Search Results - "Chulhong Min"

Earables for Personal-Scale Behavior Analytics by Kawsar, Fahim, Min, Chulhong, Mathur, Akhil, Montanari, Alessandro

“…The rise of consumer wearables promises to have a profound impact on peoples lives by going beyond counting steps. Wearables such as eSense-an in-ear…”
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In-Ear PPG for Vital Signs by Ferlini, Andrea, Montanari, Alessandro, Min, Chulhong, Li, Hongwei, Sassi, Ugo, Kawsar, Fahim

“…Earables are now pervasive, and their established purpose, ergonomy, and noninvasive interaction uncover exciting opportunities for sensing and healthcare…”
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Towards Interpersonal Assistants: Next-Generation Conversational Agents by Hwang, Inseok, Lee, Youngki, Yoo, Chungkuk, Min, Chulhong, Yim, Dongsun, Kim, John

“…We propose novel interpersonal assistants, a next-generation conversational agent which is always-on, unobtrusively serving natural human-to-human…”
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A multidevice and multimodal dataset for human energy expenditure estimation using wearable devices by Gashi, Shkurta, Min, Chulhong, Montanari, Alessandro, Santini, Silvia, Kawsar, Fahim

“…We present a multi-device and multi-modal dataset, called WEEE , collected from 17 participants while they were performing different physical activities. WEEE…”
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On Tracking the Physicality of Wi-Fi: A Subspace Approach by Alloulah, Mohammed, Isopoussu, Anton, Min, Chulhong, Kawsar, Fahim

“…Wi-Fi channel state information (CSI) has emerged as a plausible modality for sensing different human activities as a function of modulations in the wireless…”
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SleepGAN: Towards Personalized Sleep Therapy Music by Yang, Jing, Min, Chulhong, Mathur, Akhil, Kawsar, Fahim

“…Sleep deficiency and disorders are one of the most unsolved public health challenges of modern times. Music therapy is a promising approach, offering a cheap…”
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Orchestrator: An active resource orchestration framework for mobile context monitoring in sensor-rich mobile environments by Seungwoo Kang, Youngki Lee, Chulhong Min, Younghyun Ju, Taiwoo Park, Jinwon Lee, Yunseok Rhee, Junehwa Song

“…In this paper, we present Orchestrator, an active resource orchestration framework for mobile context monitoring. Emerging pervasive environments will…”
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An efficient dataflow execution method for mobile context monitoring applications by Younghyun Ju, Chulhong Min, Youngki Lee, Jihyun Yu, Junehwa Song

“…In this paper, we propose a novel efficient dataflow execution method for mobile context monitoring applications. As a key approach to minimize the execution…”
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MobiCon: Mobile context monitoring platform: Incorporating context-awareness to smartphone-centric personal sensor networks by Youngki Lee, Younghyun Ju, Chulhong Min, Jihyun Yu, Junehwa Song

“…In this demonstration, we will show MobiCon, a context monitoring platform; it runs over smartphones and sensor OSs, and facilitates development and deployment…”
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A mobile context monitoring platform for pervasive computing environments by Youngki Lee, Chulhong Min, Younghyun Ju, Pushp, Saumay, Junehwa Song

“…In this paper, we present a new mobile platform to support emerging pervasive applications in a Personal Area Network (PAN)-scale dynamic mobile computing…”
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Time-bound Contextual Bio-ID Generation for Minimalist Wearables by Orzikulova, Adiba, Vasile, Diana A, Kawsar, Fahim, Min, Chulhong

“…As wearable devices become increasingly miniaturized and powerful, a new opportunity arises for instant and dynamic device-to-device collaboration and…”
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Enabling Cross-Camera Collaboration for Video Analytics on Distributed Smart Cameras by Min, Chulhong, Yi, Juheon, Acer, Utku Gunay, Kawsar, Fahim

“…Overlapping cameras offer exciting opportunities to view a scene from different angles, allowing for more advanced, comprehensive and robust analysis. However,…”
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Automatic Detection of Reactions to Music via Earable Sensing by Lee, Euihyoek, Min, Chulhong, Lee, Jeaseung, Yu, Jin, Kang, Seungwoo

“…We present GrooveMeter, a novel system that automatically detects vocal and motion reactions to music via earable sensing and supports music engagement-aware…”
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SensiX: A System for Best-Effort Inference of Machine Learning Models in Multi-Device Environments by Min, Chulhong, Mathur, Akhil, Montanari, Alessandro, Kawsar, Fahim

“…Multiple sensory devices on and around us are on the rise and require us to redesign a system to make an inference of ML models accurate, robust, and efficient…”
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Quantifying a Vehicle Interior Design’s Ability to Accommodate Drivers’ Preferences by Park, Woojin, Min, Chulhong, Perdu, Loc, Escobar, Claudia

“…This study presents novel methods for evaluating a vehicle interior design’s ability to accommodate drivers’ preferences. The methods are based on the…”
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Synergy: Towards On-Body AI via Tiny AI Accelerator Collaboration on Wearables by Gong, Taesik, Jang, Si Young, Acer, Utku Günay, Kawsar, Fahim, Min, Chulhong

“…The advent of tiny artificial intelligence (AI) accelerators enables AI to run at the extreme edge, offering reduced latency, lower power cost, and improved…”
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Deploying Collaborative Machine Learning Systems in Edge with Multiple Cameras by Jang, Si Young, Acer, Utku Gunay, Min, Chulhong, Kawsar, Fahim

“…Advancement in hardware capability has opened up the possibility of performing ML inference tasks at the edge using a large volume of sensory data generated…”
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An AI-Native Runtime for Multi-Wearable Environments by Min, Chulhong, Acer, Utku Günay, Jang, SiYoung, Choi, Sangwon, Vasile, Diana A, Gong, Taesik, Yi, Juheon, Kawsar, Fahim

“…The miniaturization of AI accelerators is paving the way for next-generation wearable applications within wearable technologies. We introduce Mojito, an…”
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Scalable Power Impact Prediction of Mobile Sensing Applications at Pre-Installation Time by Min, Chulhong, Lee, Youngki, Yoo, Chungkuk, Hwang, Inseok, Ju, Younghyun, Song, Junehwa, Kang, Seungwoo

“…Today's smartphone application (hereinafter 'app') markets do not provide information on power consumption of apps, which is essential for users. Continuous…”
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ColloSSL: Collaborative Self-Supervised Learning for Human Activity Recognition by Jain, Yash, Tang, Chi Ian, Min, Chulhong, Kawsar, Fahim, Mathur, Akhil

“…A major bottleneck in training robust Human-Activity Recognition models (HAR) is the need for large-scale labeled sensor datasets. Because labeling large…”
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