IEEE

A Deep Learning Framework for Network Intrusion Detection Using hybrid CNN-BiGRU-Multi-Head Attention model

Abstract: This paper describes a fresh IDS framework that utilizes CNN and BiGRU and Multi-Head Attention techniques to develop an improved deep learning approach for network protection from changing ...
IEEE

Innovative Lightweight CNN Model for Stage-Wise Alzheimer's Disease Detection

Abstract: A common neurological condition that causes cognitive decline, particularly in older people, is Alzheimer's disease (AD). In order to improve patient treatment and minimize the progression ...
IEEE

Power Load Forecasting Based on GA-Optimized CNN-LSTM Model

Abstract: This paper proposes a short-term load forecasting method based on a GA-optimized CNN-LSTM model. The model combines the strengths of CNN in extracting local spatial features and LSTM in ...
IEEE

An Attention-Augmented BiLSTM-CNN Model for Stock Price Prediction

Abstract: The inherent volatility of the stock market has challenged investors in seeking reliable predictive models. This paper presents a hybrid deep learning model that combines bidirectional long ...
IEEE

Harnessing Temporal Awareness: Dual-CNN Model for Non-Intrusive Load Monitoring

Abstract: Thoroughly monitoring the energy consumption of each appliance in a household is essential to assist users in better engaging in power-saving practices. To get per-appliance electrical ...
IEEE

Deep Learning Approaches to Babylonian Numeral Recognition: A CNN-SVM Hybrid Model

Abstract: This paper presents a novel deep learning framework for classifying Babylonian numerals by integrating Convolutional Neural Networks (CNNs) with a hybrid CNN-SVM model. The core ...
IEEE

An Innovative Hybrid Model Combining CNN and Random Forest for Financial Transaction Analysis

Abstract: Financial fraud is a growing concern in digital transactions, with traditional fraud detection systems struggling to keep up with evolving fraudulent tactics. This study proposes a hybrid ...
IEEE

Hybrid CNN-ViT Model for Intracranial Hemorrhage Detection and Classification in DICOM Images

Abstract: Intracranial hemorrhage (ICH) refers to bleeding within the brain, a global concern that underscores the im-portance of early detection. ICH is typically detected using computed tomography ...
IEEE

Parallel Fusion CNN Enabled Data-Driven Nonlinear Model on Time-Frequency Characterization for Power Quality Analysis

Abstract: Modeling of nonlinear loads is crucial for analyzing and evaluating power quality in modern power system. To further enhance both accuracy and robustness, a novel data-driven nonlinear load ...
IEEE

Optimizing Facial Acne Detection: Evaluating CNN, ResNet, and EfficientNet Models

Abstract: Acne is a widespread dermatological condition, affecting approximately $85-90 \%$ of adolescents and young adults, with studies indicating that over 50 % of those affected experience ...
Communications of the ACM

The ‘Matrix’ for Machines

Kamal Mann is a Software Architect with over 22 years of experience in Industry 4.0 systems. He currently advises on edge ...
IEEE

Deep Learning-Based Multiclass Classification of Rice Seed Germination Status Using CNN Models

Abstract: The quality of rice seeds is crucial to agricultural productivity and food security. Traditional methods of determining seed germination status—classifying seeds as normal, abnormal, fresh ...