IEEE

VaniKG: Vanishing Key Gradient Attack and Defense for Robust Federated Aggregation

Abstract: The AGgregation Algorithms (AGAs) that combine locally trained models into a single global model in Federated Learning (FL) is becoming a new attack vector for adversaries. Model Poisoning ...
USA Today

'Stranger Things' Season 5 Episode 2 recap − The final battle begins

Spoiler alert! The following contains details from Season 5, Episode 2 of "Stranger Things," "The Vanishing of Holly Wheeler." Can you hear the demogorgan, Fernando? "Stranger Things" is known for ...
IEEE

Brain Tumor Detection using Optimized Stochastic Gradient Descent Function

Abstract: The learning rate of a CNN determines the efficiency of the neural network. In brain tumor detection, the learning rate and the optimization function plays a key role in deciding the final ...
IEEE

Gradient-Infused Multi-Scale Attention Based CNN for Robust Image Denoising

Abstract: In the field of digital image processing, noise removal is a critical preprocessing step for tasks such as object detection, segmentation, and tracking. Convolutional Neural Networks (CNNs) ...
IEEE

CNN-based Adaptive Matching and Topological Reconstruction for Diamond NV Center Multi-Axis Magnetic Gradient Imaging

Abstract: This paper addresses the limitations in nanoscale spatial resolution of diamond NV center multi-axis magnetic gradient imaging, caused by large defect feature matching errors and ...
IEEE

Cross-Domain Multilevel Feature Adaptive Alignment R-CNN for Insulator Defect Detection in Transmission Lines

Abstract: Insulator defect detection is a crucial task in the intelligent inspection of transmission lines. Currently, there are challenges such as insufficient image samples and difficulties in ...
IEEE

A Transferable Multi-Scale Convolution Domain Adaptation Network for Bearings RUL Prediction

Abstract: Transfer learning methodologies predominantly concentrate on adapting to varied operational conditions. However, disparities in probability distributions and the deterioration of performance ...
Hosted on MSN

Residual connections explained: Preventing transformer failures

Training deep neural networks like Transformers is challenging. They suffering from vanishing gradients, ineffective weight updates, and slow convergence. In this video, we break down one of the most ...
IEEE

Time Series Forecasting for Solar Power Generation using Support Vector Regression with Extreme Gradient Boosting

Abstract: In modern era, time series forecasting plays a crucial role in Solar Power Generation (SPG), by allowing the prediction of future energy output using past power and weather data for grid ...
CNN

He brought over 600 water bodies back to life. His next mission: saving India’s vanishing stepwells

EDITOR’S NOTE: Call to Earth is a CNN editorial series committed to reporting on the environmental challenges facing our planet, together with the solutions. Rolex’s Perpetual Planet Initiative has ...
IEEE

Using CNN and Gradient Boosting to Accurately Classify Guar Varieties in India

Abstract: This study introduces a new way to group different Guar types in India. It uses Convolutional Neural Networks (CNN) and Gradient Boosting (GB) methods for this task. A complete set of about ...