IEEE

Hybrid Deep Learning Framework for Road Surface Classification: Integrating Autoencoder-Based Denoising and CNN-Based Classification

Abstract: This study uses a hybrid deep learning technique to classify asphalt, pavement, and unpaved roads. In real-world circumstances, image data noise can damage image categorization algorithms.
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

Integrating CNN With PolInSAR Multidimensional Backscattering for Enhanced Forest Height Retrieval

Abstract: The operational deployment of P-band synthetic aperture radar (SAR) constellations (e.g., ESA’s BIOMASS) has established low-frequency polarimetric interferometric SAR (PolInSAR) as a ...
IEEE

Evolutionary Neural Architecture Search for Remote Sensing Image Classification

Abstract: Remote sensing scene classification is a vital task in remote sensing image analysis with significant application potential. In recent years, convolutional neural network (CNN)-based methods ...
IEEE

A Novel Transformer-CNN Hybrid Deep Learning Architecture for Robust Broad-Coverage Diagnosis of Eye Diseases on Color Fundus Images

Abstract: We present a novel and robust deep-learning architecture that takes into account the pathological characteristics of eye diseases on color fundus images. The proposed hybrid architecture is ...
IEEE

StressIRNet: A Novel Lightweight CNN Architecture for Stress Classification Leveraging Smartphone Thermal Imaging Modality

The pervasive and growing incidence of stress-related disorders underscores a critical need for accessible, non-invasive monitoring technologies. Conventional physiological modalities such as ...
Frontiers

CNN-based framework for Alzheimer's disease detection from EEG via dynamic mode decomposition

Alzheimer's disease (AD) and frontotemporal dementia (FTD) are major neurodegenerative disorders with characteristic EEG alterations. While most prior studies have focused on eyes-closed (EC) EEG, ...
Frontiers

A Dual-input deep learning architecture for classification and latency estimation in ABR signals

Introduction: Auditory brainstem response (ABR) is an objective neurophysiological evaluation designed to measure the electrical activity originating from the auditory nerve and brainstem in response ...