Results 81 to 90 of about 3,740 (194)

Oil Spill Detection in Quad-Polarimetric SAR Images Using an Advanced Convolutional Neural Network Based on SuperPixel Model

Remote Sensing, 2020
Oil spill detection plays an important role in marine environment protection. Quad-polarimetric Synthetic Aperture Radar (SAR) has been proved to have great potential for this task, and different SAR polarimetric features have the advantages to recognize
Jin Zhang, Hao Feng, Qingli Luo, Yu Li, Jujie Wei, Jian Li   +5 more
doaj   +1 more source

Weakly supervised brain tumour segmentation with label propagation and level set loss

IET Image Processing, Volume 19, Issue 1, January/December 2025.
We introduce a new weakly supervised method for 3D brain tumour segmentation using point and scribble supervision. In our weakly supervised method, we generate a new pseudo‐ground‐truth with a marginal area for weakly labelled data (point and scribble) based on region‐growing methods.
Fatemeh‐Sadat Abadian‐Zadeh, Mohammad Reza Mohammadi, Mohsen Soryani   +2 more
wiley   +1 more source

Image Compression Algorithm Based on Region of Interest Extraction for Unmanned Aerial Vehicles Communication

IET Image Processing, Volume 19, Issue 1, January/December 2025.
UAVs are widely used but have limited storage and bandwidth issues, so we propose ROIE‐UC, an image compression algorithm for UAV communication. ROIE‐UC uses SLIC and DBSCAN to segment images into ROI and non‐ROI, applying lossless and high‐ratio lossy compression, respectively, and is decompressed at the receiving end.
Yanxia Liang, Tong Jia, Xin Liu, Huanhuan Zhang   +3 more
wiley   +1 more source

Explainable Dual‐Stream Attention Network for Image Forgery Detection and Localisation Using Contrastive Learning

IET Radar, Sonar &Navigation, Volume 19, Issue 1, January/December 2025.
The model aims to tackle the forgeries observed in manipulated images. A dual‐stream contrastive learning network (DSCL‐Net) that jointly exploits spatial (pixel‐level) and frequency (noise‐level) cues was developed. ABSTRACT Image forgery detection aims to identify tampered content and localise manipulated regions within images.
Maryam Munawar, Mourad Oussalah
wiley   +1 more source

An Effective Classification Scheme for Hyperspectral Image Based on Superpixel and Discontinuity Preserving Relaxation

Remote Sensing, 2019
Hyperspectral image (HSI) classification is one of the most active topics in remote sensing. However, it is still a nontrivial task to classify the hyperspectral data accurately, since HSI always suffers from a large number of noise pixels, the ...
Fuding Xie, Cunkuan Lei, Jun Yang, Cui Jin   +3 more
doaj   +1 more source

Hyperspectral Superpixel-Wise Glioblastoma Tumor Detection in Histological Samples

Applied Sciences, 2020
The combination of hyperspectral imaging (HSI) and digital pathology may yield more accurate diagnosis. In this work, we propose the use of superpixels in HS images for combining regions of pixels that can be classified according to their spectral ...
Samuel Ortega, Himar Fabelo, Martin Halicek, Rafael Camacho, María de la Luz Plaza, Gustavo M. Callicó, Baowei Fei   +6 more
doaj   +1 more source

BiofilmQuant: A Computer-Assisted Tool for Dental Biofilm Quantification

, 2014
Dental biofilm is the deposition of microbial material over a tooth substratum. Several methods have recently been reported in the literature for biofilm quantification; however, at best they provide a barely automated solution requiring significant ...
Mansoor, Awais, Patsekin, Valery, Rajwa, Bartlomiej, Robinson, J. Paul, Scherl, Dale   +4 more
core   +1 more source

Vehicle Object Detection Algorithm Based on Region of Interest–Convolutional Neural Network

IET Software, Volume 2025, Issue 1, 2025.
Traditional vehicle object detection faces problems such as low detection precision, high computational complexity, and poor performance in handling complex backgrounds. To address these challenges, this article adopts the simple linear iterative clustering (SLIC) algorithm for superpixel segmentation, generates candidate regions through selective ...
Zhaosheng Xu, Zhongming Liao, Jianbang Liu, Xiaoyong Xiao, Zhongqi Xiang, Xiuhong Xu, Nadeem Sarwar   +6 more
wiley   +1 more source

AI‐Enhanced PV Power Forecasting Using Cloud Thickness and Motion in Kayseri, Türkiye

The Journal of Engineering, Volume 2025, Issue 1, January/December 2025.
Integration of cloud motion, thickness data, and environmental factors into a deep learning algorithm for PV production forecasting, leading to improved accuracy compared to traditional methods. ABSTRACT The incorporation of renewable energy in photovoltaic (PV) systems has made significant progress.
Levent Yavuz, Ahmet Onen, Ahmed Awad, Razzaqul Ahshan, Abdullah Al‐Badi   +4 more
wiley   +1 more source

A Unified Deep Architecture for Segmentation in Remote Sensing Images

Applied Computational Intelligence and Soft Computing, Volume 2025, Issue 1, 2025.
Deep learning–based segmentation models have gained significant focus in various computer vision applications, including remote sensing and medical imaging. There exist deep learning architectures for semantic and instance segmentation separately, with limitations prevailing such as imprecise boundary delineation, poor spatial consistency, improper ...
Nagamani Gonthina, L. V. Narasimha Prasad, Yiming Tang   +2 more
wiley   +1 more source