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In recent years, deep neural network tasks have increasingly relied on high-quality image inputs. With the development of high-resolution representation learning, the task of image dehazing has ...

Improve this page Add a description, image, and links to the basic-image-recognition-algorithms topic page so that developers can more easily learn about it. Curate this topic ...

In remote sensing image processing for Earth and environmental applications, super-resolution (SR) is a crucial technique for enhancing the resolution of low-resolution (LR) images. In this study, we ...

Different molecular representations exist to provide visual and mathematical means to depict complex structures. However, the detailing required for algorithmic applications remains a challenge. This ...

We propose a structured approach to the problem of retrieval of images by content and present a description logic that has been devised for the semantic indexing and retrieval of images containing ...

Artificial intelligence has the potential to improve the analysis of medical image data. For example, algorithms based on deep learning can determine the location and size of tumors. This is the ...

Results from artificial intelligence image generators can range from appropriate to downright offensive — particularly for cultures that aren’t well represented in the internet’s data. “We wanted to ...

A little over a month after launching its most capable text-to-image model, Ideogram has pushed an update introducing several new capabilities to the AI, including description-based referencing ...

3 Hunan University of Science and Technology, Xiangtan, Hunan, China This study proposes a novel color image encryption algorithm based on a 3D chaotic Hopfield neural network and random row–column ...