IEEE

A Novel CNN Architecture for Alzheimer's Disease Classification Using MRI Images: Comparison with Traditional Machine Learning Models

Abstract: Automated medical image processing has significantly improved with recent advances in deep learning and imaging technologies, particularly in the area of neuroimaging-based Alzheimer's ...
IEEE

Improved Deep Learning-Based Microwave Inversion With Experimental Training Data

Abstract: Deep learning-based inversion methods show great promise. The most common way to develop deep learning inversion techniques is to use synthetic (i.e., computationally-generated) data for ...
IEEE

Epileptic Seizure Prediction Using a Deep Hybrid CNN-GAN Model on EEG Data

Abstract: Epileptic seizure detection from EEG signals is essential for the diagnosis and treatment of neurological conditions. However, this task is difficult because of the complex and fluctuating ...
IEEE

Deep Learning-Based Malaria Detection: A Robust CNN Framework for Accurate and Automated Diagnosis

Abstract: This research suggests a strong framework for automated malaria detection using a Convolutional Neural Network (CNN) model. The dataset, sourced from Kaggle, consists of 27,558 ...
AlphaGalileo

Deep learning breakthrough enables rapid identification of soil "Canaries" – Collembola

A groundbreaking study published in Soil Ecology Letters unveils a novel deep learning method to rapidly and accurately identify soil-dwelling ...
Physics World

Hybrid deep-learning model eases brachytherapy planning

The BCTVNet neural network provides accurate and rapid target volume delineation for cervical cancer brachytherapy ...
IEEE

A Hybrid CNN-LSTM Deep Learning Model for Next-Generation OFDM Channel Estimation in Wireless Networks

Abstract: Orthogonal Frequency Division Multiplexing (OFDM) enables high-rate data transmission wards wirelss broadband connections. Accurate channel estimation continues to be an unsolved issue in ...
IEEE

Hybrid CNN and Transformer-Based Sequential Learning Techniques for Plant Disease Classification

Abstract: Plant diseases have important consequences for livelihoods and economies, both on local and global scales, whereby the spread of plant pathogens can lead to high levels of damage to ...
Microsoft

nnScaler: Constraint-Guided Parallelization Plan Generation for Deep Learning Training

With the growing model size of deep neural networks (DNN), deep learning training is increasingly relying on handcrafted search spaces to find efficient parallelization execution plans. However, our ...
IEEE

Handwritten Amharic Character Recognition Through Transfer Learning: Integrating CNN Models and Machine Learning Classifiers

Abstract: Handwritten Amharic character recognition presents significant challenges due to the script’s syllabic nature and variations in handwriting styles. This study investigates a hybrid approach ...

What is CNN in Deep Learning? The AI Behind Computer Vision

Learn what CNN is in deep learning, how they work, and why they power modern image recognition AI and computer vision programs.