Results 1 to 10 of about 833,049 (266)
The pervasion of 3-D technologies over the years gives rise to the increasing demands of accurate and efficient stereoscopic image quality assessment (SIQA) methods, designed to automatically supervise and optimize 3-D image and video processing systems.
Yong Ding +6 more
doaj +1 more source
No-Reference Quality Assessment for Contrast-Distorted Images
Contrast distortion is a common distortion type in the image applications. However, there are still very limited approaches proposed for quantifying the quality of the contrast-distorted images reliably.
Yutao Liu, Xiu Li
doaj +1 more source
Data Quality-Aware Client Selection in Heterogeneous Federated Learning
Federated Learning (FL) enables decentralized data utilization while maintaining edge user privacy, but it faces challenges due to statistical heterogeneity. Existing approaches address client drift and data heterogeneity issues.
Shinan Song +4 more
semanticscholar +1 more source
Toward accurate single image sand dust removal by utilizing uncertainty-aware neural network
Although deep learning methods have made significant strides in single image sand dust removal, the heterogeneous uncertainty induced by dusty environments poses a considerable challenge.
Bingcai Wei +5 more
doaj +1 more source
A Patch-Level Region-Aware Module with a Multi-Label Framework for Remote Sensing Image Captioning
Recent Transformer-based works can generate high-quality captions for remote sensing images (RSIs). However, these methods generally feed global or grid visual features to a Transformer-based captioning model for associating cross-modal information ...
Yunpeng Li +5 more
doaj +1 more source
RAFnet: SAR Image Autofocusing via Range-Aware Attention and Multi-Scale Loss
Platform motion errors degrade SAR image quality in terms of severe defocusing and azimuth blurring. We propose a Range-aware Autofocus Network (RAFnet) by embedding a novel range-aware attention module into a progressive autofocus framework.
Hua Wu +4 more
doaj +1 more source
OASL: Orientation-aware adaptive sampling learning for arbitrary oriented object detection
Arbitrary oriented object detection (AOOD) is a fundamental task in aeiral image interpretation, which is commonly implemented by optimizing three subtasks: classification, localization, and orientation.
Zifei Zhao, Shengyang Li
doaj +1 more source
Quality estimation of the predicted interaction interface of protein complex structural models is not only important for complex model evaluation and selection but also useful for protein-protein docking.
Md Hossain Shuvo, Debswapna Bhattacharya
doaj +1 more source
Spatial Orthogonal and Boundary-Aware Network for Rotated and Elongated-Target Detection
In recent years, the refinement of bounding box representations has emerged as a major research focus in remote sensing. Nevertheless, mainstream detection algorithms typically ignore the disruptive impacts induced by the diverse morphologies and ...
Yong Liu +3 more
doaj +1 more source
Quality Aware Feature Selection for Video Object Tracking
Roger Gomez Nieto +2 more
openaire +1 more source

