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Found 5 papers, 1 papers with code
Pre-training of Lightweight Vision Transformers on Small Datasets with Minimally Scaled Images
Can a lightweight Vision Transformer (ViT) match or exceed the performance of Convolutional Neural Networks (CNNs) like ResNet on small datasets with small image resolutions?
Ranked #105 on
Image Classification
on CIFAR-10
A deep convolutional neural network model to classify heartbeats
The CNN was trained using the augmented data and achieved an accuracy of 94. 03% and 93. 47% in the diagnostic classification of heartbeats in original and noise free ECGs, respectively.
Application of deep convolutional neural network for automated detection of myocardial infarction using ecg signals
In this study, we implemented a convolutional neural network (CNN) algorithm for the automated detection of a normal and MI ECG beats (with noise and without noise).
Segmentation of optic disc, fovea and retinal vasculature using a single convolutional neural network
We have developed and trained a convolutional neural network to automatically and simultaneously segment optic disc, fovea and blood vessels.
Active spline model: A shape based model-interactive segmentation
Rarely in literature a method of segmentation cares for the edit after the algorithm delivers.
