Demo of Inception v3.

Simple Example of Image Recognition

Here is an implementation of InceptionV3 and VGG-16 models in Python from scratch. These models were then trained on a dataset of handwritten alphabets. An experiment was carried out to achieve higher accuracy by using different combinations of optimizers and learning rates. These models were then compared to the inbuilt models in Python.

Smart bike using deep learning and iot

A deep learning model that generates captions for camera trap images in the Snapshot Serengeti dataset.

an implementation of the Convolutional Neural Network model and Transfer Learning (InceptionV3) model to classify horse or human images.

Multi image label classification by multi models.

Using CNN to classify dog's breed. Inception v3 model has been trained using Transfer Learning.

pytorch implementations of some DL architectures. Includes googlenet, resnet, inceptionV3, densenet, mobilenetV1, mobilenetV2, senet, efficientnetV1, transformer etc.

Used CNN architecture and pre trained weights of VGG16 to detect brain tumor from Images.

A Comparative Study of the performance of CNN from scratch compared to a transfer learning approach (InceptionV3)

This repository contains the code and resources for a deep learning project aimed at recognizing hand signs for the game of Rock-Paper-Scissors. The project utilizes convolutional neural networks (CNNs) to classify hand signs captured through a webcam, enabling users to play the game without the need for physical gestures.

Various codes and scripts used during AI research, all neatly organised

Jupyter notebook was made for doing machine learning which classify images

Identifying vehicle and appliance damage from an image on a scale of low, moderate, high

Udacity's Deep Learning Nanodegree Project - Dog-Breed Classifier

Inception_v3 in Tensorflow 2

One notebook trains a vegetable classification model with InceptionV3 using TensorFlow and Keras. The second notebook showcases the pre-trained model's inference on vegetable categories, loading InceptionV3 and enhancing image features. Together, they offer a compact solution for vegetable classification through deep learning.

Image Dehazing using GANs