5 citations · 20 across the 34 of their papers we have counts for
12 papers · 1 filter
Expanding Event Modality Applications through a Robust CLIP-Based Encoder
Sungheon Jeong, Hanning Chen, Sanggeon Yun +4
This paper introduces a powerful encoder that transfers CLIP`s capabilities to event-based data, enhancing its utility and expanding its applicability across diverse domains. While…
Scalable Readability Evaluation for Graph Layouts: 2D Geometric Distributed Algorithms
Sanggeon Yun
Graphs, consisting of vertices and edges, are vital for representing complex relationships in fields like social networks, finance, and blockchain. Visualizing these graphs helps a…
Exploiting Boosting in Hyperdimensional Computing for Enhanced Reliability in Healthcare
SungHeon Jeong, Hamza Errahmouni Barkam, Sanggeon Yun +3
Hyperdimensional computing (HDC) enables efficient data encoding and processing in high-dimensional space, benefiting machine learning and data analysis. However, underutilization…
Continuous GNN-based Anomaly Detection on Edge using Efficient Adaptive Knowledge Graph Learning
Sanggeon Yun, Ryozo Masukawa, William Youngwoo Chung +3
The increasing demand for robust security solutions across various industries has made Video Anomaly Detection (VAD) a critical task in applications such as intelligent surveillanc…
PV-VTT: A Privacy-Centric Dataset for Mission-Specific Anomaly Detection and Natural Language Interpretation
Ryozo Masukawa, Sanggeon Yun, Yoshiki Yamaguchi +1
Video crime detection is a significant application of computer vision and artificial intelligence. However, existing datasets primarily focus on detecting severe crimes by analyzin…
MissionGNN: Hierarchical Multimodal GNN-based Weakly Supervised Video Anomaly Recognition with Mission-Specific Knowledge Graph Generation
Sanggeon Yun, Ryozo Masukawa, Minhyoung Na +1
In the context of escalating safety concerns across various domains, the tasks of Video Anomaly Detection (VAD) and Video Anomaly Recognition (VAR) have emerged as critically impor…
NeuroHash: A Hyperdimensional Neuro-Symbolic Framework for Spatially-Aware Image Hashing and Retrieval
Sanggeon Yun, Ryozo Masukawa, SungHeon Jeong +1
Customizable image retrieval from large datasets remains a critical challenge, particularly when preserving spatial relationships within images. Traditional hashing methods, primar…
HDReason: Algorithm-Hardware Codesign for Hyperdimensional Knowledge Graph Reasoning
Hanning Chen, Yang Ni, Ali Zakeri +7
In recent times, a plethora of hardware accelerators have been put forth for graph learning applications such as vertex classification and graph classification. However, previous w…
EcoSense: Energy-Efficient Intelligent Sensing for In-Shore Ship Detection through Edge-Cloud Collaboration
Wenjun Huang, Hanning Chen, Yang Ni +5
Detecting marine objects inshore presents challenges owing to algorithmic intricacies and complexities in system deployment. We propose a difficulty-aware edge-cloud collaborative…
TaskCLIP: Extend Large Vision-Language Model for Task Oriented Object Detection
Hanning Chen, Wenjun Huang, Yang Ni +6
Task-oriented object detection aims to find objects suitable for accomplishing specific tasks. As a challenging task, it requires simultaneous visual data processing and reasoning…
A Plug-in Tiny AI Module for Intelligent and Selective Sensor Data Transmission
Wenjun Huang, Arghavan Rezvani, Hanning Chen +4
Applications in the Internet of Things (IoT) utilize machine learning to analyze sensor-generated data. However, a major challenge lies in the lack of targeted intelligence in curr…
HyperSense: Hyperdimensional Intelligent Sensing for Energy-Efficient Sparse Data Processing
Sanggeon Yun, Hanning Chen, Ryozo Masukawa +6
Introducing HyperSense, our co-designed hardware and software system efficiently controls Analog-to-Digital Converter (ADC) modules' data generation rate based on object presence p…