Demo of Inception v3.
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Updated
Nov 30, 2017 - Python
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.
simple transfer learning example form Inceptoinv3
Example models for cifar10 classification
Scraping prices from web and clustering images to fit price categories.
This complete project is made as a part of Data Science Internship at iNeuron.ai Refer to the README for more detailed explanation about the project!
A ML model which helps the differently abled people(i.e, deaf , dumb & blind) to communicate
Accurate image classification powered by InceptionV3 deep learning model. Quickly classify diverse images with high precision using TensorFlow.
Blindness Detection - Machine Learning Model for Diabetic Retinopathy Patients
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
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
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