Results 81 to 90 of about 1,040 (193)

SU-ESRGAN: Semantic and Uncertainty-Aware ESRGAN for Super-Resolution of Satellite and Drone Imagery with Fine-Tuning for Cross Domain Evaluation

2025 International Conference on Modeling, Simulation & Intelligent Computing (MoSICom)
Generative Adversarial Networks (GANs) have achieved realistic super-resolution (SR) of images however, they lack semantic consistency and per-pixel confidence, limiting their credibility in critical remote sensing applications such as disaster response, urban planning and agriculture.
openaire   +3 more sources

Implementation of Real-ESRGAN for image resolution enhancement in a YOLOv8-based vehicle license plate identification system under low-light conditions

Vehicle license plate identification systems still face significant challenges under low-light conditions, including low image resolution, high noise levels, and decreased detection accuracy. Conventional methods such as contrast enhancement or filtering
Mustazzihim Suhaidi, Tri Handayani
core   +1 more source

Autonomous vehicle number plate recognition using a YOLO and Esrgan framework

A vehicle number plate recognition framework supports law enforcement for recognizing and tracking vehicles that are lost or used for criminal activities.
Kasaraneni, Dherraj
core   +1 more source

GA-GESRGAN: Document Images Super Resolution using Gabor Filters, ESRGAN Models and Genetic Algorithms [PDF]

In the last decade, we have witnessed significant progress in image super-resolution, thanks in particular to the emergence and improvement of deep learning models, which can adapt to the complexity of tasks and improve image quality.
KEZZOULA, Zakia, GACEB, Djamel, TITOUN, Ayoub   +2 more
core  

Enhancing Image Quality by Optimizing and Fine-Tuning Multi-Fidelity Generative Adversarial Networks

IEEE Access
Achieving a balance between image quality and computational efficiency is one of the most challenging tasks in image enhancement. Conventional single-fidelity methods focus on structural integrity; yet, they are ineffective in improving perceptual ...
Noor Baha Aldin
doaj   +1 more source

From PSNR to Frequency Evidence: Evaluating Super-Resolution Reliability on Low-SNR Fluorescence Channels

Photonics
Existing super-resolution evaluation systems for fluorescence microscopy images struggle to effectively detect potential artifacts in weak signal reconstruction.
Haoxuan Huang, Hasan Abbas
doaj   +1 more source

Perbaikan Citra Medis Low-Resolution Menggunakan REAL-ESRGAN

Citra medis memegang peranan vital dalam diagnosis klinis dan penanganan pasien, namun kualitasnya sering kali terdegradasi akibat keterbatasan perangkat, noise, dan resolusi rendah yang menghambat kemudahan dokter dalam menganalisis citra.
Hidayanto, Atha Dzaky
core  

A new generation of artificial intelligence contributing to improving the image quality [PDF]

High-resolution (HR) images provide inclusive and critical information, which is substantial for many implementations. Production operation for high-quality images from low-quality images can be costly and time consuming.
Mohammed, Suad Khairi, Abdullah, Hadeel N., Alagha, Salwa A.   +2 more
core   +1 more source

Sentinel-2 Super-Resolution with Real-ESRGAN using Satellite and Aerial Image Pairs and Color Correction Techniques

Improving the spatial resolution of satellite images offers considerable potential for a wide range of remote sensing applications. This study investigates the use of an Enhanced Super-Resolution Generative Adversarial Network (Real-ESRGAN) to improve ...
Kleebauer, Maximilian, Marz, Christopher, Horst, Daniel   +2 more
core   +1 more source

Application of Computer Vision for Automated Processing of Medical Documents

Цифровая трансформация
This paper examines the automation of medical image processing for diagnosing arterial hypertension using artificial intelligence and computer vision technologies.
Y. A. Kurliuk, N. A. Larchenko, M. V. Davydov, E. K. Kurlyanskaya   +3 more
doaj   +1 more source