IEEE

Neural Networks for High-Resolution Image Processing in Computer Vision

Abstract: Present day innovative technologies like object identification, image division and photo creation are based different values of high-resolution picture processing. In the last few years, ...
IEEE

High Resolution Multi-Mode Electromagnetic Vortex Imaging Driven by the RELAX Algorithm

Abstract: Vortex electromagnetic waves carrying orbital angular momentum (OAM) enable differentiated scaling of multiple targets within the beam coverage, granting them superior theoretical ...
IEEE

DEM Super-Resolution Using Frequency-Selective Cross Attention Assisted by Remote Sensing Images

Abstract: Digital Elevation Model (DEM) plays a crucial role in geospatial analysis. However, high-resolution DEM is often costly to acquire and has limited spatial coverage. This letter proposes a ...
IEEE

Remote Sensing Image Blind Super-Resolution via a Convolutional Neural Network-Guided Conditional Diffusion Model

Abstract: Conventional methods based on bicubic degradation assumption for single remote sensing image super-resolution (SRSISR) have achieved remarkable progress. However, they would possibly fail in ...
IEEE

Deep Learning-Based Super-Resolution Estimation of DOA at Low SNR

Abstract: Aiming at the low signal-to-noise ratio (SNR) environment in which the performance of traditional model-based super-resolution direction-of-arrival (DOA) estimation algorithms will be ...
IEEE

Distillation-Supervised Convolutional Low-Rank Adaptation for Efficient Image Super-Resolution

Abstract: Convolutional neural networks (CNNs) have been widely used in efficient image super-resolution. However, for CNNbased methods, performance gains often require deeper networks and larger ...
IEEE

Wound Image Segmentation Method Based on Fuzzy Clustering Algorithm

Abstract: Accurate acquisition of wound area is crucial for clinical evaluation and monitoring the healing process in wound research. However, traditional methods relying on manual measurement and ...
IEEE

Hyperspectral Image Super-Resolution Based on Adapter-Enhanced Foundation Models

Abstract: Hyperspectral images (HSIs) contain rich spectral information and are highly valuable in applications such as remote sensing monitoring and target identification. However, due to limitations ...
IEEE

GDSR: Global-Detail Integration Through Dual-Branch Network With Wavelet Losses for Remote Sensing Image Super-Resolution

Abstract: In recent years, deep neural networks, including convolutional neural networks (CNNs), Transformers, and State-Space Models, have achieved significant progress in remote sensing image (RSI) ...
IEEE

UAV Image Classification: A Comparative Evaluation of CNN Models

Abstract: Aerial image classification plays a vital role in applications such as building footprint extraction, water/soil analysis, 3D reconstruction. Accurate classification enables timely ...
IEEE

Deepfake Face Image Detection: Benchmarking CNN Models' Performance

Abstract: The Deepfake Face Image Detection System uses Convolutional Neural Networks (CNNs) to address the growing threat of deepfakes, which manipulate images to falsely depict events or actions, ...
IEEE

A CNN network for coronary chronic total occlusion state classification using image data

Abstract: Chronic total occlusion (CTO) is a critical determinant of treatment efficacy in coronary artery disease, but its accurate diagnosis remains heavily reliant on the expertise of experienced ...