Sign inSubmit
Tips: “quotes” for a phrase · author:Lee · a DOI goes straight to its article

19 articles for “Deep Learning Robustness”
Set a search alert
Research ArticleOpen accessIn the abstractDeep Sense: Deep Learning for Early Staging the Onset of Diabetes Emanating Recognition of Activity PatternsMohammed Shamsul Alam, Erfanul Hoque Bahadur, Md Fokrul Islam Khan et al.This study presents a comprehensive framework for Human Activity Recognition (HAR) using smartphone sensor data, with a specific focus on identifying activities associated with diabetic risk factors. We investigate the efficacy of two deep learning architectures (Long Short-Term Memory (LSTM) networks and Graph Convolutional Networks (GCNs)) for activity recognition under conditions of limited training data. To address data scarcity, we … …Journal of Computer Science, Vol. 21, Issue 10 · 15 Dec 2025 · 2,268 accessesView PDFCite
Research ArticleOpen accessIn the abstractEnhancing E-Banking Security and Personalization through Convolutional Neural Network-Based Facial RecognitionRamy Kamal Amin, Ghada A. El Khayat, Farid El Sahn, Abeer A. AmerFacial recognition technology has become a cornerstone in enhancing the security and user experience of electronic banking services. Its ability to provide a seamless yet secure authentication method is vital in combating fraud and maintaining the integrity of online financial transactions. This study presents the development of an advanced electronic banking system that strengthens security through the integration of a … …Journal of Computer Science, Vol. 21, Issue 10 · 7 Dec 2025 · 3,310 accessesView PDFCite
Review ArticleOpen accessIn the abstractDDoS Mitigation Using Machine Learning in Software-Defined NetworksAhmed Gaber Abu Abd-Allah, Noureldin Omar Mohamed, Mohamed Samir Mohamed et al.With the escalating frequency and sophistication of Distributed Denial of Service (DDoS) attacks, the realm of cyber security has witnessed a paradigm shift towards innovative solutions. This review explores the potential of machine learning as a powerful defense mechanism in the field of DDoS mitigation within Software-Defined Networks (SDNs). The study methodically examines a variety of machine learning algorithms used … …Journal of Computer Science, Vol. 21, Issue 4 · 23 Mar 2025 · 6,774 accessesView PDFCite
Research ArticleOpen accessIn the abstractDeep Learning Approach to Mitigate DDoS Attacks in SDNHema Surendrakumar Dhadhal, Paresh Kotak, Parvez Faruki, Atul GonsaiThe rise of Distributed Denial of Service (DDoS) attacks remains a significant obstacle to network security and availability. This abstract presents a new hybrid model for DDoS mitigation in Software-Defined Networking (SDN) environments, combining a Semi-supervised Deep Extreme Learning Machine (Semi-Deep ELM) with a hybrid architecture. SDN's centralized control and programmability create an ideal platform for implementing advanced mitigation strategies. … …Journal of Computer Science, Vol. 20, Issue 9 · 5 Jul 2024 · 5,338 accessesView PDFCite
Research ArticleOpen accessIn the abstractDeep Learning Models for Speech Emotion RecognitionV.M. Praseetha, Sangil VadivelEmotions play a vital role in the efficient and natural human computer interaction. Recognizing human emotions from their speech is truly a challenging task when accuracy, robustness and latency are considered. With the recent advancements in deep learning now it is possible to get better accuracy, robustness and low latency for solving complex functions. In our experiment we have developed … …Journal of Computer Science, Vol. 14, Issue 11 · 26 Nov 2018 · 8,768 accessesView PDFCite
Research ArticleOpen accessAll words, across the recordModified U-Net With VGG11-BN Encoder and Frost Filter Based Pre-Processing for Copy Move Forgery LocalizationAshutosh Pandey, Niranjan Lal, Ashish Kumar ChakravertiCopy-move forgery is a widely used forgery method in digital image forensics, which involves copying and pasting a part of an image into another part of the image to hide or duplicate the visual information. This makes it difficult to detect such manipulations, particularly when the regions are subjected to geometric and photometric transformations. A Frost Filter-Enhanced Encoder-Decoder U-Net is … …Journal of Computer Science, Vol. 22, Issue 10 · 6 Oct 2026 · 457 accessesView PDFCite
Research ArticleOpen accessAll words, across the recordImplementing a Hybrid VMD–BiTCN–BiGRU Architecture With Intelligent Optimization for Agricultural Commodity Price Prognostication in Gujarat MarketsJignesh Hirapara, Ratnesh Kumar Namdeo, Ankit Kumar Dubey et al.In the agricultural sector, the prices of pulses require adequate forecasting to plan farming activities, store and market, and guide policy-making. However, the pulse price series is highly volatile, seasonal, nonstationary, and nonlinear, and thus conventional linear time series models are not necessarily very effective. In the suggested framework, the raw price data series is decomposed using Variational Mode Decomposition … …Journal of Computer Science, Vol. 22, Issue 7 · 1 Aug 2026 · 1,021 accessesView PDFCite
Research ArticleOpen accessAll words, across the recordIntelligent Traffic Light System Using Convolutional Neural Network to Optimize Vehicle Flow in IndonesiaBhustomy Hakim, Fergie Joanda Kaunang, Yemima Monica Geasela, Regina HillaryTraffic congestion remains a persistent challenge in major Indonesian cities due to rapidly increasing vehicle density and the continued reliance on fixed-time traffic signal scheduling. This study aims to develop an intelligent traffic light system that dynamically adjusts sequencing based on real-time road conditions. A dataset of 902 CCTV images was collected from intersections in six large cities across Indonesia, … …Journal of Computer Science, Vol. 22, Issue 2 · 17 Feb 2026 · 2,155 accessesView PDFCite
Research ArticleOpen accessAll words, across the recordAutism Spectrum Disorder Prediction Using Hybrid Deep Learning Model and a Recommendation System Application for Autistic PatientBiplov Paneru, Bishwash Paneru, Krishna Bikram Shah et al.The goal of this study is to create machine learning models that use a big dataset to predict Autism Spectrum Disorder (ASD). To achieve optimal performance, a number of algorithms were employed and refined, including Support Vector Machines (SVM), Random Forest, XGBoost, Multi-Layer Perceptron (MLP) and a hybrid model that combines MLP and SVM. To evaluate the durability of the … …Journal of Computer Science, Vol. 20, Issue 9 · 6 Jul 2024 · 6,219 accessesView PDFCite