Sangheum Hwang

Orcid: 0000-0003-2136-296X

According to our database1, Sangheum Hwang authored at least 36 papers between 2015 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Bibliography

2024
Context-aware cross feature attentive network for click-through rate predictions.
Appl. Intell., October, 2024

StochCA: A novel approach for exploiting pretrained models with cross-attention.
Neural Networks, 2024

Generalized Outlier Exposure: Towards a trustworthy out-of-distribution detector without sacrificing accuracy.
Neurocomputing, 2024

GTA: Guided Transfer of Spatial Attention from Object-Centric Representations.
CoRR, 2024

Self-Supervised Representation Learning for Basecalling Nanopore Sequencing Data.
IEEE Access, 2024

Comparison of Out-of-Distribution Detection Performance of CLIP-based Fine-Tuning Methods.
Proceedings of the International Conference on Electronics, Information, and Communication, 2024

2023
A unified benchmark for the unknown detection capability of deep neural networks.
Expert Syst. Appl., November, 2023

Elucidating robust learning with uncertainty-aware corruption pattern estimation.
Pattern Recognit., June, 2023

Rethinking Evaluation Protocols of Visual Representations Learned via Self-supervised Learning.
CoRR, 2023

Few-shot Fine-tuning is All You Need for Source-free Domain Adaptation.
CoRR, 2023

Deep Active Learning with Contrastive Learning Under Realistic Data Pool Assumptions.
CoRR, 2023

2022
A new smart smudge attack using CNN.
Int. J. Inf. Sec., 2022

2021
Exploiting Global Structure Information to Improve Medical Image Segmentation.
Sensors, 2021

Similarity based Deep Neural Networks.
Int. J. Fuzzy Log. Intell. Syst., 2021

Elucidating Noisy Data via Uncertainty-Aware Robust Learning.
CoRR, 2021

Supervised Contrastive Embedding for Medical Image Segmentation.
IEEE Access, 2021

A Unified Defect Pattern Analysis of Wafer Maps Using Density-Based Clustering.
IEEE Access, 2021

Self-Knowledge Distillation with Progressive Refinement of Targets.
Proceedings of the 2021 IEEE/CVF International Conference on Computer Vision, 2021

2020
Self-Knowledge Distillation: A Simple Way for Better Generalization.
CoRR, 2020

Additive Ensemble Neural Networks.
IEEE Access, 2020

A New Splitting Criterion for Better Interpretable Trees.
IEEE Access, 2020

Confidence-Aware Learning for Deep Neural Networks.
Proceedings of the 37th International Conference on Machine Learning, 2020

2018
A Scalable Feature Based Clustering Algorithm for Sequences with Many Distinct Items.
Int. J. Fuzzy Log. Intell. Syst., 2018

Predicting breast tumor proliferation from whole-slide images: the TUPAC16 challenge.
CoRR, 2018

Robust relevance vector machine for classification with variational inference.
Ann. Oper. Res., 2018

2017
A Unified Framework for Tumor Proliferation Score Prediction in Breast Histopathology.
Proceedings of the Deep Learning in Medical Image Analysis and Multimodal Learning for Clinical Decision Support, 2017

Accurate Lung Segmentation via Network-Wise Training of Convolutional Networks.
Proceedings of the Deep Learning in Medical Image Analysis and Multimodal Learning for Clinical Decision Support, 2017

2016
A robust support vector regression with a linear-log concave loss function.
J. Oper. Res. Soc., 2016

Collaborative crystal structure prediction.
Expert Syst. Appl., 2016

A Unified Framework for Tumor Proliferation Score Prediction in Breast Histopathology.
CoRR, 2016

Semantic Noise Modeling for Better Representation Learning.
CoRR, 2016

Scale-Invariant Feature Learning using Deconvolutional Neural Networks for Weakly-Supervised Semantic Segmentation.
CoRR, 2016

Self-Transfer Learning for Fully Weakly Supervised Object Localization.
CoRR, 2016

Self-Transfer Learning for Weakly Supervised Lesion Localization.
Proceedings of the Medical Image Computing and Computer-Assisted Intervention - MICCAI 2016, 2016

A novel approach for tuberculosis screening based on deep convolutional neural networks.
Proceedings of the Medical Imaging 2016: Computer-Aided Diagnosis, San Diego, California, United States, 27 February, 2016

2015
Robust kernel-based regression with bounded influence for outliers.
J. Oper. Res. Soc., 2015


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