7 citations · 19 across the 15 of their papers we have counts for
15 papers
One Model, Two Worlds: Bidirectional Sonar-Optical Translation
Shengji Jin, Trung Tien Dong, Ahmed Lamidi +3
Translating between imaging sonar and optical cameras is valuable for underwater perception, but supporting both directions with separate models duplicates storage and computation.…
Breaking the Compression Barrier: Cross-Architecture Compression Boundary Learning via Reverse Regrowth
Zhaocen Liu, Satvik Praveen, Yi Sheng
Model compression is critical for deploying networks on resource-constrained edge devices. While pruning-based methods can significantly reduce model size, they often suffer from a…
BAP-MOS: Bandit-Based Adaptive Prompting for Boundary-Sensitive Multi-Organ Segmentation
Satvik Praveen, Shengji Jin, Ahmed Lamidi +2
Multi-organ ultrasound segmentation remains challenging when anatomically adjacent structures must be delineated jointly, as localized boundary errors can persist even when Dice sc…
A Novel Diffusion Model for Pairwise Geoscience Data Generation with Unbalanced Training Dataset
Junhuan Yang, Yuzhou Zhang, Yi Sheng +2
Recently, the advent of generative AI technologies has made transformational impacts on our daily lives, yet its application in scientific applications remains in its early stages.…
APS-USCT: Ultrasound Computed Tomography on Sparse Data via AI-Physic Synergy
Yi Sheng, Hanchen Wang, Yipei Liu +4
Ultrasound computed tomography (USCT) is a promising technique that achieves superior medical imaging reconstruction resolution by fully leveraging waveform information, outperform…
Data-Algorithm-Architecture Co-Optimization for Fair Neural Networks on Skin Lesion Dataset
Yi Sheng, Junhuan Yang, Jinyang Li +6
As Artificial Intelligence (AI) increasingly integrates into our daily lives, fairness has emerged as a critical concern, particularly in medical AI, where datasets often reflect i…
PristiQ: A Co-Design Framework for Preserving Data Security of Quantum Learning in the Cloud
Zhepeng Wang, Yi Sheng, Nirajan Koirala +4
Benefiting from cloud computing, today's early-stage quantum computers can be remotely accessed via the cloud services, known as Quantum-as-a-Service (QaaS). However, it poses a hi…
A Physics-guided Generative AI Toolkit for Geophysical Monitoring
Junhuan Yang, Hanchen Wang, Yi Sheng +2
Full-waveform inversion (FWI) plays a vital role in geoscience to explore the subsurface. It utilizes the seismic wave to image the subsurface velocity map. As the machine learning…
TrojFair: Trojan Fairness Attacks
Mengxin Zheng, Jiaqi Xue, Yi Sheng +3
Deep learning models have been incorporated into high-stakes sectors, including healthcare diagnosis, loan approvals, and candidate recruitment, among others. Consequently, any bia…
Muffin: A Framework Toward Multi-Dimension AI Fairness by Uniting Off-the-Shelf Models
Yi Sheng, Junhuan Yang, Lei Yang +3
Model fairness (a.k.a., bias) has become one of the most critical problems in a wide range of AI applications. An unfair model in autonomous driving may cause a traffic accident if…
On-Device Unsupervised Image Segmentation
Junhuan Yang, Yi Sheng, Yuzhou Zhang +2
Along with the breakthrough of convolutional neural networks, learning-based segmentation has emerged in many research works. Most of them are based on supervised learning, requiri…
Federated Self-Supervised Contrastive Learning and Masked Autoencoder for Dermatological Disease Diagnosis
Yawen Wu, Dewen Zeng, Zhepeng Wang +5
In dermatological disease diagnosis, the private data collected by mobile dermatology assistants exist on distributed mobile devices of patients. Federated learning (FL) can use de…
The Larger The Fairer? Small Neural Networks Can Achieve Fairness for Edge Devices
Yi Sheng, Junhuan Yang, Yawen Wu +5
Along with the progress of AI democratization, neural networks are being deployed more frequently in edge devices for a wide range of applications. Fairness concerns gradually emer…
Federated Contrastive Learning for Dermatological Disease Diagnosis via On-device Learning
Yawen Wu, Dewen Zeng, Zhepeng Wang +5
Deep learning models have been deployed in an increasing number of edge and mobile devices to provide healthcare. These models rely on training with a tremendous amount of labeled…
Automated Architecture Search for Brain-inspired Hyperdimensional Computing
Junhuan Yang, Yi Sheng, Sizhe Zhang +6
This paper represents the first effort to explore an automated architecture search for hyperdimensional computing (HDC), a type of brain-inspired neural network. Currently, HDC des…