84 citations · 272 across the 15 of their papers we have counts for
11 papers · 1 filter
A Location-Sensitive Local Prototype Network for Few-Shot Medical Image Segmentation
Qinji Yu, Kang Dang, Nima Tajbakhsh +2
Despite the tremendous success of deep neural networks in medical image segmentation, they typically require a large amount of costly, expert-level annotated data. Few-shot segment…
MultiMix: Sparingly Supervised, Extreme Multitask Learning From Medical Images
Ayaan Haque, Abdullah-Al-Zubaer Imran, Adam Wang +1
Semi-supervised learning via learning from limited quantities of labeled data has been investigated as an alternative to supervised counterparts. Maximizing knowledge gains from co…
End-to-End Trainable Deep Active Contour Models for Automated Image Segmentation: Delineating Buildings in Aerial Imagery
Ali Hatamizadeh, Debleena Sengupta, Demetri Terzopoulos
The automated segmentation of buildings in remote sensing imagery is a challenging task that requires the accurate delineation of multiple building instances over typically large i…
Image Segmentation Using Deep Learning: A Survey
Shervin Minaee, Yuri Boykov, Fatih Porikli +3
Image segmentation is a key topic in image processing and computer vision with applications such as scene understanding, medical image analysis, robotic perception, video surveilla…
End-to-End Deep Convolutional Active Contours for Image Segmentation
Ali Hatamizadeh, Debleena Sengupta, Demetri Terzopoulos
The Active Contour Model (ACM) is a standard image analysis technique whose numerous variants have attracted an enormous amount of research attention across multiple fields. Incorr…
End-to-End Boundary Aware Networks for Medical Image Segmentation
Ali Hatamizadeh, Demetri Terzopoulos, Andriy Myronenko
Fully convolutional neural networks (CNNs) have proven to be effective at representing and classifying textural information, thus transforming image intensity into output class mas…
Automatic Segmentation of Pulmonary Lobes Using a Progressive Dense V-Network
Abdullah-Al-Zubaer Imran, Ali Hatamizadeh, Shilpa P. Ananth +3
Reliable and automatic segmentation of lung lobes is important for diagnosis, assessment, and quantification of pulmonary diseases. The existing techniques are prohibitively slow,…
Surrogate Supervision for Medical Image Analysis: Effective Deep Learning From Limited Quantities of Labeled Data
Nima Tajbakhsh, Yufei Hu, Junli Cao +6
We investigate the effectiveness of a simple solution to the common problem of deep learning in medical image analysis with limited quantities of labeled training data. The underly…
Learning to Sketch with Deep Q Networks and Demonstrated Strokes
Tao Zhou, Chen Fang, Zhaowen Wang +5
Doodling is a useful and common intelligent skill that people can learn and master. In this work, we propose a two-stage learning framework to teach a machine to doodle in a simula…
Attention-based Natural Language Person Retrieval
Tao Zhou, Muhao Chen, Jie Yu +1
Following the recent progress in image classification and captioning using deep learning, we develop a novel natural language person retrieval system based on an attention mechanis…
Configurable 3D Scene Synthesis and 2D Image Rendering with Per-Pixel Ground Truth using Stochastic Grammars
Chenfanfu Jiang, Siyuan Qi, Yixin Zhu +5
We propose a systematic learning-based approach to the generation of massive quantities of synthetic 3D scenes and arbitrary numbers of photorealistic 2D images thereof, with assoc…