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Found 11 papers, 5 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.
Affine-based Deformable Attention and Selective Fusion for Semi-dense Matching
Identifying robust and accurate correspondences across images is a fundamental problem in computer vision that enables various downstream tasks.
DrHouse: An LLM-empowered Diagnostic Reasoning System through Harnessing Outcomes from Sensor Data and Expert Knowledge
Large language models (LLMs) have the potential to transform digital healthcare, as evidenced by recent advances in LLM-based virtual doctors.
An Ensemble Learning Approach for Exercise Detection in Type 1 Diabetes Patients
Artificial pancreas (AP) systems have been developed as a solution for type 1 diabetic patients to mimic the behavior of the pancreas and regulate blood glucose levels.
A Deep Reinforcement Learning Framework for Optimizing Congestion Control in Data Centers
We leverage multiagent reinforcement learning to design a system for dynamic tuning of congestion control parameters at end-hosts in a data center.
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.
ASpanFormer: Detector-Free Image Matching with Adaptive Span Transformer
Generating robust and reliable correspondences across images is a fundamental task for a diversity of applications.
Learning to Match Features with Seeded Graph Matching Network
2) Seeded Graph Neural Network, which utilizes seed matches to pass messages within/across images and predicts assignment costs.
PointDSC: Robust Point Cloud Registration using Deep Spatial Consistency
Removing outlier correspondences is one of the critical steps for successful feature-based point cloud registration.
ASLFeat: Learning Local Features of Accurate Shape and Localization
This work focuses on mitigating two limitations in the joint learning of local feature detectors and descriptors.
MPC-guided Imitation Learning of Neural Network Policies for the Artificial Pancreas
Even though model predictive control (MPC) is currently the main algorithm for insulin control in the artificial pancreas (AP), it usually requires complex online optimizations, which are infeasible for resource-constrained medical devices.
