Search Results for author:
Found 6 papers, 2 papers with code
End-to-end Learning for Image-based Detection of Molecular Alterations in Digital Pathology
We propose a novel learning pipeline for WSI classification that is trainable end-to-end and does not require any auxiliary annotations.
Large Scale Joint Semantic Re-Localisation and Scene Understanding via Globally Unique Instance Coordinate Regression
We obtain smaller mean distance and angular errors than state-of-the-art 6-DoF pose estimation algorithms based on direct pose regression and pose estimation from scene coordinates on all datasets.
Detect-to-Retrieve: Efficient Regional Aggregation for Image Search
Then, we demonstrate how a trained landmark detector, using our new dataset, can be leveraged to index image regions and improve retrieval accuracy while being much more efficient than existing regional methods.
Comparative evaluation of instrument segmentation and tracking methods in minimally invasive surgery
The paper presents a comparative validation study of different vision-based methods for instrument segmentation and tracking in the context of robotic as well as conventional laparoscopic surgery.
MultiNet: Real-time Joint Semantic Reasoning for Autonomous Driving
While most approaches to semantic reasoning have focused on improving performance, in this paper we argue that computational times are very important in order to enable real time applications such as autonomous driving.
Pixel-wise Segmentation of Street with Neural Networks
Pixel-wise street segmentation of photographs taken from a drivers perspective is important for self-driving cars and can also support other object recognition tasks.
