Results 71 to 80 of about 9,139 (221)

Quantitative Metrics for Edge Bundling of Network Visualizations

Computer Graphics Forum, EarlyView.
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, J. Miller, A. Maftei, S. G. Kobourov   +3 more
wiley   +1 more source

Model‐Agnostic Influential Outlier Metric

Stat, Volume 15, Issue 3, September 2026.
ABSTRACT The influential outlier metric (IOM) provides model‐agnostic influential outlier detection. We define influence of an observation using a combination of SHapley Additive exPlanation (SHAP) values and the residual. Both are transformed using normalizing flows, changing their respective measures to Gaussian distributions.
Colin C. Jones, David A. Campbell
wiley   +1 more source

Explainable Deep Learning for Imaging‐Based Skin Lesion Diagnosis: A Systematic Literature Review

Concurrency and Computation: Practice and Experience, Volume 38, Issue 16, August 2026.
ABSTRACT In the latest years, the use of Deep Learning (DL) in imaging‐based skin lesion diagnosis has become increasingly prevalent. The deep models have revolutionized the computer‐aided diagnosis systems in terms of performance. However, DL models are often criticized as black boxes due to their complex and opaque internal design of numerous ...
Rym Dakhli, Walid Barhoumi
wiley   +1 more source

Retinal Vessel Segmentation: A Comprehensive Review From Classical Methods to Deep Learning Advances (1982–2025)

Advanced Intelligent Systems, Volume 8, Issue 7, July 2026.
Four decades of retinal vessel segmentation research (1982–2025) are synthesized, spanning classical image processing, machine learning, and deep learning paradigms. A meta‐analysis of 428 studies establishes a unified taxonomy and highlights performance trends, generalization capabilities, and clinical relevance.
Avinash Bansal, Jan Kubíček, Jana Bahrová, Alice Varyšová, Martin Augustýnek, Marek Penhaker, Juraj Timkovič   +6 more
wiley   +1 more source

Hyperspectral Band Selection for Lithologic Discrimination and Geological Mapping

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2020
Classification techniques applied to hyperspectral images are very useful for lithologic discrimination and geological mapping. Classifiers are often applied either to all spectral channels or only to absorption spectral channels.
Yulei Tan, Laijun Lu, Lorenzo Bruzzone, Renchu Guan, Zhiyong Chang, Chen Yang   +5 more
doaj   +1 more source

Video‐Based Rainfall Opportunistic Sensing in Hydrology: A Lightweight Machine Learning Approach

Water Resources Research, Volume 62, Issue 7, July 2026.
Abstract Video‐based rainfall measurement is a frontier topic in opportunistic sensing; however, rapid, accurate, and robust identification of rainfall‐related rain‐streak features from dynamic videos remains a key challenge, especially for monitoring devices with limited computational resources.
Yongcheng Jin, Zhe Zhu, Xinwei Xue, Guangtao Fu, Chi Zhang, Yu Li   +5 more
wiley   +1 more source

A deep learning‐enabled toolkit for the 3D segmentation of ventricular cardiomyocytes

The Journal of Physiology, Volume 604, Issue 13, Page 5561-5584, 1 July 2026.
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, Fabio Frangiamore, Frédéric Sonak, Josef Madl, Thomas Seidel, Peter Kohl, Eva A. Rog‐Zielinska   +6 more
wiley   +1 more source

A Novel Object-Based Deep Learning Framework for Semantic Segmentation of Very High-Resolution Remote Sensing Data: Comparison with Convolutional and Fully Convolutional Networks

Remote Sensing, 2019
Deep learning architectures have received much attention in recent years demonstrating state-of-the-art performance in several segmentation, classification and other computer vision tasks.
Maria Papadomanolaki, Maria Vakalopoulou, Konstantinos Karantzalos   +2 more
doaj   +1 more source

Multifiber Array‐Based Photometry System for Multiregional Functional Mapping in the Mouse Brain

European Journal of Neuroscience, Volume 63, Issue 12, June 2026.
Existing fiber photometry approaches suffer from invasiveness and limited scalability. A newly developed multifiber array‐based photometry system allows targeting multiple brain regions with less invasiveness. The system was validated in two jGCaMP8s‐expressing mouse lines by monitoring GABAergic neural population activity across multiple brain regions
Manil Bradai, Mirna Merkler, Gabriela Gil, Rebecca Davie, Shuzo Sakata   +4 more
wiley   +1 more source

The Outlining of Agricultural Plots Based on Spatiotemporal Consensus Segmentation

Remote Sensing, 2018
The outlining of agricultural land is an important task for obtaining primary information used to create agricultural policies, estimate subsidies and agricultural insurance, and update agricultural geographical databases, among others.
Angel Garcia-Pedrero, Consuelo Gonzalo-Martín, Mario Lillo-Saavedra, Dionisio Rodríguez-Esparragón   +3 more
doaj   +1 more source