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Most implemented papers

Continual Learning with Deep Generative Replay

ContinualAI/avalanche NeurIPS 2017

Attempts to train a comprehensive artificial intelligence capable of solving multiple tasks have been impeded by a chronic problem called catastrophic forgetting.

Model-Free Episodic Control

ShibiHe/Model-Free-Episodic-Control 14 Jun 2016

State of the art deep reinforcement learning algorithms take many millions of interactions to attain human-level performance.

Extended 2D Consensus Hippocampus Segmentation

dscarmo/e2dhipseg 12 Feb 2019

Segmentation done by experts is considered to be a gold-standard when evaluating automated methods, buts it is a time consuming and arduos task, requiring specialized personnel.

Enforcing temporal consistency in Deep Learning segmentation of brain MR images

bigmb/Unet-Segmentation-Pytorch-Nest-of-Unets 13 Jun 2019

Proposed CNN based segmentation approaches demonstrate how 2D segmentation using prior slices can provide similar results to 3D segmentation while maintaining good continuity in the 3D dimension and improved speed.

Hippocampus Segmentation on Epilepsy and Alzheimer's Disease Studies with Multiple Convolutional Neural Networks

dscarmo/e2dhipseg 14 Jan 2020

We test this methodology alongside other recent deep learning methods, in two domains: The HarP test set and an in-house epilepsy dataset, containing hippocampus resections, named HCUnicamp.

3D-UCaps: 3D Capsules Unet for Volumetric Image Segmentation

vinairesearch/3d-ucaps 16 Mar 2022

Medical image segmentation has been so far achieving promising results with Convolutional Neural Networks (CNNs).

Deep Direct Discriminative Decoders for High-dimensional Time-series Data Analysis

mrrezaeiuoft/deep_direct_discriminative_decoder-d4- 22 May 2022

The D4 brings deep neural networks' expressiveness and scalability to the SSM formulation letting us build a novel solution that efficiently estimates the underlying state processes through high-dimensional observation signal.

Med-NCA: Robust and Lightweight Segmentation with Neural Cellular Automata

meclabtuda/med-nca 7 Feb 2023

Access to the proper infrastructure is critical when performing medical image segmentation with Deep Learning.

Clique topology reveals intrinsic geometric structure in neural correlations

nebneuron/clique-top 22 Feb 2015

Detecting meaningful structure in neural activity and connectivity data is challenging in the presence of hidden nonlinearities, where traditional eigenvalue-based methods may be misleading.

Alzheimer's Disease Diagnostics by a Deeply Supervised Adaptable 3D Convolutional Network

ehosseiniasl/3d-convolutional-network 2 Jul 2016

The 3D-CNN is built upon a 3D convolutional autoencoder, which is pre-trained to capture anatomical shape variations in structural brain MRI scans.