Transfer Learning for Dentist diagnosis aid , an intelligent healthcare application for train/validate/test/predict.
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Updated
Aug 31, 2024 - Python
Transfer Learning for Dentist diagnosis aid , an intelligent healthcare application for train/validate/test/predict.
dog breed classifier based on convnets, using catdog and lfw datasets.
Image classifier with Jax and Elegy. Using as an input any net to get the bottleneck features.
Built an algorithm to identify canine breed given an image of a dog. If given image of a human, the algorithm identifies the dog breed that is most resembling.
Query by example spoken term detection using bottleneck features and a convolutional neural network
Image captioning is the task of generating a caption for an image. We explore new models and analyse their performances. We will be using Tensorflow in this project.
An autoencoder that improves quality of a picture
Part 1 of Undergraduate Thesis Project @ UniBo: implementation of a convolutional neural network to recognize pills from photos, based on VGG16, using transfer learning, fine tuning
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.
QuickCNN is high-level library written in Python, and backed by the Keras, TensorFlow, and Scikit-learn libraries. It was developed to exercise faster experimentation with Convolutional Neural Networks(CNN). Majorly, it is intended to use the Google-Colaboratory to quickly play with the ConvNet architectures. It also allow to train on your local…
Given an image of a dog, our algorithm will identify an estimate of the canine’s breed. If supplied an image of a human, the code will identify the resembling dog breed.
A Keras implementation of YOLOv3 (Tensorflow backend)
An IPython notebook demonstrating the process of Transfer Learning using pre-trained Convolutional Neural Networks with Keras on the popular CIFAR-10 Image Classification dataset.
99.7% accuracy solution for Dogs vs Cats Redux Kaggle competition
Simple, yet fast, Python scripts to read Kaldi NNet3 models and compute bottleneck features
Simple classifier in your browser to predict dog breeds using Flask and Keras/Tensorflow.
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