research
∙
07/13/2023
TinyMetaFed: Efficient Federated Meta-Learning for TinyML
The field of Tiny Machine Learning (TinyML) has made substantial advance...
share
research
∙
04/11/2023
TinyReptile: TinyML with Federated Meta-Learning
Tiny machine learning (TinyML) is a rapidly growing field aiming to demo...
research
∙
03/06/2023
A Semi-Parametric Model Simultaneously Handling Unmeasured Confounding, Informative Cluster Size, and Truncation by Death with a Data Application in Medicare Claims
Nearly 300,000 older adults experience a hip fracture every year, the ma...
research
∙
07/18/2022
SeLoC-ML: Semantic Low-Code Engineering for Machine Learning Applications in Industrial IoT
Internet of Things (IoT) is transforming the industry by bridging the ga...
research
∙
02/18/2022
How to Manage Tiny Machine Learning at Scale: An Industrial Perspective
Tiny machine learning (TinyML) has gained widespread popularity where ma...
research
∙
05/04/2021
The Synergy of Complex Event Processing and Tiny Machine Learning in Industrial IoT
Focusing on comprehensive networking, big data, and artificial intellige...
research
∙
03/15/2021
TinyOL: TinyML with Online-Learning on Microcontrollers
Tiny machine learning (TinyML) is a fast-growing research area committed...
research
∙
06/11/2019
TW-SMNet: Deep Multitask Learning of Tele-Wide Stereo Matching
In this paper, we introduce the problem of estimating the real world dep...
research
∙
06/07/2019
Deep Robust Single Image Depth Estimation Neural Network Using Scene Understanding
Single image depth estimation (SIDE) plays a crucial role in 3D computer...
research
∙
10/16/2018
DN-ResNet: Efficient Deep Residual Network for Image Denoising
A deep learning approach to blind denoising of images without complete k...
research
∙
11/11/2017
