IEEE

Gender Abusive Bengali Text Classification using Enhanced CNN-LSTM Model with Bangla BERT Base Preprocessing

Abstract: With the rapid proliferation of social media and online communication platforms, the presence of gender-based abusive language has emerged as a significant issue in the digital sphere.
IEEE

CTPMSN: Enhancing Multimodal Remote Sensing Classification With Composite Text Prompts

Abstract: Remote sensing multimodal data integrates information from various sensors, providing detailed characterization and reliable monitoring capabilities for Earth observation tasks. This data is ...
IEEE

A Hybrid Approach Using CNN Feature Extraction and SVM/XGBoost for Lung Nodule Classification

Abstract: Early detection of lung cancer is highly beneficial for patient survival. This paper proposes a hybrid deep learning diagnostic pipeline for pulmonary nodules in chest CT. We constructed a ...
IEEE

Hierarchical Text Classification Method Driven by Dynamic Hierarchical Fusion and Prompt Embedding

Abstract: Hierarchical Text Classification, as a critical task in natural language processing, has broad applications in scenarios with complex label structures and limited samples. However, existing ...
IEEE

Accurate Fake News Detection in Text-Based Content Using K-Nearest Neighbor, LSTM, MLP and CNN Models

Abstract: With the proliferation of social media platforms, where users are free to express themselves and share content, the detection of fake news in text has become an important issue. The ...
IEEE

Cross-Domain Hyperspectral Image Classification via Mamba–CNN and Knowledge Distillation

Abstract: Domain adaptation (DA)-based cross-domain hyperspectral image (HSI) classification methods have garnered significant attention. The majority of DA techniques utilize models based on ...
IEEE

Enhancing Text Classification Through Quantum Transfer Learning: A Hybrid Quantum-Classical Approach With Complex Kernel Self-Attention Networks

Abstract: Quantum computing, with its unique principles such as superposition and entanglement, promises to transform various domains, including artificial intelligence. This study investigates the ...
IEEE

An Ensemble Deep Learning Model Using CNN, LSTM and Autoencoder for EEG-Based Parkinson’s Disease Classification

Abstract: Parkinson's disease is a neurological disorder hat effects the movements including shaking, stiffness, difficulty while walking and speaking. This condition will occur when the nerve cells ...
IEEE

CNN with Efficient Channel Attention for Multi-Class Respiratory Sound Prediction

Abstract: Computerized listening relies on machine learning tools for the analysis of breathing sounds and can be reliably used for the detection of lung diseases. This paper presents the design of a ...
Frontiers

CNNAttLSTM: an attention-enhanced CNN–LSTM architecture for high-precision jackfruit leaf disease classification

Introduction: Jackfruit cultivation is highly affected by leaf diseases that reduce yield, fruit quality, and farmer income. Early diagnosis remains challenging due to the limitations of manual ...
IEEE

CNN-Based Deep Learning Framework for Multi-Class Rice Leaf Disease Detection and Classification

Abstract: Being a major contributor to rice production worldwide, rice leaf diseases need to be detected early and correctly to achieve maximum output and reduce losses. Processes based on deep ...