Frontiers

A Deep-Learning-Based Real-Time Detector for Grape Leaf Diseases Using Improved Convolutional Neural Networks

Black rot, Black measles, Leaf blight and Mites of grape are four common grape leaf diseases that seriously affect grape yield. However, the existing research lacks a real-time detecting method for ...
Frontiers

Deep Convolutional Neural Networks With Ensemble Learning and Generative Adversarial Networks for Alzheimer’s Disease Image Data Classification

1 Pluripotent Diagnostics Corp. (PDx), Molecular Medicine Research Institute, Sunnyvale, CA, United States 2 Eastern Nazarene College, Quincy, MA, United States Recent advancements in deep learning ...
IEEE

Facial Expression Recognition Using Deep Convolution Neural Networks

Abstract: Facial Expressions are being used as a communication tool between humans and technology devices. Humans express their emotions through their body movements, facial expressions, speech, text, ...
IEEE

Convolutional Neural Networks

The concepts and structure of convolutional neural structures are described in Chapter 4. It starts with the concept of convolution in two dimensions and its justification for its use in deep learning ...
GitHub

Convolution_model_Step_by_Step_v1.ipynb

" - Example: $a^{[4]}$ is the $4^{th}$ layer activation. $W^{[5]}$ and $b^{[5]}$ are the $5^{th}$ layer parameters.\n", "- Subscript $i$ denotes the $i^{th}$ entry of ...
GitHub

In this project, we are using deep learning convolution neural network algorithms to classify plant seedlings. The dataset is available on Kaggle.

In the dataset, we have different 12 classes of seedlings under train dataset. In particular, we will focus on the parameters and preprocess the parameters before training our model. In modeling, we ...