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08/26/2023
Muffin: A Framework Toward Multi-Dimension AI Fairness by Uniting Off-the-Shelf Models
Model fairness (a.k.a., bias) has become one of the most critical proble...
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08/10/2023
Masked Diffusion as Self-supervised Representation Learner
Denoising diffusion probabilistic models have recently demonstrated stat...
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07/30/2023
Proof-of-Federated-Learning-Subchain: Free Partner Selection Subchain Based on Federated Learning
The continuous thriving of the Blockchain society motivates research in ...
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07/29/2023
Improving Realistic Worst-Case Performance of NVCiM DNN Accelerators through Training with Right-Censored Gaussian Noise
Compute-in-Memory (CiM), built upon non-volatile memory (NVM) devices, i...
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06/26/2023
Toward Fairness Through Fair Multi-Exit Framework for Dermatological Disease Diagnosis
Fairness has become increasingly pivotal in medical image recognition. H...
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06/26/2023
AME-CAM: Attentive Multiple-Exit CAM for Weakly Supervised Segmentation on MRI Brain Tumor
Magnetic resonance imaging (MRI) is commonly used for brain tumor segmen...
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06/23/2023
How to Efficiently Adapt Large Segmentation Model(SAM) to Medical Images
The emerging scale segmentation model, Segment Anything (SAM), exhibits ...
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06/12/2023
On the Viability of using LLMs for SW/HW Co-Design: An Example in Designing CiM DNN Accelerators
Deep Neural Networks (DNNs) have demonstrated impressive performance acr...
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06/08/2023
A Novel Confidence Induced Class Activation Mapping for MRI Brain Tumor Segmentation
Magnetic resonance imaging (MRI) is a commonly used technique for brain ...
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06/06/2023
Conditional Diffusion Models for Weakly Supervised Medical Image Segmentation
Recent advances in denoising diffusion probabilistic models have shown g...
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05/31/2023
Additional Positive Enables Better Representation Learning for Medical Images
This paper presents a new way to identify additional positive pairs for ...
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05/23/2023
Negative Feedback Training: A Novel Concept to Improve Robustness of NVCiM DNN Accelerators
Compute-in-Memory (CiM) utilizing non-volatile memory (NVM) devices pres...
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05/09/2023
TinyML Design Contest for Life-Threatening Ventricular Arrhythmia Detection
The first ACM/IEEE TinyML Design Contest (TDC) held at the 41st Internat...
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01/08/2023
Fair Multi-Exit Framework for Facial Attribute Classification
Fairness has become increasingly pivotal in facial recognition. Without ...
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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...
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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...
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11/15/2022
Unsupervised Feature Clustering Improves Contrastive Representation Learning for Medical Image Segmentation
Self-supervised instance discrimination is an effective contrastive pret...
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11/03/2022
ImageCAS: A Large-Scale Dataset and Benchmark for Coronary Artery Segmentation based on Computed Tomography Angiography Images
Cardiovascular disease (CVD) accounts for about half of non-communicable...
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10/30/2022
QuEst: Graph Transformer for Quantum Circuit Reliability Estimation
Among different quantum algorithms, PQC for QML show promises on near-te...
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10/15/2022
TopGen: Topology-Aware Bottom-Up Generator for Variational Quantum Circuits
Variational Quantum Algorithms (VQA) are promising to demonstrate quantu...
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10/04/2022
Improving Quantum Classifier Performance in NISQ Computers by Voting Strategy from Ensemble Learning
Due to the immense potential of quantum computers and the significant co...
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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...
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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...
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08/07/2022
Distributed Contrastive Learning for Medical Image Segmentation
Supervised deep learning needs a large amount of labeled data to achieve...
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08/02/2022
PAN: Pulse Ansatz on NISQ Machines
Variational quantum algorithms (VQAs) have demonstrated great potentials...
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07/27/2022
Contrastive Image Synthesis and Self-supervised Feature Adaptation for Cross-Modality Biomedical Image Segmentation
This work presents a novel framework CISFA (Contrastive Image synthesis ...
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07/15/2022
Computing-In-Memory Neural Network Accelerators for Safety-Critical Systems: Can Small Device Variations Be Disastrous?
Computing-in-Memory (CiM) architectures based on emerging non-volatile m...
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06/08/2022
RT-DNAS: Real-time Constrained Differentiable Neural Architecture Search for 3D Cardiac Cine MRI Segmentation
Accurately segmenting temporal frames of cine magnetic resonance imaging...
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05/25/2022
On the Reliability of Computing-in-Memory Accelerators for Deep Neural Networks
Computing-in-memory with emerging non-volatile memory (nvCiM) is shown t...
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05/10/2022
OTFPF: Optimal Transport-Based Feature Pyramid Fusion Network for Brain Age Estimation with 3D Overlapped ConvNeXt
Chronological age of healthy brain is able to be predicted using deep ne...
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04/23/2022
Federated Contrastive Learning for Volumetric Medical Image Segmentation
Supervised deep learning needs a large amount of labeled data to achieve...
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03/25/2022
A Semi-Decoupled Approach to Fast and Optimal Hardware-Software Co-Design of Neural Accelerators
In view of the performance limitations of fully-decoupled designs for ne...
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03/04/2022
FairPrune: Achieving Fairness Through Pruning for Dermatological Disease Diagnosis
Many works have shown that deep learning-based medical image classificat...
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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...
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02/17/2022
SWIM: Selective Write-Verify for Computing-in-Memory Neural Accelerators
Computing-in-Memory architectures based on non-volatile emerging memorie...
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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...
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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 ...
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11/21/2021
Distributed Unsupervised Visual Representation Learning with Fused Features
Federated learning (FL) enables distributed clients to learn a shared mo...
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11/01/2021
One Proxy Device Is Enough for Hardware-Aware Neural Architecture Search
Convolutional neural networks (CNNs) are used in numerous real-world app...
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10/23/2021
"One-Shot" Reduction of Additive Artifacts in Medical Images
Medical images may contain various types of artifacts with different pat...
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09/15/2021
Semi-supervised Contrastive Learning for Label-efficient Medical Image Segmentation
The success of deep learning methods in medical image segmentation tasks...
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09/14/2021
Hardware-aware Real-time Myocardial Segmentation Quality Control in Contrast Echocardiography
Automatic myocardial segmentation of contrast echocardiography has shown...
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09/13/2021
RADARS: Memory Efficient Reinforcement Learning Aided Differentiable Neural Architecture Search
Differentiable neural architecture search (DNAS) is known for its capaci...
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09/08/2021
Exploration of Quantum Neural Architecture by Mixing Quantum Neuron Designs
With the constant increase of the number of quantum bits (qubits) in the...
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09/08/2021
Can Noise on Qubits Be Learned in Quantum Neural Network? A Case Study on QuantumFlow
In the noisy intermediate-scale quantum (NISQ) era, one of the key quest...
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09/01/2021
ImageTBAD: A 3D Computed Tomography Angiography Image Dataset for Automatic Segmentation of Type-B Aortic Dissection
Type-B Aortic Dissection (TBAD) is one of the most serious cardiovascula...
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07/06/2021
Uncertainty Modeling of Emerging Device-based Computing-in-Memory Neural Accelerators with Application to Neural Architecture Search
Emerging device-based Computing-in-memory (CiM) has been proved to be a ...
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06/29/2021
Segmentation with Multiple Acceptable Annotations: A Case Study of Myocardial Segmentation in Contrast Echocardiography
Most existing deep learning-based frameworks for image segmentation assu...
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06/16/2021
Positional Contrastive Learning for Volumetric Medical Image Segmentation
The success of deep learning heavily depends on the availability of larg...
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06/07/2021