Zobrazeno 1 - 10
of 1 686
pro vyhledávání: '"Vasilakos, Athanasios"'
Autor:
Li, Jialiang, Wang, Haoyue, Li, Sheng, Qian, Zhenxing, Zhang, Xinpeng, Vasilakos, Athanasios V.
Recently, a vast number of image generation models have been proposed, which raises concerns regarding the misuse of these artificial intelligence (AI) techniques for generating fake images. To attribute the AI-generated images, existing schemes usua
Externí odkaz:
http://arxiv.org/abs/2407.14570
In this paper, we address the challenging source-free unsupervised domain adaptation (SFUDA) for pinhole-to-panoramic semantic segmentation, given only a pinhole image pre-trained model (i.e., source) and unlabeled panoramic images (i.e., target). Ta
Externí odkaz:
http://arxiv.org/abs/2404.16501
Unsupervised visible-infrared person re-identification (UVI-ReID) has recently gained great attention due to its potential for enhancing human detection in diverse environments without labeling. Previous methods utilize intra-modality clustering and
Externí odkaz:
http://arxiv.org/abs/2404.06683
Autor:
Jiang, Tianqi, Luo, Haoxiang, Yang, Kun, Sun, Gang, Yu, Hongfang, Huang, Qi, Vasilakos, Athanasios V.
The energy market encompasses the behavior of energy supply and trading within a platform system. By utilizing centralized or distributed trading, energy can be effectively managed and distributed across different regions, thereby achieving market eq
Externí odkaz:
http://arxiv.org/abs/2403.20045
This paper addresses an interesting yet challenging problem -- source-free unsupervised domain adaptation (SFUDA) for pinhole-to-panoramic semantic segmentation -- given only a pinhole image-trained model (i.e., source) and unlabeled panoramic images
Externí odkaz:
http://arxiv.org/abs/2403.12505
Autor:
Nguyen, Tri, Nguyen, Huong, Ijaz, Ahmad, Sheikhi, Saeid, Vasilakos, Athanasios V., Kostakos, Panos
The rapid integration of Generative AI (GenAI) and Large Language Models (LLMs) in sectors such as education and healthcare have marked a significant advancement in technology. However, this growth has also led to a largely unexplored aspect: their s
Externí odkaz:
http://arxiv.org/abs/2403.12239
Low-light images often suffer from limited visibility and multiple types of degradation, rendering low-light image enhancement (LIE) a non-trivial task. Some endeavors have been recently made to enhance low-light images using convolutional neural net
Externí odkaz:
http://arxiv.org/abs/2312.13265
In recent years, artificial intelligence (AI) and machine learning (ML) are reshaping society's production methods and productivity, and also changing the paradigm of scientific research. Among them, the AI language model represented by ChatGPT has m
Externí odkaz:
http://arxiv.org/abs/2310.06278
The ability to scene understanding in adverse visual conditions, e.g., nighttime, has sparked active research for RGB-Thermal (RGB-T) semantic segmentation. However, it is essentially hampered by two critical problems: 1) the day-night gap of RGB ima
Externí odkaz:
http://arxiv.org/abs/2307.04470
Autor:
Chang, Weng-Long, Wong, Renata, Chung, Wen-Yu, Chen, Yu-Hao, Chen, Ju-Chin, Vasilakos, Athanasios V.
Given an undirected, unweighted graph with $n$ vertices and $m$ edges, the maximum cut problem is to find a partition of the $n$ vertices into disjoint subsets $V_1$ and $V_2$ such that the number of edges between them is as large as possible. Classi
Externí odkaz:
http://arxiv.org/abs/2305.16644