487 datasets found

The dataset used in this paper is a collection of neural network acceleration with TensorFlow and FPGA.

PrivCirNet: Efficient Private Inference via Block Circulant Transformation

Synthetic data generated from a conditional Gaussian distribution to establish a reference characterizing the robustness-accuracy tradeoff based on the Bayes optimal linear...

The dataset used in this paper is a pre-trained DNN trained on the Cifar10 and Cifar100 datasets.

The MNIST dataset is used to demonstrate the clustering capability of the proposed group-sparse autoencoder.

The dataset used in the paper is ResNet-20, a deep convolutional neural network for image classification.

q-Space Deep Learning for Twelve-Fold Shorter and Model-Free Diffusion MRI Scans.

DELIMIT is a framework extension for deep learning in dif-fusion imaging, which extends the basic framework PyTorch towards spherical signals.

A deep learning and IoT based computer vision system to process computer vision and natural language in real time in order to address the safety and security of production sites...

The dataset used in the paper to prove the representation defects of a cascaded convolutional decoder network in frequency representation.

Fetal brain MRI dataset for automatic linear measurements of the fetal brain

HetACUMN consists of two tasks: variational image reconstruction and conditional pose prediction. The variational image reconstruction task follows the standard self-supervised...

Deep convolutional neural networks have dominated the pattern recognition scene by providing much more accurate solutions in computer vision problems such as object recognition...

Medical head CT-scan imaging has been successfully combined with deep learning for medical diagnostics of head diseases and lesions. A custom dataset was used for this study.

This dataset is used to evaluate CNNs and human observers on images with a texture-shape cue conflict.

The proposed interpretable CADx framework is devised to provide the diagnostic decision with interpretation in terms of medical descriptions (BI-RADS).

Moving Infants In RGB-D (MINI-RGBD) dataset is used for CP prediction. The dataset contains 12 sequences of real infant movements.

The dataset used for training deep neural networks using half-precision floating point numbers.

Binary neural networks have attracted numerous attention in recent years. However, mainly due to the information loss stemming from the biased binarization, how to preserve the...

The proposed framework generates a unique set of context-dependent filters based on the input image, and combines them with max-pooling to produce transformation-invariant...