2 citations · 5 across the 11 of their papers we have counts for
12 papers
A Mixture of Experts Foundation Model for Scanning Electron Microscopy Image Analysis
Sk Miraj Ahmed, Yuewei Lin, Chuntian Cao +9
Scanning Electron Microscopy (SEM) is indispensable in modern materials science, enabling high-resolution imaging across a wide range of structural, chemical, and functional invest…
Substrate-Mediated Evaporation and Stochastic Evolution of Supported Au Nanoparticles
Dmitri N. Zakharov, Xiaohui Qu, Hong Wang +6
We use in situ transmission electron microscopy with automated tracking to study supported gold nanoparticles (NPs) during high-temperature vacuum annealing. \rev{The average mass…
TPCpp-10M: Simulated proton-proton collisions in a Time Projection Chamber for AI Foundation Models
Shuhang Li, Yi Huang, David Park +10
Scientific foundation models hold great promise for advancing nuclear and particle physics by improving analysis precision and accelerating discovery. Yet, progress in this field i…
FM4NPP: A Scaling Foundation Model for Nuclear and Particle Physics
David Park, Shuhang Li, Yi Huang +9
Large language models have revolutionized artificial intelligence by enabling large, generalizable models trained through self-supervision. This paradigm has inspired the developme…
Macro2Micro: A Rapid and Precise Cross-modal Magnetic Resonance Imaging Synthesis using Multi-scale Structural Brain Similarity
Sooyoung Kim, Joonwoo Kwon, Junbeom Kwon +5
The human brain is a complex system requiring both macroscopic and microscopic components for comprehensive understanding. However, mapping nonlinear relationships between these sc…
Revisiting Your Memory: Reconstruction of Affect-Contextualized Memory via EEG-guided Audiovisual Generation
Joonwoo Kwon, Heehwan Wang, Jinwoo Lee +4
In this paper, we introduce RevisitAffectiveMemory, a novel task designed to reconstruct autobiographical memories through audio-visual generation guided by affect extracted from e…
Repurposing Image Diffusion Models for Training-Free Music Style Transfer on Mel-spectrograms
Heehwan Wang, Joonwoo Kwon, Sooyoung Kim +4
Music style transfer blends source structure with reference style to enable personalized music creation. However, existing zero-shot methods often struggle to capture fine-grained…
AesFA: An Aesthetic Feature-Aware Arbitrary Neural Style Transfer
Joonwoo Kwon, Sooyoung Kim, Yuewei Lin +2
Neural style transfer (NST) has evolved significantly in recent years. Yet, despite its rapid progress and advancement, existing NST methods either struggle to transfer aesthetic i…
Exploring Robust Features for Improving Adversarial Robustness
Hong Wang, Yuefan Deng, Shinjae Yoo +1
While deep neural networks (DNNs) have revolutionized many fields, their fragility to carefully designed adversarial attacks impedes the usage of DNNs in safety-critical applicatio…
INSURE: An Information Theory Inspired Disentanglement and Purification Model for Domain Generalization
Xi Yu, Huan-Hsin Tseng, Shinjae Yoo +2
Domain Generalization (DG) aims to learn a generalizable model on the unseen target domain by only training on the multiple observed source domains. Although a variety of DG method…
AGKD-BML: Defense Against Adversarial Attack by Attention Guided Knowledge Distillation and Bi-directional Metric Learning
Hong Wang, Yuefan Deng, Shinjae Yoo +2
While deep neural networks have shown impressive performance in many tasks, they are fragile to carefully designed adversarial attacks. We propose a novel adversarial training-base…
Transparent Object Tracking Benchmark
Heng Fan, Halady Akhilesha Miththanthaya, Harshit +5
Visual tracking has achieved considerable progress in recent years. However, current research in the field mainly focuses on tracking of opaque objects, while little attention is p…