An images augmentation program for yolo with labels auto adaptive

Project about developing a model that can detect multiple cards and identify their suit and rank. Includes multiple models, own created dataset, utility functions, presentations, research paper and live demo application. Course Deep Learning, FMI, 2024.

python based simple Tools for Neural network training for image classifier, (dir based image converter, Normalization, Blur Augmentation, Multiple Model Evaluate )

stain augmentation method based on stainmix up using multiple known stain matrices.

A website that displays audio and its spectrogram when an augmentation/operation is applied to the audio.

Transfer Learning with Augmentation on an EfficientNetV2L pretrained on the Imagenet dataset

A utility script to transform bounding boxes along with the object image.

RDF Graph Augmentation with BERT-based Contextual Embeddings

Udacity CarND Behavioral Cloning Project https://www.udacity.com/drive

A demo to increase the dataset size for deep learning using augmentation techniques such as rotation, width_shift, height_shift, shear, zoom, horizontal etc.

Augmentation with Hydra Config

Detect 6 class of VF using CNN

Audio preprocessing tool for signal processing and machine learning applications.

Fast image augmentation library and an easy-to-use wrapper around other libraries. Documentation: https://albumentations.ai/docs/ Paper about the library: https://www.mdpi.com/2078-2489/11/2/125

A Python library for audio data augmentation. Inspired by albumentations. Useful for machine learning.

Classifying between Car and Tank with the help of patch-based Image Classification Deep Learning Model

The program uses the albumentations library for Yolo format object detection. It takes images and labels directories as input and outputs augmented images with corresponding labels. This allows you to use albumentations functions without worrying about labeling, as it is handled automatically.

My implementation for FCV project

Automatic stain unmixing and augmentation for histopathology images in PyTorch