Results 51 to 60 of about 417 (152)

Selective Multiple Classifiers for Weakly Supervised Semantic Segmentation

CAAI Transactions on Intelligence Technology, Volume 10, Issue 6, Page 1688-1702, December 2025.
ABSTRACT Existing weakly supervised semantic segmentation (WSSS) methods based on image‐level labels always rely on class activation maps (CAMs), which measure the relationships between features and classifiers. However, CAMs only focus on the most discriminative regions of images, resulting in their poor coverage performance.
Zilin Guo, Dongyue Wu, Changxin Gao, Nong Sang   +3 more
wiley   +1 more source

Multi-scale guided filtering integrated with superpixel and patch shift

Tongxin xuebao, 2022
In order to avoid the phenomenon that edges were easily blurred during filtering, a multi-scale guided filtering integrated with superpixel and patch shift was proposed.Firstly, the bilateral filtering was applied to an input image to get more accurate ...
Jianwu LONG, Jiangzhou ZHU
doaj   +2 more sources

Region-Based Relaxed Multiple Kernel Collaborative Representation for Hyperspectral Image Classification

IEEE Access, 2017
This paper presents a region-based relaxed multiple kernel collaborative representation method for the spatial-spectral classification of hyperspectral images. The proposed method consists of three steps.
Jianjun Liu, Zebin Wu, Zhiyong Xiao, Jinlong Yang   +3 more
doaj   +1 more source

Applied Artificial Intelligence in Materials Science and Material Design

Advanced Intelligent Systems, Volume 7, Issue 8, August 2025.
AI‐driven methods are transforming materials science by accelerating material discovery, design, and analysis, leveraging large datasets to enhance predictive modeling and streamline experimental techniques. This review highlights advancements in AI applications across spectroscopy, microscopy, and molecular design, enabling efficient material ...
Emigdio Chávez‐Angel, Martin Børstad Eriksen, Alejandro Castro‐Alvarez, Jose H. Garcia, Marc Botifoll, Oscar Avalos‐Ovando, Jordi Arbiol, Aitor Mugarza   +7 more
wiley   +1 more source

Multiscale Superpixels and Supervoxels Based on Hierarchical Edge-Weighted Centroidal Voronoi Tessellation

2015 IEEE Winter Conference on Applications of Computer Vision, 2015
Superpixels and supervoxels play an important role in many computer vision applications, such as image segmentation, object recognition, and video analysis. In this paper, we propose a new hierarchical edge-weighted centroidal Voronoi tessellation (HEWCVT) method for generating superpixels/supervoxels in multiple scales.
Youjie Zhou, Lili Ju, Song Wang 0002
openaire   +2 more sources

Detecting Changes in Space‐Varying Parameters of Local Poisson Point Processes

Environmetrics, Volume 36, Issue 5, July 2025.
ABSTRACT Recent advances in local models for point processes have highlighted the need for flexible methodologies to account for the spatial heterogeneity of external covariates influencing process intensity. In this work, we introduce tessellated spatial regression, a novel framework that extends segmented regression models to spatial point processes,
Nicoletta D'Angelo
wiley   +1 more source

Hybrid CNN-GCN Network for Hyperspectral Image Classification

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
In recent years, convolutional neural networks (CNNs) have been impressive due to their excellent feature representation abilities, but it is difficult to learn long-distance spatial structures information. Unlike CNN, graph convolutional networks (GCNs)
Cuiping Shi, Diling Liao, Liguo Wang
doaj   +1 more source

Deep‐Learning‐Enhanced Electron Microscopy for Earth Material Characterization

Journal of Geophysical Research: Machine Learning and Computation, Volume 2, Issue 2, June 2025.
Abstract Rocks, as Earth materials, contain intricate microstructures that reveal their geological history. These microstructures include grain boundaries, preferred orientation, twinning and porosity, holding critical significance in the realm of the energy transition.
Hans van Melick, Richard Taylor, Oliver Plümper   +2 more
wiley   +1 more source

Multiscale Feature Search-Based Graph Convolutional Network for Hyperspectral Image Classification

Remote Sensing
With the development of hyperspectral sensors, the availability of hyperspectral images (HSIs) has increased significantly, prompting advancements in deep learning-based hyperspectral image classification (HSIC) methods.
Ke Wu, Yanting Zhan, Ying An, Suyi Li
doaj   +1 more source

Cutting‐Edge Deep Learning Methods for Image‐Based Object Detection in Autonomous Driving: In‐Depth Survey

Expert Systems, Volume 42, Issue 4, April 2025.
ABSTRACT Object detection is a critical aspect of computer vision (CV) applications, especially within autonomous driving systems (AVs), where it is fundamental to ensuring safety and reducing traffic accidents. Recent advancements in computational resources have enabled the widespread adoption of Deep Learning (DL) techniques, significantly enhancing ...
Narges Saeedizadeh, Seyed Mohammad Jafar Jalali, Burhan Khan, Shady Mohamed   +3 more
wiley   +1 more source