IEEE

Transfer Learning Based Multiclass Brain Tumor Classification Using Mri Data

Abstract: Deep learning for classifying brain tumors has transformed medical image analysis, significantly improving upon manual detection techniques. Brain tumors are defined by aberrant cellular ...
EurekAlert!

PolyU develops novel AI graph neural network models to unravel interdisciplinary complexities in image recognition and neuroscience

As an emerging technology in the field of artificial intelligence (AI), graph neural networks (GNNs) are deep learning models designed to process graph-structured data. Currently, GNNs are effective ...
Medical Xpress

AI model predicts neural network degeneration patterns in ALS progression

New research from the University of St Andrews, the University of Copenhagen and Drexel University has developed AI computational models that predict the degeneration of neural networks in amyotrophic ...
Hosted on MSN

Python neural network for multiclass classification using softmax

Implement Neural Network in Python from Scratch ! In this video, we will implement MultClass Classification with Softmax by making a Neural Network in Python from Scratch. We will not use any build in ...
C&EN

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

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GitHub

ash1ra/Numpy-FFNN-Classification-MNIST

It is possible to choose the values of the model parameters for a long time, but I decided to stop on a compromise between the learning speed and test accuracy.
IEEE

A Deep Learning Model for Multiclass Image Classification Using Quantum CNN

Abstract: Technological developments in machine learning have opened up new avenues of advancement almost in every sector. The main challenge is communicating effectively with machines and enhancing ...