QAT(quantize aware training) for classification with MQBench

This is a project documentation about melanoma detection methods using convolutional neural networks.

🔪 Elimination based Lightweight Neural Net with Pretrained Weights

The purpose of Food Vision project is to classify 101 variety of food items using Machine Learning.

An implementation of the Arabic sign language classification using Keras on the zArASL_Database_54K dataset

American Sign Language Alphabet Detection in Real Time with EfficientNetB0 in PyTorch

TFlite+CNN

49.5 mAP50 Detector enet4y2-coco.cfg = EfficientnetB0 + 4YOLO Layers + BiDirectionalFeatureMap with COCO Dataset and 81.0 mAP50 with VOC2007 test Dataset.

Development of a depth estimation model based on a UNET architecture - connection of Bi-directional Feature Pyramid Network (BIFPN) and EfficientNet.

HAM10000 Skin Lesion Classification

Image Captioning using EfficientNet and GRU

This is my capstone project that was completed as part of the General Assembly Data Science Immersive curriculum. I conceptualized the idea, executed the project and developed a prototype for predicting success in the South Korean drama industry based on face image. This serves as a proof-of-concept which can definitely be developed further.

INR Denomination Recognition is an image classification project

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.

Mask Monitoring System

A project on building deep learning classifier to classify playing cards

Dust detection on solar photovoltaics panel using pre-trained CNN models

A multi classification using scikit-learn and TensorFlow models on MRI scans of patient's brains.

Clasificación de imágenes y reconocimiento de objetos mediante la red neuronal convolucional CNN DenseNet y EfficientNet con el modelo frozen model y el framework Coffe. Posteriomente, mediante la red neuronal convolucional CNN MobileNet-SSD y YOLO con el framework TensorFlow