research
∙
05/31/2023
Additional Positive Enables Better Representation Learning for Medical Images
This paper presents a new way to identify additional positive pairs for ...
share
research
∙
04/22/2023
BiTrackGAN: Cascaded CycleGANs to Constraint Face Aging
With the increased accuracy of modern computer vision technology, many a...
research
∙
01/06/2023
CHARM: Composing Heterogeneous Accelerators for Matrix Multiply on Versal ACAP Architecture
Dense matrix multiply (MM) serves as one of the most heavily used kernel...
research
∙
12/16/2022
Development of A Real-time POCUS Image Quality Assessment and Acquisition Guidance System
Point-of-care ultrasound (POCUS) is one of the most commonly applied too...
research
∙
12/02/2022
FedCoCo: A Memory Efficient Federated Self-supervised Framework for On-Device Visual Representation Learning
The ubiquity of edge devices has led to a growing amount of unlabeled da...
research
∙
08/25/2022
Enabling Weakly-Supervised Temporal Action Localization from On-Device Learning of the Video Stream
Detecting actions in videos have been widely applied in on-device applic...
research
∙
08/24/2022
Federated Self-Supervised Contrastive Learning and Masked Autoencoder for Dermatological Disease Diagnosis
In dermatological disease diagnosis, the private data collected by mobil...
research
∙
08/23/2022
Achieving Fairness in Dermatological Disease Diagnosis through Automatic Weight Adjusting Federated Learning and Personalization
Dermatological diseases pose a major threat to the global health, affect...
research
∙
08/07/2022
Distributed Contrastive Learning for Medical Image Segmentation
Supervised deep learning needs a large amount of labeled data to achieve...
research
∙
07/04/2022
Sustainable AI Processing at the Edge
Edge computing is a popular target for accelerating machine learning alg...
research
∙
04/29/2022
H2H: Heterogeneous Model to Heterogeneous System Mapping with Computation and Communication Awareness
The complex nature of real-world problems calls for heterogeneity in bot...
research
∙
04/28/2022
FPIRM: Floating-point Processing in Racetrack Memories
Convolutional neural networks (CNN) have become a ubiquitous algorithm w...
research
∙
04/23/2022
Federated Contrastive Learning for Volumetric Medical Image Segmentation
Supervised deep learning needs a large amount of labeled data to achieve...
research
∙
03/04/2022
FairPrune: Achieving Fairness Through Pruning for Dermatological Disease Diagnosis
Many works have shown that deep learning-based medical image classificat...
research
∙
02/23/2022
The Larger The Fairer? Small Neural Networks Can Achieve Fairness for Edge Devices
Along with the progress of AI democratization, neural networks are being...
research
∙
02/18/2022
EF-Train: Enable Efficient On-device CNN Training on FPGA Through Data Reshaping for Online Adaptation or Personalization
Conventionally, DNN models are trained once in the cloud and deployed in...
research
∙
02/14/2022
Learn by Challenging Yourself: Contrastive Visual Representation Learning with Hard Sample Generation
Contrastive learning (CL), a self-supervised learning approach, can effe...
research
∙
02/14/2022
Federated Contrastive Learning for Dermatological Disease Diagnosis via On-device Learning
Deep learning models have been deployed in an increasing number of edge ...
research
∙
11/21/2021
Distributed Unsupervised Visual Representation Learning with Fused Features
Federated learning (FL) enables distributed clients to learn a shared mo...
research
∙
09/14/2021
Hardware-aware Real-time Myocardial Segmentation Quality Control in Contrast Echocardiography
Automatic myocardial segmentation of contrast echocardiography has shown...
research
∙
06/16/2021
Positional Contrastive Learning for Volumetric Medical Image Segmentation
The success of deep learning heavily depends on the availability of larg...
research
∙
06/07/2021
Enabling On-Device Self-Supervised Contrastive Learning With Selective Data Contrast
After a model is deployed on edge devices, it is desirable for these dev...
research
∙
08/18/2020
Personalized Deep Learning for Ventricular Arrhythmias Detection on Medical IoT Systems
Life-threatening ventricular arrhythmias (VA) are the leading cause of s...
research
∙
08/17/2020
Towards Cardiac Intervention Assistance: Hardware-aware Neural Architecture Exploration for Real-Time 3D Cardiac Cine MRI Segmentation
Real-time cardiac magnetic resonance imaging (MRI) plays an increasingly...
research
∙
07/17/2020
Standing on the Shoulders of Giants: Hardware and Neural Architecture Co-Search with Hot Start
Hardware and neural architecture co-search that automatically generates ...
research
∙
07/07/2020
Enabling On-Device CNN Training by Self-Supervised Instance Filtering and Error Map Pruning
This work aims to enable on-device training of convolutional neural netw...
research
∙
02/06/2020
Low Overhead Online Data Flow Tracking for Intermittently Powered Non-volatile FPGAs
Energy harvesting is an attractive way to power future IoT devices since...
research
∙
10/31/2019
Device-Circuit-Architecture Co-Exploration for Computing-in-Memory Neural Accelerators
Co-exploration of neural architectures and hardware design is promising ...
research
∙
10/31/2019
On Neural Architecture Search for Resource-Constrained Hardware Platforms
In the recent past, the success of Neural Architecture Search (NAS) has ...
research
∙
07/21/2019
Achieving Super-Linear Speedup across Multi-FPGA for Real-Time DNN Inference
Real-time Deep Neural Network (DNN) inference with low-latency requireme...
research
∙
07/06/2019
Hardware/Software Co-Exploration of Neural Architectures
We propose a novel hardware and software co-exploration framework for ef...
research
∙
01/31/2019
Accuracy vs. Efficiency: Achieving Both through FPGA-Implementation Aware Neural Architecture Search
A fundamental question lies in almost every application of deep neural n...
research
∙
09/01/2018
DAC-SDC Low Power Object Detection Challenge for UAV Applications
The 55th Design Automation Conference (DAC) held its first System Design...
research
∙
02/03/2018