Search Results for author:
Found 4 papers, 2 papers with code
Learning to Predict RNA Sequence Expressions from Whole Slide Images with Applications for Search and Classification
In this paper, we propose tRNAsfomer, an attention-based topology that can learn both to predict the bulk RNA-seq from an image and represent the whole slide image of a glass slide simultaneously.
Offline versus Online Triplet Mining based on Extreme Distances of Histopathology Patches
We analyze the effect of offline and online triplet mining for colorectal cancer (CRC) histopathology dataset containing 100, 000 patches.
Dimensionality Reduction
Histopathological Image Classification
+1
Supervision and Source Domain Impact on Representation Learning: A Histopathology Case Study
In this work, we explored the performance of a deep neural network and triplet loss in the area of representation learning.
Pan-Cancer Diagnostic Consensus Through Searching Archival Histopathology Images Using Artificial Intelligence
The emergence of digital pathology has opened new horizons for histopathology and cytology.
