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20162022
most citedImproving Camouflaged Object Detection with the Uncertainty of Pseudo-edge Labels

23 citations · 69 across the 10 of their papers we have counts for

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Showing 2019Show all

6 papers · 1 filter

eess.IV2019

GAN-based Multiple Adjacent Brain MRI Slice Reconstruction for Unsupervised Alzheimer's Disease Diagnosis

Changhee Han, Leonardo Rundo, Kohei Murao +5

Unsupervised learning can discover various unseen diseases, relying on large-scale unannotated medical images of healthy subjects. Towards this, unsupervised methods reconstruct a…

cs.CV201911 cited

Learning More with Less: GAN-based Medical Image Augmentation

Changhee Han, Kohei Murao, Shin'ichi Satoh +1

Convolutional Neural Network (CNN)-based accurate prediction typically requires large-scale annotated training data. In Medical Imaging, however, both obtaining medical data and an…

cs.CV2019

Beyond Intra-modality: A Survey of Heterogeneous Person Re-identification

Zheng Wang, Zhixiang Wang, Yinqiang Zheng +3

An efficient and effective person re-identification (ReID) system relieves the users from painful and boring video watching and accelerates the process of video analysis. Recently,…

cs.CV2019

DotSCN: Group Re-identification via Domain-Transferred Single and Couple Representation Learning

Ziling Huang, Zheng Wang, Chung-Chi Tsai +2

Group re-identification (G-ReID) is an important yet less-studied task. Its challenges not only lie in appearance changes of individuals which have been well-investigated in genera…

cs.CV2019

Illumination-Adaptive Person Re-identification

Zelong Zeng, Zhixiang Wang, Zheng Wang +3

Most person re-identification (ReID) approaches assume that person images are captured under relatively similar illumination conditions. In reality, long-term person retrieval is c…

cs.CV2019

Learning More with Less: Conditional PGGAN-based Data Augmentation for Brain Metastases Detection Using Highly-Rough Annotation on MR Images

Changhee Han, Kohei Murao, Tomoyuki Noguchi +5

Accurate Computer-Assisted Diagnosis, associated with proper data wrangling, can alleviate the risk of overlooking the diagnosis in a clinical environment. Towards this, as a Data…