Publication

Scale-Aware Test-Time Click Adaptation for Pulmonary Nodule and Mass Segmentation

Related publications (46)

About
Privacy
Disclaimer

Graph Chatbot

Chat with Graph Search

Ask any question about EPFL courses, lectures, exercises, research, news, etc. or try the example questions below.

DISCLAIMER: The Graph Chatbot is not programmed to provide explicit or categorical answers to your questions. Rather, it transforms your questions into API requests that are distributed across the various IT services officially administered by EPFL. Its purpose is solely to collect and recommend relevant references to content that you can explore to help you answer your questions.

Scale-Aware Test-Time Click Adaptation for Pulmonary Nodule and Mass Segmentation

Graph Chatbot

Chat with Graph Search

DermoNet: Densely Linked Convolutional Neural Network for Efficient Skin Lesion Segmentation

dhSegment: A generic deep-learning approach for document segmentation

Large-Scale Image Segmentation with Convolutional Networks

Large-Scale Image Segmentation with Convolutional Networks

Webly Supervised Semantic Segmentation

Color Representation in Deep Neural Networks

Fast and Robust Segmentation of the Striatum Using Deep Convolutional Neural Networks

Word Sequence Modeling using Deep Learning

IMAGE AESTHETIC PREDICTORS BASED ON WEIGHTED CNNS

From Image-level to Pixel-level Labeling with Convolutional Networks

Color Representation in Deep Neural Networks

dhSegment: A generic deep-learning approach for document segmentation

Large-Scale Image Segmentation with Convolutional Networks

Fast and Robust Segmentation of the Striatum Using Deep Convolutional Neural Networks

Large-Scale Image Segmentation with Convolutional Networks

From Image-level to Pixel-level Labeling with Convolutional Networks

Word Sequence Modeling using Deep Learning

DermoNet: Densely Linked Convolutional Neural Network for Efficient Skin Lesion Segmentation

Webly Supervised Semantic Segmentation

IMAGE AESTHETIC PREDICTORS BASED ON WEIGHTED CNNS