kratzert/finetune_alexnet_with_tensorflow

Code for finetuning AlexNet in TensorFlow >= 1.2rc0

/ 100

Established

This project helps machine learning engineers adapt a pre-trained image classification model (AlexNet) to new, specific image datasets. You provide your custom image dataset, organized with image file paths and corresponding labels in text files, along with pre-trained AlexNet weights. The output is a fine-tuned AlexNet model capable of accurately classifying images within your unique categories.

782 stars. No commits in the last 6 months.

Use this if you are a machine learning engineer who needs to quickly get a high-performing image classifier for your specific image categories without training a model from scratch.

Not ideal if you are looking for a no-code solution or want to train a custom deep learning architecture from the ground up without using existing models.

image-classification deep-learning model-adaptation computer-vision machine-learning-engineering

Stale 6m No Package No Dependents

Maintenance 0 / 25

Adoption 10 / 25

Maturity 16 / 25

Community 25 / 25

How are scores calculated?

Stars

782

Forks

404

Language

Jupyter Notebook

License

BSD-3-Clause

Related frameworks

raghakot/keras-resnet

Residual networks implementation using Keras-1.0 functional API

titu1994/DenseNet

DenseNet implementation in Keras

liuzhuang13/DenseNet

Densely Connected Convolutional Networks, In CVPR 2017 (Best Paper Award).

BIGBALLON/cifar-10-cnn

Play deep learning with CIFAR datasets

bamos/densenet.pytorch

A PyTorch implementation of DenseNet.

Explore ML Frameworks

All categories Trending ML Framework directory Insights