Repo for the "APTOS 2019 Blindness Detection" competition on Kaggle, to share my approach to solving the problem.

Leaf disease classification on kaggle

Using a CNN to make a facial emotion recognition model and comparing its performance to other transfer layer architectures.

I'm developing an app named BarkRescue, which includes project code, app functionalities, and system architecture. Additionally, I've written three detailed blogs on EfficientNet, YOLOv5, and MobileNet-v2, focusing on their architecture and workings before integrating these models into my project.

Reteaua neuronala CitNet

One-stage and two-stage face detection models

This project aims to improve the performance of the classification algorithm by implementing state-of-the-art model: EfficientNet in place of VGG-16.

Glume pubescence classification of wheat using convolutional neural networks

Project 7 of the course "Specialization Data Science" that updated to the app

EfficientNet-Transformer model for convert image to UTF8 text

Image recommendation app using EfficientNet-B7 / Vision Transformer

This Kaggle challenge is part of the Deep Learning course offered by University of Siegen, Germany.

one-stage and two-stage detectors and segmentation-based detectors

Skin lesion (Melanoma) cancer detector

Mask Monitoring System

Ear recognition using CNN based on EfficientNet-B0 (Assignment 3 for Image Based Biometry course at University of Ljubljana)

Driver's Drowsiness Prediction Using CNN Architechtures

Classification of Liver fat with a voting classifier

Automation of model training and ensemble creation for making predictions in a Kaggle competition submission.