research
∙
03/11/2022
Spatial Consistency Loss for Training Multi-Label Classifiers from Single-Label Annotations
As natural images usually contain multiple objects, multi-label image cl...
share
research
∙
10/26/2020
Optimization for Medical Image Segmentation: Theory and Practice when evaluating with Dice Score or Jaccard Index
In many medical imaging and classical computer vision tasks, the Dice sc...
research
∙
05/21/2020
AOWS: Adaptive and optimal network width search with latency constraints
Neural architecture search (NAS) approaches aim at automatically finding...
research
∙
11/25/2019
Discriminative training of conditional random fields with probably submodular constraints
Problems of segmentation, denoising, registration and 3D reconstruction ...
research
∙
11/05/2019
Optimizing the Dice Score and Jaccard Index for Medical Image Segmentation: Theory Practice
The Dice score and Jaccard index are commonly used metrics for the evalu...
research
∙
07/23/2019
Adaptive Compression-based Lifelong Learning
The problem of a deep learning model losing performance on a previously ...
research
∙
03/11/2019
Generating superpixels using deep image representations
Superpixel algorithms are a common pre-processing step for computer visi...
research
∙
02/14/2019
MultiGrain: a unified image embedding for classes and instances
MultiGrain is a network architecture producing compact vector representa...
research
∙
09/06/2018
Yes, IoU loss is submodular - as a function of the mispredictions
This note is a response to [7] in which it is claimed that [13, Proposit...
research
∙
07/17/2018
Supermodular Locality Sensitive Hashes
In this work, we show deep connections between Locality Sensitive Hashab...
research
∙
06/07/2018
Efficient semantic image segmentation with superpixel pooling
In this work, we evaluate the use of superpixel pooling layers in deep n...
research
∙
10/18/2017
Stochastic Weighted Function Norm Regularization
Deep neural networks (DNNs) have become increasingly important due to th...
research
∙
05/24/2017