50 datasets found

A dataset with 1,127 images of pyrolyzed smartphone components, used to train and assess a VGG-16 image classification model for sorting waste electrical and electronic...

The dataset used in this paper is the SqueezeNet v1.1 and ZynqNet CNNs, which are characterized by small model size and limited computational requirements.

Residual and plain convolutional neural networks for 3d brain mri classification

The dataset used in the paper is LeNet, a convolutional neural network for image classification.

This paper proposes a convolutional neural network hardware accelerator based on field programmable logic gate array (FPGA).

The dataset used in this paper is a benchmark suite for Convolutional Neural Networks.

The dataset used in this paper is a modified version of the Caffe CNN framework with support for FPGA implementations.

The dataset used in the paper is the ResNet-50 dataset, a convolutional neural network model.

The dataset used in the paper is the VGG-11 dataset, a convolutional neural network model.

The dataset used in the paper is the AlexNet dataset, which contains 60,000 32x32 color images in 10 classes, with 6,000 images per class.

The dataset used in this paper is a convolutional neural network problem with 60,000 training examples and 10,000 testing examples.

The dataset used in the paper is a generic framework for convolution on arbitrary structures, which includes grid convolutions and graph convolutions.

A survey of the foundations, selected improvements, and some current applications of Deep Convolutional Neural Networks (CNNs).

To address memory and computation resource limitations for hardware-oriented acceleration of deep convolutional neural networks (CNNs), we present a compu-tation flow, stacked...

NESTA: a specialized neural processing engine designed for executing learning models in which filter-weights, input-data, and applied biases are expressed in fixed-point format.

The dataset used for training and testing the SediNet model for PSD determination.

The dataset used for training and testing the GRAINet model for PSD determination.

The dataset used for training and testing the ConvNet model for PSD determination.

The dataset used in this paper is a Bottleneck layer, which is a type of convolutional neural network layer. The dataset is used to evaluate the performance of the proposed...

The dataset used in this paper is a binary convolution dataset, where the inputs are binary images and the outputs are the results of the convolution operation.