Deep learning techniques can enhance diagnosis of Meniere disease

Deep learning techniques can enhance diagnosis of Meniere disease (MD) and severity grading, according to a study published ...
Hosted on MSN

Mini-batch gradient descent in deep learning explained

Mini Batch Gradient Descent is an algorithm that helps to speed up learning while dealing with a large dataset. Instead of updating the weight parameters after assessing the entire dataset, Mini Batch ...
Beebom

What is Deep Learning in AI? Understanding How AI Really Works

Deep learning uses multi-layered neural networks that learn from data through predictions, error correction and parameter adjustments. It started with the ...
IEEE

Load Frequency Control of Multi-Microgrids Based on Deep Deterministic Policy Gradient Integrated With Online Learning

Abstract: The integration of wind power into microgrids significantly increases the complexity of the microgrid’s dynamical behavior and introduces higher levels of uncertainty. This paper addresses ...
Frontiers

Construction of a deep - learning - based rehabilitation prediction model for lower-limb motor dysfunction after stroke using synchronous EEG-EMG and fMRI

Objective: Construct a predictive model for rehabilitation outcomes in ischemic stroke patients 3 months post-stroke using resting state functional magnetic resonance imaging (fMRI) images, as well as ...
GitHub

Gradient Similarity Surgery in Multi-task Deep Learning

Official implementation of the SAM-GS optimizer for multitask learning ArxIv Comparison of different MTL methods for 20000 steps.\ Top row: The loss trajectories of different MTL methods in the loss ...
IEEE

Mixture of Gradient: A Unified Enhancing Approach for Deep Learning-Based Wireless Network Optimization

Abstract: Deep learning plays increasingly important role in future wireless network management and optimization. Existing training methods such as label-based supervised learning and label-free ...