Results 111 to 120 of about 14,679 (231)

Optimising Image Feature Extraction and Selection: A Comprehensive Review With Spark Case Studies

Expert Systems, Volume 43, Issue 2, February 2026.
ABSTRACT As benchmark image datasets expand in sample size and feature complexity, the challenge of managing increased dimensionality becomes apparent. Contrary to the expectation that more features equate to enhanced information and improved outcomes, the curse of dimensionality often hampers performance.
J. Guzmán Figueira‐Domínguez, Beatriz Remeseiro, Verónica Bolón‐Canedo   +2 more
wiley   +1 more source

Comparative and Interpretative Analysis of CNN and Transformer Models in Predicting Wildfire Spread Using Remote Sensing Data [PDF]

Facing the escalating threat of global wildfires, numerous computer vision techniques using remote sensing data have been applied in this area. However, the selection of deep learning methods for wildfire prediction remains uncertain due to the lack of ...

core   +1 more source

Detection Method of Concave Defect on Specular Surfaces Based on Swin Transformer [PDF]

Shallow concave defects on mirrored surfaces are difficult to detect automatically. This paper proposes a defect detection method using a deep neural network (DNN) that learns the presence or absence of distortion in the image of a stripe pattern ...
Tanaka, Kazumoto
core   +2 more sources

Federated Multi‐Source Data Fusion for Semi‐Supervised Fault Detection in District Heating Substations

Expert Systems, Volume 43, Issue 2, February 2026.
ABSTRACT Fault detection in district heating (DH) substations is critical for energy efficiency and reliability. However, it is challenged by scarce fault labels, low‐frequency data, privacy concerns, and battery‐constrained gateways. We propose a novel hybrid semi‐supervised federated domain adaptation architecture for fault detection in DH.
Jonne van Dreven, Sadi Alawadi, Abbas Cheddad, Ahmad Nauman Ghazi, Jad Al Koussa, Dirk Vanhoudt   +5 more
wiley   +1 more source

Swin Routiformer: Moss Classification Algorithm Based on Swin Transformer With Bi-Level Routing Attention

IEEE Access
Accurate classification of moss species is essential for progress in ecology and biology. However, traditional methods for classifying moss require significant expertise, and current deep learning techniques struggle due to limited dataset diversity and ...
Peichen Li, Huiqin Wang, Zhan Wang, Ke Wang, Chong Wang   +4 more
doaj   +1 more source

DeepLOC: Deep Learning-based Bone Pathology Localization and Classification in Wrist X-ray Images

, 2023
In recent years, computer-aided diagnosis systems have shown great potential in assisting radiologists with accurate and efficient medical image analysis.
Astashev, Pavel, Dibo, Razan, Dylov, Dmitry V., Galichin, Andrey, Rogov, Oleg Y.   +4 more
core  

Climatological Benchmarking of AI‐Generated Tropical Cyclones

Journal of Geophysical Research: Atmospheres, Volume 131, Issue 2, 28 January 2026.
Abstract This study presents a comprehensive climatological benchmarking of tropical cyclones (TCs) generated by AI‐based global weather prediction models. Using all TC events from the North Atlantic and Western Pacific basins between 2020 and 2025, we assess the ability of two AI models (Pangu‐Weather and Aurora) to reproduce observed TC track density,
Yanmo Weng, Avantika Gori
wiley   +1 more source

Swin Transformer With Spatial and Local Context Augmentation for Enhanced Semantic Segmentation of Remote Sensing Images

IEEE Open Journal of Signal Processing
Semantic segmentation of remote sensing images is extensively used in crop cover and type analysis, and environmental monitoring. In the semantic segmentation of remote sensing images, owning to the specificity of remote sensing images, not only the ...
Rong-Xing Ding, Yi-Han Xu, Gang Yu, Wen Zhou, Ding Zhou   +4 more
doaj   +1 more source

Transformer-based semantic segmentation for large-scale building footprint extraction from very-high resolution satellite images [PDF]

Extracting building footprints from extensive very-high spatial resolution (VHSR) remote sensing data is crucial for diverse applications, including surveying, urban studies, population estimation, identification of informal settlements, and disaster ...
A. Gibril, Mohamed Barakat, Al-Ruzouq, Rami, Bolcek, Jan, Ghorbanzadeh, Omid, Jena, Ratiranjan, Mohd Shafri, Helmi Zulhaidi, Shanableh, Abdallah   +6 more
core   +1 more source

SE‐Swin: An improved Swin‐Transfomer network of self‐ensemble feature extraction framework for image retrieval

IET Image Processing
The Swin‐Transformer is a variant of the Vision Transformer, which constructs a hierarchical Transformer that computes representations with shifted windows and window multi‐head self‐attention.
Yixuan Xu, Xianbing Wang, Hua Zhang, Hai Lin   +3 more
doaj   +1 more source