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Found 9 papers, 1 papers with code
SensEmo: Enabling Affective Learning through Real-time Emotion Recognition with Smartwatches
More importantly, SensEmo assists students to achieve better online learning outcomes, e. g., an average of 40. 0% higher grades in quizzes, over the traditional learning without student emotional feedback.
Characterizing Disparity Between Edge Models and High-Accuracy Base Models for Vision Tasks
To achieve this, we propose a learning-based approach to characterize the model difference, named the DELTA network, which complements the feature representation capability of the edge network in a compact form.
Data Distribution Dynamics in Real-World WiFi-Based Patient Activity Monitoring for Home Healthcare
This paper examines the application of WiFi signals for real-world monitoring of daily activities in home healthcare scenarios.
CarFi: Rider Localization Using Wi-Fi CSI
With the rise of hailing services, people are increasingly relying on shared mobility (e. g., Uber, Lyft) drivers to pick up for transportation.
SmartON: Just-in-Time Active Event Detection on Energy Harvesting Systems
We propose SmartON, a batteryless system that learns to wake up proactively at the right moment in order to detect events of interest.
Wi-Fringe: Leveraging Text Semantics in WiFi CSI-Based Device-Free Named Gesture Recognition
The lack of adequate training data is one of the major hurdles in WiFi-based activity recognition systems.
Zygarde: Time-Sensitive On-Device Deep Inference and Adaptation on Intermittently-Powered Systems
We propose Zygarde -- which is an energy -- and accuracy-aware soft real-time task scheduling framework for batteryless systems that flexibly execute deep learning tasks1 that are suitable for running on microcontrollers.
Intermittent Learning: On-Device Machine Learning on Intermittently Powered System
This paper introduces intermittent learning - the goal of which is to enable energy harvested computing platforms capable of executing certain classes of machine learning tasks effectively and efficiently.
AI-Enhanced 3D RF Representation Using Low-Cost mmWave Radar
This paper introduces a system that takes radio frequency (RF) signals from an off-the-shelf, low-cost, 77 GHz mm Wave radar and produces an enhanced 3D RF representation of a scene.
