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

300 results for “Artificial Intelligence”
Set a search alert
Research ArticleOpen accessPhrase in the titlePerson Re-Identification From Video Surveillance Systems Using Artificial Intelligence MethodsRevathi Lavanya Baggam, Vatsavayi Valli KumariThe study explores use of deep learning models in person re identification, leveraging the advancements made in face recognition however the abundance of model choices presents a challenge in selecting the optimal architecture. The study proposes a comprehensive framework for evaluating deep learning models on person re-identification tasks by considering various performance metrics, dataset preprocessing methods, model architectures, and evaluation … …Journal of Computer Science, Vol. 21, Issue 8 · 19 Sep 2025 · 4,836 accessesView PDFCite
Research ArticleOpen accessPhrase in the titleArtificial Intelligence Based Three-Phase Unified Power Quality ConditionerMoleykutty GeorgePower quality is an important measure of the performance of an electrical power system. This paper discusses the topology, control strategies using artificial intelligent based controllers and the performance of a unified power quality conditioner for power quality improvement. UPQC is an integration of shunt and series compensation to limit the harmonic contamination within 5 %, the limit imposed by … …Journal of Computer Science, Vol. 3, Issue 7 · 31 Jul 2007 · 6,911 accessesView PDFCite
Research ArticleOpen accessPhrase in the titleVHDL DESIGN AND HARDWARE REALIZATION OF HYBRIDARTIFICIAL INTELLIGENCE ARCHITECTURERajeswaran Nagalingam, Tenneti Madhu, Munagala SuryakalavathiEvolutionary Algorithms (EA) use Genetic Algorithm (GA) in many optimization problems to efficiently compute the function value in less time. In this study the weight optimization of the Artificial Neural Net-work (ANN), using the Back Propagation Network (BPN), is tested and presented with GA. The combined architecture of Neuro-Genetic (Hybrid Artificial Intelligence) approach is proposed and simulated results are provided … …American Journal of Applied Sciences, Vol. 11, Issue 5 · 24 Feb 2014 · 6,566 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleA Data-Sharing Model to Secure Borders Using an Artificial-Intelligence-Based Risk Engine and Big-Data ConceptsMohammad S. Al Rousan, Benedetto IntrigilaThe primary aim of this research is to develop a framework for data management and sharing that will enable countries to share complex data about known and unknown high-risk passengers to streamline border-control security processes through the use of big data analytics and Artificial Intelligence (AI). A total of 15 semi-structured interviews were used to gather qualitative data. A thematic … …American Journal of Applied Sciences, Vol. 19, Issue 1 · 2 May 2022 · 6,937 accessesView PDFCite
Review ArticleOpen accessEvery word in the titleAn Overview of Artificial General Intelligence: Recent Developments and Future ChallengesKhalid Alattas, Ahmed Alkaabi, Alanoud Bandar AlsaudThe defense sphere of Artificial General Intelligence (AGI) is developing exponentially. Notwithstanding, there is an under the definition of the character of human beliefs pertaining to AGI associations. Distinctive AGI protection scholars formulated numerous hypotheses regarding the existence of human beliefs, but contradictions exist. This study provides an analysis of what AGI protection scholars, up to the beginning of 2019, … …Journal of Computer Science, Vol. 17, Issue 4 · 15 Apr 2021 · 7,950 accessesView PDFCite
Research ArticleOpen accessIn the keywordsExplainability Aware Heterogeneous Temporal Graph Transformer for Automated Genetic Disorder Detection from Genomic DataPuvaneswari Subramaniapillai, Indirani Govindasamy, Revathy GurumurthyGenetic disorders affect millions worldwide, posing major challenges for accurate diagnosis and effective treatments. New developments in genomic technologies, especially Next-Generation Sequencing (NGS), have enhanced the classification of genetic modification and improved diagnostic abilities. Moreover, the Machine Learning (ML) and Deep Learning (DL) methods emerged as efficient tools for evaluating the intricate genomic data and determining the patterns, which can … …Journal of Computer Science, Vol. 22, Issue 11 · 14 Oct 2026 · 566 accessesView PDFCite
Research ArticleOpen accessIn the keywordsA Machine Learning Framework for Strategic Gameplay Optimization in Scrabble Using Reinforcement LearningMohd Kaleem, Kanta Prasad Sharma, Tapsi Nagpal et al.This paper explores and compare various artificial intelligence-based techniques used for playing classic board game Scrabble. As the world is evolving around finding quick and efficient techniques for the solution of each problem using Machine learning, gaming industry is also a flourishing industry and has grown 9.8% compared to previous year and has generated a revenue of 26.14 billion dollars … …Journal of Computer Science, Vol. 22, Issue 9 · 22 Sep 2026 · 666 accessesView PDFCite
Research ArticleOpen accessIn the keywordsThe Impact of Design and Security on Generation Z’s Continuance Intention in the AI-Enhanced MetaverseShailja TripathiArtificial Intelligence (AI) and the Metaverse are the source of quick and extensive changes in the virtual world. Unfortunately, such a point is rarely discussed in the academic community and the reasons why users may be able to accept an AI-enhanced Metaverse environment are not well explored. The purpose of this study is to further reconnoiter the relationship between AI … …Journal of Computer Science, Vol. 22, Issue 9 · 21 Sep 2026 · 609 accessesView PDFCite
Research ArticleOpen accessIn the keywordsForecasting Corporate Financial Distress Using Explainable Machine Learning: Implications for Risk Management TechnologyKanjana Hinthaw, Warawut NarkbunnumFinancial distress prediction is a critical task in financial risk management, yet it remains challenging due to class imbalance, complex financial structures, and limited model interpretability. This study develops an integrated machine learning framework that combines feature selection, class imbalance handling, threshold optimization, and Explainable Artificial Intelligence (XAI) to improve both predictive performance and decision-making reliability. Using a dataset of … …Journal of Computer Science, Vol. 22, Issue 7 · 22 Jul 2026 · 1,130 accessesView PDFCite