Deep learning has been successfully applied in the field of medical diagnosis, and improving the accurate classification of ...

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 ...

Visual Attention Networks (VANs) leveraging Large Kernel Attention (LKA) have demonstrated remarkable performance in diverse computer vision tasks, often outperforming Vision Transformers (ViTs) in ...

Abstract: This study investigates the application of Spiking Neural Network (SNN) in seismic signal denoising by developing a Convolutional Neural Network (CNN) to SNN conversion framework. We focus ...

Researchers in China have created a dataset of various PV faults and normalized it to accommodate different array sizes and typologies. After testing the new approach in combination with the 1D-CNN ...

This repository implements a Temporal Convolutional Network (TCN) model for predicting financial instrument prices, including currencies, stocks, and cryptocurrencies. It uses advanced techniques like ...

Abstract: In recent years, real-valued neural networks have made significant progress in computer vision tasks such as image classification, object detection, and semantic segmentation. However, ...

Species distribution models (SDMs) often overlook critical spatial heterogeneity and multiscale environmental patterns, which limit their predictive accuracy for species occurrences. We demonstrate ...