986 citations · 1.1k across the 22 of their papers we have counts for
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Progressive Transformation Learning for Leveraging Virtual Images in Training
Yi-Ting Shen, Hyungtae Lee, Heesung Kwon +1
To effectively interrogate UAV-based images for detecting objects of interest, such as humans, it is essential to acquire large-scale UAV-based datasets that include human instance…
Negative Samples are at Large: Leveraging Hard-distance Elastic Loss for Re-identification
Hyungtae Lee, Sungmin Eum, Heesung Kwon
We present a Momentum Re-identification (MoReID) framework that can leverage a very large number of negative samples in training for general re-identification task. The design of t…
Exploring Cross-Domain Pretrained Model for Hyperspectral Image Classification
Hyungtae Lee, Sungmin Eum, Heesung Kwon
A pretrain-finetune strategy is widely used to reduce the overfitting that can occur when data is insufficient for CNN training. First few layers of a CNN pretrained on a large-sca…
DBF: Dynamic Belief Fusion for Combining Multiple Object Detectors
Hyungtae Lee, Heesung Kwon
In this paper, we propose a novel and highly practical score-level fusion approach called dynamic belief fusion (DBF) that directly integrates inference scores of individual detect…
Self-supervised Contrastive Learning for Cross-domain Hyperspectral Image Representation
Hyungtae Lee, Heesung Kwon
Recently, self-supervised learning has attracted attention due to its remarkable ability to acquire meaningful representations for classification tasks without using semantic label…