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Yunfan Gao
Researcher at Fudan University
Publications - 7
Citations - 92
Yunfan Gao is an academic researcher from Fudan University. The author has contributed to research in topics: Computer science & Scarcity. The author has an hindex of 2, co-authored 2 publications receiving 14 citations.
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CRISLoc: Reconstructable CSI Fingerprinting for Indoor Smartphone Localization
TL;DR: This study reveals important properties about the stability and sensitivity of smartphone CSI that has not been reported previously, and presents CRISLoc, the first CSI fingerprinting-based localization prototype system using ubiquitous smartphones.
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CRISLoc: Reconstructable CSI Fingerprintingfor Indoor Smartphone Localization.
TL;DR: In this paper, the authors presented CRISLoc, the first CSI fingerprinting based indoor localization prototype system using ubiquitous smartphones, which operates in a completely passive mode, overhearing the packets on-the-fly for his own CSI acquisition.
Journal ArticleDOI
Chat-REC: Towards Interactive and Explainable LLMs-Augmented Recommender System
TL;DR: In this article , the ChatGPT augmented recommender system (ChatGPT Augmented Recommender System) is proposed for building conversational recommender systems by converting user profiles and historical interactions into prompts.
Journal ArticleDOI
Unmanned Aerial Vehicle (UAV)-Assisted Path Planning for Unmanned Ground Vehicles (UGVs) via Disciplined Convex-Concave Programming
TL;DR: This work presents a vision-based unmanned aerial vehicle (UAV)-assisted cooperative system for multiple UGVs that harnesses the broad vision of UAV and operates in both general outdoor and global positioning system (GPS)-denied indoor environments.
Journal ArticleDOI
GeoBERT: Pre-Training Geospatial Representation Learning on Point-of-Interest
TL;DR: Zhang et al. as mentioned in this paper proposed a large-scale pre-training geospatial representation learning model called GeoBERT, which collects about 17 million POIs in 30 cities across China to construct a pre-trained corpora, with 313 POI types as the tokens and the level-7 Geohash grids as the basic units.