Transfer Learning with TensorFlow
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Updated
Apr 19, 2018 - Python
Transfer Learning with TensorFlow
A web app that analyzes, recognizes, and gives information about dog breeds, all based on an image from the user 🐩
Udacity Artificial Intelligence Nanodegree CNN Project. Created a CNN for breed classification of dogs by transfer learning using bottleneck features of four pre-trained models. Implemented the Haar cascade classifier for human face detection.
This is a Dog Breed Classifier built using CNN
Simple app to find random pictures of selected dog breeds
Use deep learning ( CNN ) to detect dog in images and specify the breed of the dog and another part of project, is detect human face then estimate of the dog breed that is most resembling :)
This project divided into Two-part : (( Dog Breed Classifier )) Capstone-Proposal + Capstone-Project
The RNN will take an image of a dog then will identify an estimate of the canine’s breed. If supplied an image of a human, the code will identify the resembling dog breed.
Using CNNs to identify the breed of dog in an image
Trying out the Dog API. The original dataset from the Stanford Dogs Dataset. Built using vanilla JS and CSS3.
Second Deep learning project
The dog application is the part of @udacity Artificial Intelligence Nanodegree. Here I am implementing CNN in Keras to classify dog breeds.
Deep Learning Nanodegree Project : Given an image of a dog, the algorithm will identify an estimate of the canine’s breed. If supplied with an image of a human, the code will identify the resembling dog breed.
iOS app classifier that will predict dog breed by passing selected image into a trained neural network model.
A website with information about dog breeds. Built with Gatsby and Contenful CMS.
End-to-end deep learning pipeline to classify images of dogs and humans to determine what breed the human or dog most resembles
A web-based dog breed identifier in PyTorch deployed using Flask. This is an example of transfer learning for which Resnet152 is used.
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