IEEE

JOANet: An Integrated Joint Optimization Architecture Making Medical Image Segmentation Really Helped by Super-Resolution Pre-Processing

Abstract: Conventional computer vision pipelines typically treat low-level enhancement and high-level semantic tasks as isolated processes, focusing on optimizing enhancement for perceptual quality ...
IEEE

A Joint Framework for Underwater Image Enhancement and Super-Resolution Reconstruction

Abstract: Underwater images often suffer from complex degradations, such as severe color distortion and low spatial resolution. Existing restoration methods typically focus on a single as-pect-either ...
IEEE

IRBFusion: Diffusion-Based Blind Image Super Resolution Using Unsupervised Learning and Bank of Restoration Networks

Abstract: Image super resolution focuses on increasing the spatial resolution of low-quality images and enhancing their visual quality. Since the image degradation process is unknown in real-life ...
IEEE

HemaX - A CNN-Based Approach for Anemia Detection from Conjunctiva Pallor Images

Abstract: Anaemia is a condition marked by an insufficient number of healthy red blood cells, often initially indicated through visible conjunctival pallor. Conventional diagnostic approaches rely on ...
EurekAlert!

Artificial intelligence for organelle segmentation in live-cell imaging

Recently, Assoc. Prof. Bo Peng (Northwestern Polytechnical University) and Prof. Lin Li (Xiamen University), et ...
IEEE

Bayesian Muography Incorporating Prior Knowledge: A High-Resolution Imaging Algorithm for Structurally Complex Cultural Artifacts

Abstract: Cultural artifacts are vital for heritage preservation but vulnerable to environmental damage that creates internal structural defects not visible on the surface. The drainage dragon heads ...
IEEE

Super-Resolution of Noisy Images Using L-Estimate Compressive Sensing Filter and Cnn Approach

Abstract: This paper proposes an approach for super-resolution of images corrupted by impulse noise by integrating iterative image reconstruction with convolutional neural networks (CNNs). While CNNs ...
IEEE

A Distributed Cloud Storage and Medical Image Encryption Algorithm Application: Medical Image Sharing System

Abstract: This paper proposes a new chaotic system, and experimental analysis shows that its Lyapunov exponent can reach up to 6.85, demonstrating excellent chaotic performance. It is highly suitable ...
IEEE

OmniScaleSR: Unleashing Scale-Controlled Diffusion Prior for Faithful and Realistic Arbitrary-Scale Image Super-Resolution

Abstract: Arbitrary-scale super-resolution (ASSR) overcomes the limitation of traditional super-resolution (SR) that works only at a fixed scale (e.g., ×4), enabling a single model to achieve ...
IEEE

Real vs AI-Generated Image Identification with Enhanced Resolution and Multi-Model Transfer Learning and CNN Approach

Abstract: The fast-paced growth of generative AI has resulted in the appearing of synthetic human face images that are so realistic that it has become hard to distinguish them from the real ones and ...
IEEE

Breaking the Resolution Barrier in Microscopic Imaging: An Optics-Preserving Super-Resolution System Combining Motion Modulation and Deep Learning

Abstract: With the rapid development of micro/nano technology, the requirements for high-resolution images have become increasingly stringent. However, conventional microscopic imaging suffers from ...
IEEE

Research on Super-Resolution Reconstruction Algorithm Based on SwinIR for Brain MRI Images

Abstract: Magnetic resonance imaging (MRI) is crucial in clinical diagnosis. Image super-resolution techniques, which can improve MRI image quality without hardware modifications, are a promising ...