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40 results for “Artificial Intelligence and Deep Learning”
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Review ArticleOpen accessIn the abstractAI-Driven Innovations in Meat Quality and Safety: Applications, Challenges, and Future DirectionsEmrobowansan Monday IdamokoroArtificial Intelligence (AI) is revolutionizing the meat sector by improving efficiency, accurateness, as well as sustainability in meat production, quality evaluation, and safety control. The conventional systems of meat inspection, handling, and processing are usually time consuming, labour-intensive, prone to contamination during handling and often susceptible to human errors. The use of artificial intelligence to drive technologies, including Deep Learning … …American Journal of Biochemistry and Biotechnology, Vol. 21, Issue 3 · 28 Jan 2026 · 3,680 accessesView PDFCite
Research ArticleOpen accessIn the abstractAdvancements In Precision Agriculture: A Review on Image-Based Stress Detection and Predictive Yield Loss ModelingA. Josephine, A. SubhashiniPrecision agriculture utilizes cutting-edge technologies to maximize the management of crops, enhance utilization of resources, and maximize yield forecasting. This study critically analyzes 53 peer-reviewed articles to evaluate advancements in image-based stress detection and yield prediction techniques for precision agriculture. The review enumerates main issues, such as image-based analysis methods, different crop stress aspects (biotic, environmental, and abiotic), and remote … …Journal of Computer Science, Vol. 21, Issue 11 · 28 Dec 2025 · 2,508 accessesView PDFCite
Research ArticleOpen accessIn the abstractRefining Chest X-ray Interpretation with Deep Transfer Learning TechniquesR. Sriramkumar, K. Selvakumar, J. JeganChest X-rays are essential diagnostic tools for thoracic diseases, but different doctors' interpretations can differ greatly, which frequently results in inconsistent diagnoses. By using deep transfer learning techniques, this study seeks to improve the accuracy of Chest X-ray interpretations. More accurate and effective analysis can be accomplished with the growing potential of artificial intelligence (AI) in medical imaging, especially through … …Journal of Computer Science, Vol. 21, Issue 10 · 27 Nov 2025 · 2,644 accessesView PDFCite
Research ArticleOpen accessIn the abstractAutomating Paddy Crop Disease Classification With Deep Learning ModelsShiva Shankar J, S. Palanivel, S. China VenkateswarluRice is a staple food crop for more than 10 countries. High consumption of rice demands better yield of crop. Timely disease diagnosis in paddy is fundamental to preventing yield losses and ensuring an adequate supply of rice for a rapidly rising worldwide population. Agriculture and modern farming is one of the fields where IoT and automation can have a … …Journal of Computer Science, Vol. 21, Issue 8 · 1 Sep 2025 · 5,696 accessesView PDFCite
Research ArticleOpen accessIn the abstractTowards a Human-Like AGI Architecture: General Intelligence Framework (GIF)Jiran Kurian Puliyanmakkal, Rohini VArtificial Intelligence (AI) has achieved significant breakthroughs but remains limited by its specialization and inability to generalize across domains, unlike human cognition. Current models such as Large Language Models (LLMs) and Multimodal Large Language Models (MLLMs) excel at specific tasks but struggle with real-time adaptability and cross-domain generalization. This paper introduces the General Intelligence Framework (GIF), an approach designed to … …Journal of Computer Science, Vol. 21, Issue 7 · 13 Jul 2025 · 4,435 accessesView PDFCite
Review ArticleOpen accessIn the abstractA Succinct Review on Identification of Network Anomalies and Protection in Cyber-Physical SystemsShalini Kumari, Chander Prabha, Prakash Srivastava et al.Advanced cyberattacks outperform traditional threat detection methods in the rapidly expanding cybersecurity field. Advanced Machine Learning (ML) algorithms can detect network traffic and system problems using AI-based Anomaly Detection (AD) for cybersecurity in real-time. Signature-based systems may overlook new and subtle threats. This paper examines Artificial Intelligence (AI) driven AD systems' design, methodology, and efficacy. The process includes data preprocessing … …Journal of Computer Science, Vol. 21, Issue 6 · 29 May 2025 · 5,234 accessesView PDFCite
Review ArticleOpen accessIn the abstractCybercrime in the AI Era: Definitions, Classification, Severity Assessment and the Role of AI in Combating ThreatsNorah Sultan Alshahrani, Fahd Saleh Alotaibi, Khaled Hamed Alyoubi, Muhammad Sher RamzanThe growing prevalence, complexity and financial impact of cybercrimes pose significant challenges for law enforcement agencies worldwide. Many organizations are utilizing different technologies such as cloud technology to improve speed, accuracy, and reliability. However, without proper security measures, the risk is still vital against cyberattacks. Cybercrime can lead to various negative outcomes, including theft, fraud, financial losses, a decline in … …Journal of Computer Science, Vol. 21, Issue 3 · 12 Feb 2025 · 7,155 accessesView PDFCite
Research ArticleOpen accessIn the abstractSuicide Ideation and Risk Detection from Social Media Using GPT ModelsSara Lasri, El Habib Nfaoui, Karima MrizikAs a reason for the sensitiveness of suicide ideation and its considerable impact on people's lives, the demand to treat and prevent the suicide ideation issue has become an obligation. Suicide ideation is a result of a combination of psychological pain and hopelessness. According to the World Health Organization, the task of reducing the global suicide mortality rate is a … …Journal of Computer Science, Vol. 20, Issue 10 · 26 Aug 2024 · 5,704 accessesView PDFCite
Research ArticleOpen accessIn the abstractThe Stanford Dependency Relations for Commonsense Knowledge Representation of Winograd Schema Challenge (WSC)Nesreen Alsharman, Raja Masadeh, Ibrahim Ali Jawarneh, Ahmad Al-Rababa’aAn alternative to the Turing Test that could offer a more accurate measurement of artificial intelligence is the Winograd Schema Challenge (WSC). It presents a number of coreference resolution issues that cannot be resolved without the use of human behavior reasoning. A certain type of Commonsense Knowledge (CSK) is necessary for Winograd schema. In order to handle the representation of … …Journal of Computer Science, Vol. 20, Issue 9 · 10 Jul 2024 · 4,743 accessesView PDFCite
Research ArticleOpen accessIn the abstractAI-Guided Anatomical Landmark and Abnormality Detection for Autonomous Endoscopy ExaminationMd Shakhawat Hossain, Munim Ahmed et al.Aabakken, L., Barkun, A. N., Cotton, P. B., Fedorov, E., Fujino, M. A., Ivanova, E., Kudo, S., Kuznetzov, K., De Lange, T., Matsuda, K., Moine, O., Rembacken, B., Rey, J., Romagnuolo, J., Rösch, T., Sawhney, M., Yao, K., & Waye, J. D. (2014). Standardized endoscopic reporting. Journal of Gastroenterology and Hepatology, 29(2), 234–240. https://doi.org/10.1111/jgh.12489 Aliyi, S., Dese, K., & Raj, … …Journal of Computer Science, Vol. 20, Issue 8 · 29 May 2024 · 6,783 accessesView PDFCite