IEEE

Hyperspectral Image Classification Based on Subgraph-Dependent Neural Network

Abstract: Hyperspectral image classification methods based on subgraph neural networks (SGNNs) are rarely explored, and its advantage is that it can alleviate the neighbor explosion problem. After ...
Frontiers

A neural network model combining the successor representation and actor-critic methods reveals effective biological use of the representation

In learning goal-directed behavior, state representation is important for adapting to the environment and achieving goals. A predictive state representation called successive representation (SR) has ...
GitHub

Neural Network from Scratch

This project implements a neural network from scratch to classify handwritten digits using the MNIST dataset. The neural network is built using Python and utilizes libraries such as NumPy and ...
Hosted on MSN

Image Classification With Cnns In Keras — Full Code Walkthrough

In this video, we will implement Image Classification using CNN Keras. We will build a Cat or Dog Classification model using CNN Keras. Keras is a free and open-source high-level API used for neural ...
C&EN

Practical Machine Learning Strategies 4: Using Neural Networks to Replicate Proton and

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GitHub

AQI Prediction and Sky Image Classification Using a Multi-Task CNN

This repository contains the implementation of a robust multi-task learning model designed to analyze images for air quality. The model simultaneously performs two tasks: Binary Classification: It ...
The Lancet

Automatic identification of Parkinsonism using clinical multi-contrast brain MRI: a large self-supervised vision foundation model strategy

aDepartment of Radiology, Institution of Radiology and Medical Imaging, West China Hospital of Sichuan University, Chengdu, 610041, Sichuan, China bFunctional and Molecular Imaging Key Laboratory of ...
IEEE

Glioma Brain Tumor Classification Using Convolution Neural Network and Majority Voting

Abstract: Glioma brain tumors are malignant diseases for which early detection and instant treatment will increase the survival rate. Several studies have reported the efficiency of deep learning ...