Sakib1263/TF-1D-2D-ResNetV1-2-SEResNet-ResNeXt-SEResNeXt
Models supported: ResNet, ResNetV2, SE-ResNet, ResNeXt, SE-ResNeXt [layers: 18, 34, 50, 101, 152] (1D and 2D versions with DEMO for Classification and Regression).
This project offers pre-built deep learning models for classifying or predicting outcomes from both one-dimensional data, like sensor readings or time series, and two-dimensional data, such as images. It takes raw data, processes it through advanced neural network architectures (ResNet, ResNeXt), and outputs classifications (e.g., 'cat' or 'dog') or numerical predictions. This is ideal for machine learning engineers or researchers who need to quickly implement powerful, battle-tested models for their predictive tasks.
No commits in the last 6 months.
Use this if you need to apply robust deep learning models for classification or regression on either 1D sequence data or 2D image-like data, and want highly configurable, production-ready architectures.
Not ideal if you're looking for a low-code solution for general data analysis, or if your problem doesn't involve deep learning on structured 1D or 2D inputs.
Stars
44
Forks
9
Language
Jupyter Notebook
License
MIT
Category
Last pushed
Jan 27, 2022
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/Sakib1263/TF-1D-2D-ResNetV1-2-SEResNet-ResNeXt-SEResNeXt"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
kratzert/finetune_alexnet_with_tensorflow
Code for finetuning AlexNet in TensorFlow >= 1.2rc0
bamos/densenet.pytorch
A PyTorch implementation of DenseNet.
raghakot/keras-resnet
Residual networks implementation using Keras-1.0 functional API
liuzhuang13/DenseNet
Densely Connected Convolutional Networks, In CVPR 2017 (Best Paper Award).
gpleiss/efficient_densenet_pytorch
A memory-efficient implementation of DenseNets