Results 31 to 40 of about 384,232 (160)
Semantic segmentation of high-resolution remote sensing images is crucial in ecological evaluation, natural resource surveys, etc. Compared with CNN-based and transformer-based methods, graph neural networks (GNNs) have drawn increasing attention because
Ying Tang, Xiangyun Hu, Tao Ke, Mi Zhang
doaj +1 more source
Artificial Intelligence in Dermatology: Current Applications and Future Directions
This scoping review of 56 studies maps AI applications in dermatology. Image‐based classification for skin cancer detection dominates (48%), followed by clinical decision support (21%), teledermatology triage (11%), and predictive analytics (11%). While deep learning algorithms demonstrate diagnostic performance comparable to clinicians in controlled ...
Sofía Pérez‐Lalinde +1 more
wiley +1 more source
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
Superpixel image segmentation.
(a) original image. (b) result of superpixel segmentation.
Guan Yang (520726) +4 more
core +1 more source
A Hybrid Model Based on Superpixel Entropy Discrimination for PolSAR Image Classification
Superpixel segmentation is widely used in polarimetric synthetic aperture radar (PolSAR) image classification. However, the classification method using simple majority voting cannot easily handle evidence conflicts in a single superpixel.
Jili Sun, Lingdong Geng, Yize Wang
doaj +1 more source
Quantitative Metrics for Edge Bundling of Network Visualizations
Abstract Edge bundling is widely used for reducing visual clutter in large 2D network and trajectory visualizations. Various edge bundling methods have been proposed, each producing qualitatively distinct outputs for the same data; however, few quantitative metrics exist for systematic evaluation. In this paper, we propose a set of quantitative metrics
M. Wallinger +3 more
wiley +1 more source
Learning Superpixel Relations for Supervised Image Segmentation
In this paper we propose to extend the well known graph cut segmentation framework by learning superpixel relations and use them to weight superpixel-to-superpixel edges in a superpixel graph.
Costantino Grana +5 more
core +1 more source
Interactive segmentation: a scalable superpixel-based method [PDF]
This paper addresses the problem of interactive multiclass segmentation of images. We propose a fast and efficient new interactive segmentation method called superpixel alpha fusion (SaF).
Mathieu, Bérengère +5 more
core +1 more source
Improved Spatial-Spectral Superpixel Hyperspectral Unmixing
In this paper, an unsupervised unmixing approach based on superpixel representation combined with regional partitioning is presented. A reduced-size image representation is obtained using superpixel segmentation where each superpixel is represented by ...
Mohammed Q. Alkhatib +1 more
doaj +1 more source
Time course sensor‐based phenotyping can predict Ascochyta blight disease severity in Cicer species
Abstract Ascochyta blight is a widely occurring chickpea fungal disease that can cause severe yield loss. Breeding for crop resistance benefits from high‐throughput evaluation of plant–pathogen interactions in genotypes which can serve as sources of resistance.
Florian Tanner +9 more
wiley +1 more source

