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COVID-VIT: Classification of Covid-19 from CT chest images based on vision tr...
COVID-19 classification from CT chest images based on vision transformer models -
Towards Principled Causal Effect Estimation by Deep Identifiable Models
The dataset used in the paper for causal effect estimation using Intact-VAE. -
Automating sleep scoring in mice with deep learning
Reliable automation of the labor-intensive manual task of scoring animal sleep can facilitate the analysis of long-term sleep studies. -
ImageNet and Wiki103
The dataset used in the paper is ImageNet and Wiki103. -
ImageNet + ResNet101 and WT103 + TransformerXL models
The dataset used in the paper is ImageNet + ResNet101 and WT103 + TransformerXL models. -
Tied Block Convolution: Leaner and Better CNNs with Shared Thinner Filters
Convolution is the main building block of convolutional neural networks (CNN). We observe that an optimized CNN often has highly correlated filters as the number of channels... -
Deep Geometric Moment (DGM) Model
The proposed model consists of three components: 1) Coordinate base computation: uses a 2D coordinate grid as input and generates the bases, 2) Image feature computation:... -
Improving Shape Awareness and Interpretability in Deep Networks Using Geometr...
Deep networks for image classification often rely more on texture information than object shape. This paper presents a deep-learning model inspired by geometric moments, a... -
COVID-19 detection using chest X-rays: is lung segmentation important for gen...
A large DNN, containing 3 stacked modules. The segmentation module is an U-Net, trained beforehand to receive X-rays and output segmentation masks. -
LSUN Bedrooms
The dataset used in the paper is the LSUN bedrooms dataset, a large-scale image dataset. -
Adam: A method for stochastic optimization
This dataset is used to test the robustness of watermarking methods against adaptive attacks. -
AACHER: Assorted Actor-Critic Deep Reinforcement Learning with Hindsight Expe...
Actor-Critic Deep Reinforcement Learning with Hindsight Experience Replay -
Transformer-based Map Matching Model with Limited Ground-Truth Data using Tra...
This study proposes a framework for developing a novel deep learning-based map-matching model in the limited ground-truth data environment. -
Benchmarking of Deep Learning models on 2D Laminar Flow behind Cylinder
The dataset is used for benchmarking deep learning models on 2D laminar flow behind cylinder -
Vector Field Network (VFN) for De Novo Protein Design
The dataset used in the paper for de novo protein design using geometric vector field networks. -
Segmentation dataset for jet flames
The dataset used for training and testing the UNet and Attention UNet models for segmentation of radiation zones within the jet flames. -
Validation dataset for Pix2Pix model
The dataset used for training and testing the Pix2Pix model for generating artificial IR images from visible ones. -
ACDC Dataset
The ACDC dataset is a large-scale dataset containing images of urban scenes under different weather conditions. -
Dual Policy Distillation
The dataset used in the paper is a continuous control task dataset.
