plays a crucial role in transforming the visual content to textual format. It combines computer vision (to read the image) and natural language processing (to ...

KM-Prompt: A Prompt-Based CNN for Continual Learning Abstract: Deep neural networks have achieved remarkable success in many applications but often suffer from catastrophic forgetting—a significant ...