1 code implementation • 22 Sep 2021 • Zhenzhen Wang, Carla Saoud, Sintawat Wangsiricharoen, Aaron W. James, Aleksander S. Popel, Jeremias Sulam
Annotating cancerous regions in whole-slide images (WSIs) of pathology samples plays a critical role in clinical diagnosis, biomedical research, and machine learning algorithms development.
no code implementations • 30 Sep 2020 • Zhenzhen Wang, Chunyan Xu, Yap-Peng Tan, Junsong Yuan
In this paper, the attention-aware noisy label learning approach ($A^2NL$) is proposed to improve the discriminative capability of the network trained on datasets with potential label noise.
no code implementations • 10 Aug 2020 • Zhenzhen Wang, Weixiang Hong, Junsong Yuan
Deep hashing has shown promising results in image retrieval and recognition.
no code implementations • CVPR 2018 • Weixiang Hong, Zhenzhen Wang, Ming Yang, Junsong Yuan
In recent years, deep neural nets have triumphed over many computer vision problems, including semantic segmentation, which is a critical task in emerging autonomous driving and medical image diagnostics applications.
no code implementations • ICCV 2017 • Tan Yu, Zhenzhen Wang, Junsong Yuan
Most of current visual search systems focus on image-to-image (point-to-point) search such as image and object retrieval.
no code implementations • ICCV 2015 • Zhenzhen Wang, Xiao-Tong Yuan, Qingshan Liu, Shuicheng Yan
In this paper, we present a concise framework to approximately construct feature maps for nonlinear additive kernels such as the Intersection, Hellinger's, and Chi^2 kernels.