Simple numpy-based implementation of SpecAugment

Using Convolutional Neural Networks to create image classifiers [ cats + dogs & cats + dogs + lions + tigers ]

Notebook for Data Augmentation

This repository is related to the paper "Data augmentation and hierarchical classification to support the diagnosis of neuropathies based on time series analysis".

This application is made to perform data augmentation with an easy to use interface. You are provided with various traditional data augmentation techniques like rotation, crop, zooming, etc.

Disease - Symptom Dataset Cleaning and Augmenting Process

Transfer learning with VGG16 and using data augmentation.

This repository will encompass concepts that I will be learning throughout my deep learning studies.

Neural networks for algae identification

Emotion detection from small images using CNN

•Developed a Convolution Neural Network (CNN) model from scratch for detecting Covid-19 using chest X-Ray images •Achieved highest accuracy of 92.24% and 96.66% on training and testing set post data augmentation techniques

Face Mask Detection Competition on Kaggle

Curso Convolutional Neural Networks in TensorFlow disponibilizado pela DeepLearning.AI e ministrado através do Coursera

Brain tumor detection using Deep learning in MRI images

This classifier uses Convolutional Neural Networks for the Kaggle problem to classify images as cats or dogs.

Art Signature Authentication is a project that uses machine learning to verify artist signatures with high accuracy (99.46%). It addresses art forgery challenges, providing a scalable, automated solution to ensure trust and transparency in the art market. 🎨✨

Development of robust classifiers which can distinguish between images of different types of vegetables, while also correctly labeling images that do not contain any one type of vegetable as noise.