IEEE

Hybrid Deep Learning for Portable Weather Forecasting: Real-Time Predictions Using CNN-LSTM-Transformer Models

Abstract: Accurate weather forecasting is critical for agriculture, disaster management, and transportation sectors. However, traditional forecasting systems often require extensive computational ...
IEEE

MFC-CNN: A Deep Learning Framework for Urban Building Height Estimation from GF-7 Imagery

Abstract: Estimating building heights by generating disparity maps from multi-view satellite images through stereo matching remains challenging in urban research. However, disparity maps produced by ...
News-Medical.Net

Integrated Monte Carlo and deep learning improve radiotherapy QA

Led by Professor Fu Jin, the study addresses a critical challenge in radiation therapy: balancing the computational speed and ...
IEEE

Automated Food Spoilage Detection Using Deep Learning: A CNN-Based Approach

Abstract: Food spoilage detection is critical in ensuring food safety and reducing waste. In this work, we offer a new neural network model, rotOrNot, intended for image analysis-based rotten food ...
IEEE

Adversial Learning Through GAN and Feature Extraction Through CNN for Deep Fake Detection

Abstract: Deepfake technology, using deep learning, creates highly realistic yet artificial media, creating challenges for security and privacy. Convolutional Neural Networks (CNNs) play a crucial ...
IEEE

Self-Supervised Monocular Depth Estimation Using Hybrid CNN-VMamba Architecture

Abstract: Self-supervised monocular depth estimation (MDE) typically employs convolutional neural networks (CNNs) or Transformers to predict scene depth. However, CNNs struggle with long-range ...