IEEE

An Explainable Deep Learning Network With Transformer and Custom CNN for Bean Leaf Disease Classification

Abstract: Bean rust and angular leaf spot pose significant challenges to bean cultivation, impacting yields. Prompt disease identification maximizes productivity, but traditional methods need ...
IEEE

Fine-Grained Feature Extraction in Key Sentence Selection for Explainable Sentiment Classification Using BERT and CNN

Abstract: Online product reviews provide valuable insights into customer sentiment toward products; however, they often contain multiple sentences with redundant and non-essential content, making it ...
IEEE

Innovative Development of Hybrid LSTM-CNN Architecture with Optimized Parameters for Enhanced Predictive Maintenance Performance

Abstract: Maintenance is a significant cost factor in manufacturing, accounting for up to 60 of the total factory manufacturing costs. Optimizing these operations is crucial to minimize costs and ...
IEEE

Research on Sleep Stage Classification of Electroencephalogram Signals Based on CNN and LSTM

Abstract: Chronic sleep deprivation can seriously affect physical and mental health and increase the risk of many chronic diseases. Sleep staging methods can assess sleep quality, but the manual ...
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

Robust Road Surface Classification Using Time Series Augmented Intelligent Tire Sensor Data and 1-D CNN

Abstract: Tire-road friction coefficient information is an essential factor in the driving stability and safety of a vehicle. In recent years, there has been a lot of research on using the vibration ...
IEEE

Hybrid Deep Learning Architecture for Accurate Brain Tumor Classification

Abstract: An important part of medical imaging is classifying brain tumors since precise detection is critical to an early diagnosis and for the planning of effective treatment. This study presents a ...
IEEE

EmotionNet-X: An Optimized CNN Architecture for Robust Facial Emotion Analysis

Abstract: Facial emotions are expressions of people’s inner feelings. A computer’s ability to recognize emotions is known as emotion recognition (ER), which involves extracting facial characteristics ...
IEEE

Lymphoma sub-type classification using DenseNet 169-based Transfer Learning Architecture

Abstract: Lymphoma is a serious disease with significant potential complications, including heart disease, lung disease, and increased susceptibility to infections due to immune system suppression.
IEEE

Deep Learning Meets Traditional AI: A Hybrid CNN-RF Model for Accurate and Explainable Skin Lesion Classification

Abstract: In dermatology, the task of skin lesion classification is a very important one, for early detection and treatment of skin cancer. In this work, we propose a hybrid AI model where ...
IEEE

A Robust CNN-LSTM Framework for Sensitive and Specific Brain Tumor Classifications

Abstract: Diagnosing brain tumor is a key medical challenge where identification of the tumor is crucial to determine an appropriate treatment methodology. In this paper, we present a new hybrid deep ...
IEEE

Enhancing GNSS Localization in Urban Canyons With a Hybrid CNN-Autoencoder Approach to LOS/NLOS Classification

Abstract: Non-Line-of-Sight (NLOS) reception is acknowledged as a primary source of positioning error in Global Navigation Satellite System (GNSS) applications ...