@inproceedings{ae4fcc834c9f403ab9ca6827d293a4a5,
title = "The 3rd International Workshop on Deep Learning for the Web of Things",
abstract = "Deep learning and the Web of Things (WoT) have become powerful tools for web engineering, leading to increased investigation and publication of research related to deep learning in web engineering. Therefore, this workshop is titled {"}The 3rd International Workshop on Deep Learning for the Web of Things{"}for the Web Conference 2023 (WWW'23). This workshop features five research articles: (1) {"}Multiple-Agent Deep Reinforcement Learning for Avatar Migration in Vehicular Metaverses{"}, (2) {"}Web 3.0: Future of the Internet{"}, (3) {"}Weighted Statistically Significant Pattern Mining{"}, (4) {"}DSNet: Efficient Lightweight Model for Video Salient Object Detection for IoT and WoT Applications{"}, and (5) {"}The Human-Centric Metaverse: A Survey{"}.",
keywords = "Deep Learning, Internet of Things, Machine learning, Web of Things",
author = "Cheng Shi and Chang, {Chin Chen} and Eyhab Al-Masri and Chen, {Abel C.H.} and Haishuai Wang and Qichun Zhang and Tseng, {Hsiao Ting} and K. Shankar and Taehong Kim",
note = "Publisher Copyright: {\textcopyright} 2023 Owner/Author.; 2023 World Wide Web Conference, WWW 2023 ; Conference date: 30-04-2023 Through 04-05-2023",
year = "2023",
month = apr,
day = "30",
doi = "10.1145/3543873.3589744",
language = "???core.languages.en_GB???",
series = "ACM Web Conference 2023 - Companion of the World Wide Web Conference, WWW 2023",
publisher = "Association for Computing Machinery, Inc",
pages = "1257",
booktitle = "ACM Web Conference 2023 - Companion of the World Wide Web Conference, WWW 2023",
}