🚀DenseNet Model by Pytorch

2018-plant disease recognition

A PyTorch Implementation for Densely Connected Convolutional Networks (DenseNets)

a simple application of densenet in pytorch

API for a machine learning model trained to detect post-it/sticky notes from scanned document images.

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

Final Project of the Udacity AI Programming with Python Nanodegree

a tool for detecting tables in image and analysing complex header

Classifies whether an image is of a dog or cat using pre-trained models

Pretrained Efficient DenseNet Model

DenseNet on CIFAR10 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.

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.

Implementation of DenseNets Using PyTorch

Densenet for Image Classification

Heat Map 🔥 Generation codes for using PyTorch and CAM Localization Algorithm.