189 citations · 213 across the 14 of their papers we have counts for
14 papers
Cloud-Based Deep Learning: End-To-End Full-Stack Handwritten Digit Recognition
Ruida Zeng, Aadarsh Jha, Ashwin Kumar +1
Herein, we present Stratus, an end-to-end full-stack deep learning application deployed on the cloud. The rise of productionized deep learning necessitates infrastructure in the cl…
Compound Figure Separation of Biomedical Images: Mining Large Datasets for Self-supervised Learning
Tianyuan Yao, Chang Qu, Jun Long +13
With the rapid development of self-supervised learning (e.g., contrastive learning), the importance of having large-scale images (even without annotations) for training a more gene…
Glo-In-One: Holistic Glomerular Detection, Segmentation, and Lesion Characterization with Large-scale Web Image Mining
Tianyuan Yao, Yuzhe Lu, Jun Long +6
The quantitative detection, segmentation, and characterization of glomeruli from high-resolution whole slide imaging (WSI) play essential roles in the computer-assisted diagnosis a…
Compound Figure Separation of Biomedical Images with Side Loss
Tianyuan Yao, Chang Qu, Quan Liu +11
Unsupervised learning algorithms (e.g., self-supervised learning, auto-encoder, contrastive learning) allow deep learning models to learn effective image representations from large…
VoxelEmbed: 3D Instance Segmentation and Tracking with Voxel Embedding based Deep Learning
Mengyang Zhao, Quan Liu, Aadarsh Jha +6
Recent advances in bioimaging have provided scientists a superior high spatial-temporal resolution to observe dynamics of living cells as 3D volumetric videos. Unfortunately, the 3…
SimTriplet: Simple Triplet Representation Learning with a Single GPU
Quan Liu, Peter C. Louis, Yuzhe Lu +9
Contrastive learning is a key technique of modern self-supervised learning. The broader accessibility of earlier approaches is hindered by the need of heavy computational resources…