Results 91 to 100 of about 16,201 (241)
Interpretable Machine Learning: A Comprehensive Review of Foundations, Methods, and the Path Forward
WIREs Data Mining and Knowledge Discovery, Volume 16, Issue 1, March 2026.This systematic review of 352 studies establishes a comprehensive taxonomy for Interpretable Machine Learning, transitioning from foundational intrinsic models to advanced deep learning explanations. It reveals a critical paradigm shift toward “mechanistic interpretability” and actionable recourse, emphasizing that future AI systems must be rigorously ...
Shimon Fridkin, Michael Bendersky
wiley +1 more source
A GEOBIA Methodology for Fragmented Agricultural Landscapes
Remote Sensing, 2015 Very high resolution remotely sensed images are an important tool for monitoring fragmented agricultural landscapes, which allows farmers and policy makers to make better decisions regarding management practices.
Angel Garcia-Pedrero +3 more
doaj +1 more source
Superpixel Sampling Networks [PDF]
, 2018 Superpixels provide an efficient low/mid-level representation of image data, which greatly reduces the number of image primitives for subsequent vision tasks. Existing superpixel algorithms are not differentiable, making them difficult to integrate into otherwise end-to-end trainable deep neural networks.
Jampani, Varun +4 more
openaire +2 more sources
Journal of Geophysical Research: Solid Earth, Volume 131, Issue 3, March 2026.Abstract As spherical shell mantle convection models become increasingly commonplace, understanding how plates are generated has raised the issue of how to recognize whether rigid plates are present in model output. Tectonocists have long recognized that intraplate regions are not rigid without exception.
P. Javaheri, J. P. Lowman
wiley +1 more source
Superpixel Segmentation Using Gaussian Mixture Model [PDF]
IEEE Transactions on Image Processing, 2018 Superpixel segmentation algorithms are to partition an image into perceptually coherence atomic regions by assigning every pixel a superpixel label. Those algorithms have been wildly used as a preprocessing step in computer vision works, as they can enormously reduce the number of entries of subsequent algorithms.
Zhihua Ban, Jianguo Liu, Li Cao
openaire +4 more sources
Geo: Geography and Environment, Volume 13, Issue 1, January‐June 2026.Short Abstract This study evaluates the effectiveness of UAV multispectral imagery combined with machine learning techniques for mapping neglected and underutilised crop species (NUS), specifically taro and sweet potato in smallholder farming systems in South Africa.
Mishkah Abrahams +7 more
wiley +1 more source
Superpixel-based Two-view Deterministic Fitting for Multiple-structure Data
, 2016 This paper proposes a two-view deterministic geometric model fitting method, termed Superpixel-based Deterministic Fitting (SDF), for multiple-structure data.
AS Brahmachari +12 more
core +1 more source
Robust Active Contour Model for Image Segmentation Using a Probability Density Function Approach
IET Image Processing, Volume 20, Issue 1, January/December 2026.This paper proposes an active contour model‐based image segmentation algorithm using the probability density function. Initially, the probability density function is defined by the local mean and variance. Next, a length penalty term and a distance regularization term are incorporated.
XinChao Meng, Si Si, Pei Zhang
wiley +1 more source
IEEE Access, 2020 Brain tumor segmentation from Magnetic Resonance Imaging (MRI) is of great importance for better tumor diagnosis, growth rate prediction and radiotherapy planning. But this task is extremely challenging due to intrinsically heterogeneous tumor appearance,
Tamjid Imtiaz +3 more
doaj +1 more source
Curriculum Domain Adaptation for Semantic Segmentation of Urban Scenes
, 2017 During the last half decade, convolutional neural networks (CNNs) have triumphed over semantic segmentation, which is one of the core tasks in many applications such as autonomous driving.
David, Philip, Gong, Boqing, Zhang, Yang
core +1 more source