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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
Unsupervised instance segmentation with superpixels
Pattern RecognitionInstance segmentation is essential for numerous computer vision applications, including robotics, human-computer interaction, and autonomous driving. Currently, popular models bring impressive performance in instance segmentation by training with a large number of human annotations, which are costly to collect.
openaire +3 more sources
Efficient Superpixel-Guided Interactive Image Segmentation Based on Graph Theory
, 2018 Image segmentation is a challenging task in the field of image processing and computer vision. In order to obtain an accurate segmentation performance, user interaction is always used in practical image-segmentation applications.
Guanglei Gou +4 more
core +1 more source
Corrosion defect segmentation method based on superpixel feature cascade
Ain Shams Engineering JournalTo solve the segmentation problem caused by the small number of feature points and the change of image brightness on the surface of the storage tank, a corrosion defect segmentation method based on the superpixel feature cascade is proposed in this paper.
Lingyu Sun +3 more
doaj +1 more source
Automatic glioma segmentation based on adaptive superpixel
BMC Medical Imaging, 2019 Background The automatic glioma segmentation is of great significance for clinical practice. This study aims to propose an automatic method based on superpixel for glioma segmentation from the T2 weighted Magnetic Resonance Imaging.
Yaping Wu +4 more
doaj +1 more source
Superpixel-based Hyperspectral Unmixing with Regional Segmentation [PDF]
, 2018 Unsupervised unmixing analysis aims to extract the basic materials, also known as, endmembers, and their fractions (or abundances) from a hyperspectral image. In this work, a new unsupervised unmixing approach based on Low Dimensional representation with
Alkhatib, Mohammed Qassim
core +2 more sources
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
Superpixel-based class-semantic texton occurrences for natural roadside vegetation segmentation
, 2017 Vegetation segmentation from roadside data is a field that has received relatively little attention in present studies, but can be of great potentials in a wide range of real-world applications, such as road safety assessment and vegetation condition ...
Ligang Zhang +5 more
core +1 more source
Adaptive Superpixel Segmentation-Based Coastline Extraction Method for PolSAR Images
IEEE Journal of Selected Topics in Applied Earth Observations and Remote SensingTo improve the accuracy of coastline extraction for polarimetric synthetic aperture radar (PolSAR) images, an adaptive superpixel segmentation-based method is proposed.
Yu Wang +5 more
doaj +1 more source
Text segmentation using superpixel clustering
IET Image Processing, 2017 Text segmentation is important for text image analysis and recognition; however, it is challenging due to noise and complex background in natural scenes. Superpixel‐based image representation can enhance robustness to noise and local disturbances, but conventional superpixel algorithms are difficult to obtain the complete stroke regions and accurate ...
Yuanping Zhu, Kuang Zhang
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