Results 71 to 80 of about 1,040 (193)

Comparative Evaluation of Deep Learning–Based Super–Resolution Models for Urban Flood Mapping

Journal of Flood Risk Management, Volume 18, Issue 4, December 2025.
ABSTRACT Urban flood forecasting benefits from high‐resolution inundation maps, but fine‐grid hydrodynamic simulations are computationally costly. We compared three CNN–based super–resolution (SR) models, ResUNet, EDSR, and RCAN, for downscaling physics–based simulations in downtown Portland, Oregon, using paired flood maps at 1 m (HR) and both 4 and 8 
Hyeonjin Choi, Hyuna Woo, Hyungon Ryu, Dong Sop Rhee, Seong Jin Noh   +4 more
wiley   +1 more source

Second‐Order Degradation Modeling and Multiscale Feature Fusion for High‐Fidelity Segmentation of Low‐Quality Digital Rock Images

Geophysical Research Letters, Volume 52, Issue 19, 16 October 2025.
Abstract Digital Rock Physics (DRP) is a critical tool for characterizing rock properties and modeling multiphase flow, but segmenting low‐quality (LQ) rock images remains a key challenge due to partial volume blurring. In this study, we propose a method that leverages a second‐order degradation model to generate physically meaningful synthetic LQ and ...
Lulu Xu, Zhenxue Dai, Yi Du, Xiaoying Zhang, Huichao Yin, Mohamad Reza Soltanian, Hung Vo Thanh, Meifeng Cai, Kenneth C. Carroll   +8 more
wiley   +1 more source

A data augmentation method for pavement crack detection based on super‐resolution and denoising diffusion probabilistic models

Computer-Aided Civil and Infrastructure Engineering, Volume 40, Issue 25, Page 4212-4225, 20 October 2025.
Abstract Automated detection of pavement cracks is a task of wide interest. With the improvement of industrialization, high‐resolution (HR) images are increasingly favored by researchers due to their ability to provide rich information about pavements and diseases.
Hui Yao, Yanhao Liu, Svetlana Besklubova, Ioannis Brilakis, Meng Guo, Jin Wang, Min Wang   +6 more
wiley   +1 more source

Enhancing The Accuracy of Small Object Detection In Traffic Safety Attributes Using Yolov11 And Esrgan: Peningkatan Akurasi Deteksi Objek Kecil pada Atribut Keselamatan Berkendara Menggunakan Yolov11 dan ESRGAN

This study aims to detect motorcycle rider attributes, specifically helmets and side mirrors, using a deep learning approach combining YOLOv11 and ESRGAN models.
Pinem, Tuahta Hasiholan, Haris, Muhammad
core   +1 more source

Implementación del Modelo Real-ESRGAN para Imágenes Satelitales [PDF]

Aquest estudi es centra en implementar un sistema de super-resolució ràpid, eficient i fàcil d'utilitzar, específicament dissenyat per a imatges satel·litals. Mitjançant l'ús del model Real-ESRGAN, el nostre objectiu és optimitzar l'arquitectura, ajustar
Chirinos Sullcany, Jhoe Gabriel, Universitat Autònoma de Barcelona. Escola d'Enginyeria   +1 more
core   +1 more source

Advanced Image Preprocessing and Integrated Modeling for UAV Plant Image Classification

Drones
The automatic identification of plant species using unmanned aerial vehicles (UAVs) is a valuable tool for ecological research. However, challenges such as reduced spatial resolution due to high-altitude operations, image degradation from camera optics ...
Girma Tariku, Isabella Ghiglieno, Anna Simonetto, Fulvio Gentilin, Stefano Armiraglio, Gianni Gilioli, Ivan Serina   +6 more
doaj   +1 more source

Design of Generative Adversarial Network Super‐Resolution Reconstruction Algorithm for Intelligent Security Images

Engineering Reports
In the reconstruction of security images, the current generative adversarial network super‐resolution reconstruction algorithm is prone to generate unrealistic artifacts under high noise and low contrast, and the details of small targets are blurred ...
Yuyao Liu, Qiongyin Peng
doaj   +1 more source

Improving Face Image Transmission with LoRa Using a Generative Adversarial Network

Applied Sciences
Although it is a technology that can be pretty important for remote areas lacking internet or cellular data, the difficulties it presents in large data transmission prevent LoRa from developing sufficiently for image transmission.
Bilal Babayiğit, Fatma Yarlı Doğan
doaj   +1 more source

Evaluating the Impact of Super-Resolution for Coastal Boundary Segmentation Using Deep Learning for High-Resolution Imagery [PDF]

ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
Coastal areas play an important role economically, socially and environmentally due to their many functions. However, these regions are at risk of erosion, which is further exacerbated by human-driven climate change.
M.-A. Blais, M. A. Akhloufi
doaj   +1 more source

Self Attention GAN and SWIN Transformer-Based Pothole Detection With Trust Region-Based LSM and Hough Line Transform for 2D to 3D Conversion

IEEE Access
Vehicles and roads play a crucial role in connecting peoples across the world for their every day needs, activities and life style. This has enormously increased the need for maintaining the road surface with better quality and maintenance to prevent ...
R. Kothai, N. Prabakaran
doaj   +1 more source