Results 61 to 70 of about 118,760 (177)

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

Using Deep Learning in Infrared Images to Enable Human Gesture Recognition for Autonomous Vehicles

IEEE Access, 2020
The realization of a novel human gesture recognition algorithm is essential to enable the effective collision avoidance of autonomous vehicles. Compared to visible spectrum cameras, the use of infrared imaging can enable more robust human gesture ...
Keke Geng, Guodong Yin
doaj   +1 more source

Relieve the Demand for Labeled Data of Deep Learning Models for Hydraulic Conductivity Field Tasks in Groundwater Through Self‐Supervised Learning

Journal of Geophysical Research: Machine Learning and Computation, Volume 2, Issue 4, December 2025.
Abstract Deep learning (DL) has shown great potential in solving groundwater problems but often requires large labeled data sets, which are expensive and time‐consuming to obtain. In this study, we introduce a self‐supervised learning approach based on a masked autoencoder (MAE)—an encoder‐decoder architecture that reconstructs randomly masked input ...
Kai Ji, Zhengkun Zhou, Bo Zou, Ruiting Yang, Baoqing Zhang   +4 more
wiley   +1 more source

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

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

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

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   +4 more sources

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 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

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