Photo-induced force microscopy began as a concept in the mind of Kumar Wickramasinghe when he was employed by IBM in the ...

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

Arabian Post -digiKam’s 8.7.0 update foregrounds artificial intelligence enhancements, integrating tools that tackle everyday pain points in photo management. Key features include bolstered facial ...

Advances in image processing and machine learning (ML) substantially affected unmixing. This article provides an overview of advanced and conventional unmixing approaches. In addition, we draw a ...

Researchers have uncovered how primate brains transform flat, 2D visual inputs into rich, 3D mental representations of ...

By learning the relevant features of clinical images along with the relationships between them, the neural network can outperform more traditional methods.

Image registration is the process of transforming different sets of data into one coordinate system. Data may be multiple photographs, and from different sensors, times, depths, or viewpoints. It is ...

Low-rank matrix approximation (LRMA)-based methods have made a great success for grayscale image processing. When handling color images, LRMA either restores each color channel independently using the ...

keywords: Vision Transformer, Swin Transformer, convolutional neural networks, image registration This is a PyTorch implementation of my paper: Chen, Junyu, et al. "TransMorph: Transformer for ...