Code examples for training AlexNet using Keras and Theano
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Updated
Apr 10, 2017 - Jupyter Notebook
Code examples for training AlexNet using Keras and Theano
animal is good
Fine-tuning an already learned model, adapts the architecture to other datasets
Implementation on tensorflow fine tuning of generic CNN based model
Pretrained VGG-16 network as feature extractor for Object Recognition (Python, Keras, Scikit-Learn)
This repository not only contains experience about parameter finetune, but also other in-practice experience such as model ensemble (boosting, bagging and stacking) in Kaggle or other competitions.
ImageNet pre-trained models with batch normalization for the Caffe framework
Code for our paper "Generalized Orderless Pooling Performs Implicit Salient Matching" published at ICCV 2017.
DL pre-trained mode fine-tuning for cat-dog classification example
Ongoing minor project
An all-in-one Deep Learning toolkit for image classification to fine-tuning pretrained models using MXNet.
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…
Switching from GPU to the future of Machine learning the TPU. Over 1 million images trained Resnet50 in under 20 mins compared to days or weeks on GPU and all for 0$ free on Google Colab Notebooks in Google Drive, clone repo and jump right in!!
Using Pytorch with Django To distinguish Cats from Dogs by Fine Tuning pretrained Model.
Keras implementation of multi-label classification of movie genres from IMDB posters
The project aims to detect the faces and to determine whether the person wears a face mask or not.
Online machine learning competition for high school students.
From Pixels to Sentiment: Fine-tuning CNNs for Visual Sentiment Prediction
A Convolution Neural Network Model for predicting various types of food.
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