research
∙
11/24/2022
Non-inferiority of Deep Learning Model to Segment Acute Stroke on Non-contrast CT Compared to Neuroradiologists
Purpose: To develop a deep learning model to segment the acute ischemic ...
share
research
∙
09/26/2022
Evaluation of Medical Image Segmentation Models for Uncertain, Small or Empty Reference Annotations
Performance metrics for medical image segmentation models are used to me...
research
∙
07/27/2022
ALBench: A Framework for Evaluating Active Learning in Object Detection
Active learning is an important technology for automated machine learnin...
research
∙
11/19/2021
YMIR: A Rapid Data-centric Development Platform for Vision Applications
This paper introduces an open source platform for rapid development of c...
research
∙
10/16/2019
Generative Modeling for Small-Data Object Detection
This paper explores object detection in the small data regime, where onl...
research
∙
08/12/2019
Feature Partitioning for Efficient Multi-Task Architectures
Multi-task learning holds the promise of less data, parameters, and time...
research
∙
12/18/2018
Composing Text and Image for Image Retrieval - An Empirical Odyssey
In this paper, we study the task of image retrieval, where the input que...
research
∙
12/01/2018
Vision-Based Gait Analysis for Senior Care
As the senior population rapidly increases, it is challenging yet crucia...
research
∙
12/01/2018
NOTE-RCNN: NOise Tolerant Ensemble RCNN for Semi-Supervised Object Detection
The labeling cost of large number of bounding boxes is one of the main c...
research
∙
06/05/2018
Focal Visual-Text Attention for Visual Question Answering
Recent insights on language and vision with neural networks have been su...
research
∙
03/29/2018
Iterative Visual Reasoning Beyond Convolutions
We present a novel framework for iterative visual reasoning. Our framewo...
research
∙
03/10/2018
Attention-based Graph Neural Network for Semi-supervised Learning
Recently popularized graph neural networks achieve the state-of-the-art ...
research
∙
12/14/2017
MentorNet: Regularizing Very Deep Neural Networks on Corrupted Labels
Recent studies have discovered that deep networks are capable of memoriz...
research
∙
12/02/2017
Progressive Neural Architecture Search
We propose a method for learning CNN structures that is more efficient t...
research
∙
11/17/2017
Thoracic Disease Identification and Localization with Limited Supervision
Accurate identification and localization of abnormalities from radiology...
research
∙
04/12/2017
Deep Reinforcement Learning-based Image Captioning with Embedding Reward
Image captioning is a challenging problem owing to the complexity in und...
research
∙
03/07/2017
Learning from Noisy Labels with Distillation
The ability of learning from noisy labels is very useful in many visual ...
research
∙
11/21/2016
Dense Captioning with Joint Inference and Visual Context
Dense captioning is a newly emerging computer vision topic for understan...
research
∙
02/23/2016
Visual Genome: Connecting Language and Vision Using Crowdsourced Dense Image Annotations
Despite progress in perceptual tasks such as image classification, compu...
research
∙
02/10/2015
Multi-view Face Detection Using Deep Convolutional Neural Networks
In this paper we consider the problem of multi-view face detection. Whil...
research
∙
11/21/2014