🚀DenseNet Model by Pytorch
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Updated
Nov 15, 2023 - Python
🚀DenseNet Model by Pytorch
A PyTorch Implementation for Densely Connected Convolutional Networks (DenseNets)
API for a machine learning model trained to detect post-it/sticky notes from scanned document images.
Classifies whether an image is of a dog or cat using pre-trained models
Pretrained Efficient DenseNet Model
In this project, an image classifier is trained to recognize different species of flowers
Generating attention maps from resnet50 and densenet using ACDC and EMIDEC dataset
Code that can be used for training a neural network model to detect faults (sticky notes, folded corners etc.) in input documents.
Code that can be used for training a neural network model to classify input documents into distinct classes.
Final Project of the Udacity AI Programming with Python Nanodegree
a tool for detecting tables in image and analysing complex header
Using Densenet121 & Adam Optimizer on a Jupyter Notebook
API for a machine learning model trained to detect folded or torn corners and edges from scanned document images.
DenseNet on CIFAR10 dataset
Implementation of DenseNets Using PyTorch
Transfer Learning on my butterfly images using PyTorch
A deep learning, image classifying project for flower species using PyTorch and Jupyter Notebooks
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