Exploring deep learning on Cooley
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Updated
Dec 1, 2017 - Jupyter Notebook
Exploring deep learning on Cooley
something new
Partition input image into multiple augmented images
A technique to increase the variety and robustness of the data by changing a few characteristic of the image
This repository contains code and resources for performing object localization and classification using a single network on an Augmented MNIST dataset.
Few NLP augmentation techniques: synonym/antonym and back translation.
Attempt to classify images of 10 fast foods by KNN, ANN and CNN.
A library that includes pure TF/Keras preprocessing and augmentation layers, providing support for various data types such as images, labels, bounding boxes, segmentation masks, and more.
Evaluating the impact of the Easy Data Augmentation (EDA) framework on the performance of various text classification models.
Sentiment Analysis On DeepSentiPers. With text augmentation and Flask-based API.
This repository contains my project for computer vision.
Chinese NLP Data Augmentation, for simplicity!!!
Expanding limited datasets in CNN-LSTM to improve accuracy.
In this project I will be utilizing the Brain Tumor Classification dataset, which contains a variety of brain imaging scans that are labeled as either tumorous or non-tumorous. Our primary objective is to develop a deep learning model that can accurately recognize and categorize these images based on their classification labels.
An images augmentation program for yolo with labels auto adaptive
Classification of defective lemons by augmenting images with GAN variations.
Synthetic dataset for Object Detection
This repository contains the code of our published work in IEEE JBHI. Our main objective was to demonstrate the feasibility of the use of synthetic data to effectively train Machine Learning algorithms, prooving that it benefits classification performance most of the times.
Fast Augmentation library for NLP
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