Search Results for author: Seong Jae Hwang

Found 18 papers, 8 papers with code

EAGLE: Eigen Aggregation Learning for Object-Centric Unsupervised Semantic Segmentation

1 code implementation3 Mar 2024 Chanyoung Kim, Woojung Han, Dayun Ju, Seong Jae Hwang

Semantic segmentation has innately relied on extensive pixel-level annotated data, leading to the emergence of unsupervised methodologies.

Object Representation Learning +4

Test-time Fourier Style Calibration for Domain Generalization

1 code implementation13 May 2022 Xingchen Zhao, Chang Liu, Anthony Sicilia, Seong Jae Hwang, Yun Fu

Thus, it is still possible that those methods can overfit to source domains and perform poorly on target domains.

Domain Generalization

The Change that Matters in Discourse Parsing: Estimating the Impact of Domain Shift on Parser Error

4 code implementations Findings (ACL) 2022 Katherine Atwell, Anthony Sicilia, Seong Jae Hwang, Malihe Alikhani

Our results not only motivate our proposal and help us to understand its limitations, but also provide insight on the properties of discourse models and datasets which improve performance in domain adaptation.

Discourse Parsing Domain Adaptation +1

PAC-Bayesian Domain Adaptation Bounds for Multiclass Learners

1 code implementation12 Jul 2022 Anthony Sicilia, Katherine Atwell, Malihe Alikhani, Seong Jae Hwang

Multiclass neural networks are a common tool in modern unsupervised domain adaptation, yet an appropriate theoretical description for their non-uniform sample complexity is lacking in the adaptation literature.

Unsupervised Domain Adaptation

PAC Bayesian Performance Guarantees for Deep (Stochastic) Networks in Medical Imaging

1 code implementation12 Apr 2021 Anthony Sicilia, Xingchen Zhao, Anastasia Sosnovskikh, Seong Jae Hwang

Application of deep neural networks to medical imaging tasks has in some sense become commonplace.

Sampling-free Uncertainty Estimation in Gated Recurrent Units with Exponential Families

no code implementations19 Apr 2018 Seong Jae Hwang, Ronak Mehta, Hyunwoo J. Kim, Vikas Singh

There has recently been a concerted effort to derive mechanisms in vision and machine learning systems to offer uncertainty estimates of the predictions they make.

Conditional Recurrent Flow: Conditional Generation of Longitudinal Samples with Applications to Neuroimaging

no code implementations ICCV 2019 Seong Jae Hwang, Zirui Tao, Won Hwa Kim, Vikas Singh

Such models may work for cross-sectional studies, however, they are not suitable to generate data for longitudinal studies that focus on "progressive" behavior in a sequence of data.

Tensorize, Factorize and Regularize: Robust Visual Relationship Learning

no code implementations CVPR 2018 Seong Jae Hwang, Sathya N. Ravi, Zirui Tao, Hyunwoo J. Kim, Maxwell D. Collins, Vikas Singh

Visual relationships provide higher-level information of objects and their relations in an image – this enables a semantic understanding of the scene and helps downstream applications.

Relational Reasoning Relationship Detection +1

Coupled Harmonic Bases for Longitudinal Characterization of Brain Networks

no code implementations CVPR 2016 Seong Jae Hwang, Nagesh Adluru, Maxwell D. Collins, Sathya N. Ravi, Barbara B. Bendlin, Sterling C. Johnson, Vikas Singh

There is a great deal of interest in using large scale brain imaging studies to understand how brain connectivity evolves over time for an individual and how it varies over different levels/quantiles of cognitive function.

A Projection Free Method for Generalized Eigenvalue Problem With a Nonsmooth Regularizer

no code implementations ICCV 2015 Seong Jae Hwang, Maxwell D. Collins, Sathya N. Ravi, Vamsi K. Ithapu, Nagesh Adluru, Sterling C. Johnson, Vikas Singh

Eigenvalue problems are ubiquitous in computer vision, covering a very broad spectrum of applications ranging from estimation problems in multi-view geometry to image segmentation.

Image Segmentation Semantic Segmentation +1

Advancing Text-Driven Chest X-Ray Generation with Policy-Based Reinforcement Learning

no code implementations11 Mar 2024 Woojung Han, Chanyoung Kim, Dayun Ju, Yumin Shim, Seong Jae Hwang

Recent advances in text-conditioned image generation diffusion models have begun paving the way for new opportunities in modern medical domain, in particular, generating Chest X-rays (CXRs) from diagnostic reports.

Denoising Image Generation +1

WoLF: Large Language Model Framework for CXR Understanding

no code implementations19 Mar 2024 Seil Kang, Donghyun Kim, Junhyeok Kim, Hyo Kyung Lee, Seong Jae Hwang

(1) Previous methods solely use CXR reports, which are insufficient for comprehensive Visual Question Answering (VQA), especially when additional health-related data like medication history and prior diagnoses are needed.

Anatomy Instruction Following +4

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