Home /
Research
Showing 271 - 276 / 897
Ranking Deep Learning Generalization using Label Variation in Latent Geometry Graphs
CarlosLassance, LouisBéthune, MyriamBontonou....
Published date-11/25/2020
Measuring the generalization performance of a Deep Neural Network (DNN) without relying on a validation set is a difficult task. In this work, we propose exploiting Latent Geometry Graphs (LGGs) …
BinPlay: A Binary Latent Autoencoder for Generative Replay Continual Learning
KamilDeja, PawełWawrzyński, DanielMarczak....
Published date-11/25/2020
ContinualLearning
We introduce a binary latent space autoencoder architecture to rehearse training samples for the continual learning of neural networks. The ability to extend the knowledge of a model with new …
Physics-informed neural networks for myocardial perfusion MRI quantification
RudolfL.M.vanHerten, AmedeoChiribiri, MarcelBreeuwer....
Published date-11/25/2020
Tracer-kinetic models allow for the quantification of kinetic parameters such as blood flow from dynamic contrast-enhanced magnetic resonance (MR) images. Fitting the observed data with multi-compartment exchange models is desirable, …
The Unreasonable Effectiveness of Encoder-Decoder Networks for Retinal Vessel Segmentation
BjörnBrowatzki, Jörn-PhilippLies, ChristianWallraven....
Published date-11/25/2020
RetinalVesselSegmentation
We propose an encoder-decoder framework for the segmentation of blood vessels in retinal images that relies on the extraction of large-scale patches at multiple image-scales during training. Experiments on three …
Generalized Focal Loss V2: Learning Reliable Localization Quality Estimation for Dense Object Detection
XiangLi, WenhaiWang, XiaolinHu....
Published date-11/25/2020
DenseObjectDetection, ObjectClassification, ObjectDetection
Localization Quality Estimation (LQE) is crucial and popular in the recent advancement of dense object detectors since it can provide accurate ranking scores that benefit the Non-Maximum Suppression processing and …
TLeague: A Framework for Competitive Self-Play based Distributed Multi-Agent Reinforcement Learning
PengSun, JiechaoXiong, LeiHan....
Published date-11/25/2020
Dota2, Multi-agentReinforcementLearning, Starcraft, StarcraftII
Competitive Self-Play (CSP) based Multi-Agent Reinforcement Learning (MARL) has shown phenomenal breakthroughs recently. Strong AIs are achieved for several benchmarks, including Dota 2, Glory of Kings, Quake III, StarCraft II, …