Robust fall detection in video surveillance based on weakly supervised learning
Fall event detection has been a research hotspot in recent years in the fields of medicine
and health. Currently, vision-based fall detection methods have been considered the most …
and health. Currently, vision-based fall detection methods have been considered the most …
A two-step descriptor-based keypoint filtering algorithm for robust image matching
Finding robust and correct keypoints in images remains a challenge, especially when
repetitive patterns are present. In this article, we propose a universal two-step filtering …
repetitive patterns are present. In this article, we propose a universal two-step filtering …
[HTML][HTML] Horticultural image feature matching algorithm based on improved ORB and LK optical flow
Q Chen, L Yao, L Xu, Y Yang, T Xu, Y Yang, Y Liu - Remote Sensing, 2022 - mdpi.com
To solve the low accuracy of image feature matching in horticultural robot visual navigation,
an innovative and effective image feature matching algorithm was proposed combining the …
an innovative and effective image feature matching algorithm was proposed combining the …
Heterogeneous self-supervised interest point matching for multi-modal remote sensing image registration
M Zhao, G Zhang, M Ding - International Journal of Remote …, 2022 - Taylor & Francis
The implementation of multi-modal remote sensing image registration is still a challenge in
various applications. In this paper, a novel framework called Heterogeneous SuperPoint …
various applications. In this paper, a novel framework called Heterogeneous SuperPoint …
PMA-Net: Progressive multi-stage adaptive feature learning for two-view correspondence
Establishing high-quality correspondences is a fundamental step for many computer vision
tasks. Leveraging the local consistency of correct correspondences (ie, inliers) has been a …
tasks. Leveraging the local consistency of correct correspondences (ie, inliers) has been a …
Fortune favors the invariant: Enhancing GNNs' generalizability with Invariant Graph Learning
Generalizable and transferrable graph representation learning endows graph neural
networks (GNN) with the ability to extrapolate potential test distributions. Nonetheless …
networks (GNN) with the ability to extrapolate potential test distributions. Nonetheless …
Weakly supervised setting for learning concept prerequisite relations using multi-head attention variational graph auto-encoders
An increasing number of learners can benefit from educational resources in Massive Open
Online Courses (MOOCs) through self-regulated learning. However, it is difficult for learners …
Online Courses (MOOCs) through self-regulated learning. However, it is difficult for learners …
Similarity Measurement for Graph Data: An Improved Centrality and Geometric Perspective-Based Approach
L Deng, S Liu, W Xu, X Lin - Big Data Research, 2024 - Elsevier
How to make a precise similarity measurement for graph data is considered as highly
recommended research in many fields. Hereinto, the so-named graph data is the coalition of …
recommended research in many fields. Hereinto, the so-named graph data is the coalition of …
Development of computational vision methodologies for monitoring cuttings in the drilling fluid treatment system
CD Grossi, YN Hummel, EA Moura, CM Scheid… - Brazilian Journal of …, 2023 - Springer
The objective of this work was to apply artificial intelligence techniques, such as
computational vision, image processing, and machine learning, to develop a software for …
computational vision, image processing, and machine learning, to develop a software for …
Weakly supervised object-aware convolutional neural networks for semantic feature matching
We address the task of establishing visual correspondences between two images depicting
main objects of the same semantic category. This task encounters various challenges such …
main objects of the same semantic category. This task encounters various challenges such …