Results 61 to 70 of about 3,600 (211)
Litter on the streets - solid waste detection using VHR images
European Journal of Remote Sensing, 2023 Failures in urban areas’ solid waste management lead to clandestine garbage dumping and pollution. This affects sanitation and public human hygiene, deteriorates quality of life, and contributes to deprivation.
Yrneh Zarit Ulloa-Torrealba +3 more
doaj +1 more source
Exploiting Superpixels for Multi-Focus Image Fusion
, 2021 Multi-focus image fusion is the process of combining focused regions of two or more images to obtain a single all-in-focus image. It is an important research area because a fused image is of high quality and contains more details than the source images ...
Marcin Grzegorzek +3 more
core +1 more source
Remote Sensing in Ecology and Conservation, EarlyView.High‐resolution visible‐light imagery from low‐altitude unmanned aerial vehicles, combined with superpixel segmentation and a Random Forest classifier, provides an efficient and scalable framework for mapping and monitoring crustose coralline algae and reef habitats.
Po‐Chien Lin +2 more
wiley +1 more source
An Improved Image Semantic Segmentation Method Based on Superpixels and Conditional Random Fields
Applied Sciences, 2018 This paper proposed an improved image semantic segmentation method based on superpixels and conditional random fields (CRFs). The proposed method can take full advantage of the superpixel edge information and the constraint relationship among different ...
Wei Zhao, Yi Fu, Xiaosong Wei, Hai Wang
doaj +1 more source
Relevance maps: A weakly supervised segmentation method for 3D brain tumours in MRIs
Frontiers in Radiology, 2022 With the increased reliance on medical imaging, Deep convolutional neural networks (CNNs) have become an essential tool in the medical imaging-based computer-aided diagnostic pipelines.
Sajith Rajapaksa +8 more
doaj +1 more source
A deep learning‐enabled toolkit for the 3D segmentation of ventricular cardiomyocytes
The Journal of Physiology, EarlyView.Abstract figure legend 3D cardiomyocyte segmentation enables comprehensive analyses of myocardial microstructure in health and disease; however, it is technically demanding. We present an open‐source toolkit for this task, which reduces challenges associated with sample preparation, image restoration, segmentation and proofreading.
Joachim Greiner +6 more
wiley +1 more source
Advancing Photonic Inverse Design with Interpretable Machine Learning
Advanced Photonics Research, Volume 7, Issue 5, May 2026.The work applies the interpretable machine learning technique called LIME (local interpretable model‐agnostic explanations) to the inverse design of photonic chips, revealing hidden optimization patterns and guiding better starting designs. Using insights from LIME improves performance of two‐mode multiplexers, showing interpretable methods can ...
Lirandë Pira +5 more
wiley +1 more source
Brain and Behavior, Volume 16, Issue 5, May 2026.Tablet‐based handwriting tasks (spiral, meander, and wave) are transformed into unified images and analyzed using PD‐MGMA‐DSCNN, a lightweight multiscale gated attention network. Bayesian–genetic optimization improves performance, while SHAP attribution maps provide interpretable handwriting biomarkers for Parkinson's disease screening.
Khosro Rezaee, Ali Khalili Fakhrabadi
wiley +1 more source
Superpixel and Supervoxel Segmentation Assessment of Landslides Using UAV-Derived Models
Remote Sensing, 2022 Reality capture technologies such as Structure-from-Motion (SfM) photogrammetry have become a state-of-the-art practice within landslide research workflows in recent years.
Ioannis Farmakis +4 more
doaj +1 more source
SEEDS: Superpixels Extracted Via Energy-Driven Sampling [PDF]
, 2021 Superpixel algorithms aim to over-segment the image by grouping pixels that belong to the same object. Many state-of-the-art superpixel algorithms rely on minimizing objective functions to enforce color homogeneity.
Van den Bergh, Michael +3 more
core