Projects in Awesome Lists tagged with fine-tuning-cnns
A curated list of projects in awesome lists tagged with fine-tuning-cnns .
https://github.com/duggalrahul/AlexNet-Experiments-Keras
Code examples for training AlexNet using Keras and Theano
convolutional-neural-networks deep-learning feature-extraction fine-tuning-cnns keras theano
Last synced: 27 Nov 2024
https://github.com/knjcode/mxnet-finetuner
An all-in-one Deep Learning toolkit for image classification to fine-tuning pretrained models using MXNet.
deep-learning deep-neural-networks fine-tuning-cnns machine-learning mxnet
Last synced: 17 Apr 2025
https://github.com/imatge-upc/sentiment-2017-imavis
From Pixels to Sentiment: Fine-tuning CNNs for Visual Sentiment Prediction
affective-computing cnn computer-vision deep-learning fine-tuning-cnns sentiment sentiment-maps
Last synced: 11 May 2025
https://github.com/cg1507/quickcnn
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 system.
bottleneck-features cnn-training convolutional-neural-network deep-learning fine-tuning-cnns google-colaboratory image-classification keras sklearn-library tensorboard tensorflow transfer-learning
Last synced: 16 Feb 2025
https://github.com/kleinyuan/tf-ft
Implementation on tensorflow fine tuning of generic CNN based model
alexnet convolutional-neural-networks fine-tuning fine-tuning-cnns tensorflow vgg
Last synced: 12 Apr 2025
https://github.com/nikamrohan/cats-vs-dogs
Using Pytorch with Django To distinguish Cats from Dogs by Fine Tuning pretrained Model.
cats-vs-dogs deep-learning deep-neural-networks django django-framework fine-tuning-cnns pretrained-models pytorch pytorch-implmention vgg16
Last synced: 24 Feb 2025
https://github.com/ranfysvalle02/cnn-transfer-learning
The provided code demonstrates transfer learning by adapting a model trained using synthetic data to classify circles, squares, and triangles to classify new shapes like stars and pentagons. By fine-tuning a pre-trained model originally designed for a different task, the repository showcases how to efficiently adapt a model to a new domain.
cnn-classification convolutional-neural-network fine-tuning fine-tuning-cnns neural-network transfer-learning transfer-learning-with-cnn
Last synced: 12 Apr 2025
https://github.com/sayamalt/brain-tumor-image-classification
Successfully developed an image classification model to classify images of distinct types of brain tumors such as glioma tumor, meningioma tumor, pituitary tumor, etc.
alexnet convolutional-neural-networks data-loader deep-learning densenet121 fine-tuning-cnns image-classification mobilenetv3-large model-training-and-evaluation pytorch resnet-50 vgg16
Last synced: 29 Mar 2025
https://github.com/sayamalt/natural-scenes-image-classification-using-cnns
Successfully established an image classification model using PyTorch to classify the images of several distinct natural sceneries such as mountains, glaciers, forests, seas, streets and buildings with an accuracy of 86%.
convolutional-neural-networks deep-learning fine-tuning-cnns flask-deployment image-classification image-transformations model-inference model-training-and-evaluation multiclass-classification pytorch resnet50-model torch-dataloader
Last synced: 19 Feb 2025