IEEE

Enhancing Soybean Disease Diagnosis using CNN-based Feature Extraction and Random Forest Classification

Abstract: Soybean plants are highly susceptible to various diseases, impacting crop yield and quality. Accurate and early detection of these diseases is essential for effective management and ...
IEEE

SCFNet:A Swin-CNN Synergistic Fusion Network For Urban and Rural Water Extraction In Remote Sensing Images

Accurate monitoring of water resources is essential for disaster risk reduction and sustainable development amid global climate change. At present, various methods based on convolutional neural ...
IEEE

Investigating SAR Data Denoising: A Comparative Analysis of CNN Models with Multi-Channel Signal Processing Features

Abstract: This paper investigates the necessity for denoising in Synthetic Aperture Radar (SAR) dataset, emphasizing the comparison of three distinct neural networks: U-Net, ResNet, and DeepDeblur.

How AI coding agents work—and what to remember if you use them

At the core of every AI coding agent is a technology called a large language model (LLM), which is a type of neural network ...