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Brazilian PUC-PR
The dataset used for the research on writer-independent feature learning for offline signature verification using deep convolutional neural networks. -
Training dataset generation for bridge game registration
The proposed method of automatic dataset generation for cards detection and classification makes it possible to obtain any number of images of any size, which can be used to... -
IMAGENET ILSVRC2012
The dataset used for image recognition using deep convolutional neural networks. -
Dogs vs Cats
The dataset used for image recognition using deep convolutional neural networks. -
3D MRI brain tumor segmentation using deep convolutional neural networks
3D MRI brain tumor segmentation using deep convolutional neural networks. -
ECOVNet: An Ensemble of Deep Convolutional Neural Networks for COVID-19 Detec...
The proposed architecture uses a CNN-based approach to detect COVID-19 from chest X-ray images. The dataset is used to train and evaluate the proposed model. -
Churn analysis using deep convolutional neural networks and autoencoders
Customer temporal behavioral data represented as images to perform churn prediction by leveraging deep learning architectures prominent in image classification. -
Cell2cell Dataset
The Cell2cell dataset is a standard telecom dataset used for churn prediction. It has 34 features and no missing values. -
Orange Dataset
The Orange dataset is a standard telecom dataset used for churn prediction. It has 18 features with missing values and 5 features have just a single value. -
Transfer Learning and Meta Classification Based Deep Churn Prediction System ...
A churn prediction system guides telecom service providers to reduce revenue loss. However, the development of churn prediction system for a telecom industry is a challenging... -
JutePestDetect
A comprehensive jute pest dataset consisting of 17 distinct pest classes, facilitating a more thorough analysis. -
Hardware-Oriented Acceleration of Deep Convolutional Neural Networks
To address memory and computation resource limitations for hardware-oriented acceleration of deep convolutional neural networks (CNNs), we present a compu-tation flow, stacked...
