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125 articles for “Deep learning (deep structured learning)”
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Text-to-SQL Systems: A Comprehensive Study of Evolution, Architectural Advancements, Challenges, and the Role of Large Language Models in Intelligent Query Generation
Abstract: Interacting with relational databases traditionally requires knowledge of Structured Query Language (SQL), which creates a significant barrier for users who do not have technical expertise. To address this challenge, Text-to-SQL systems have emerged as an important area of research, enabling users to express their information needs in natural language while automatically generating executable SQL queries. These systems aim to make database access more intuitive, efficient, and accessible across a wide …
Published in Journal of Advanced Database Management & Systems · Vol. 13, Issue 2, 2026 · pp. 10–19 Read article
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VolleyNexis AI: A Multimodal Artificial Intelligence Framework for Opponent Strategy Prediction, Tactical Intelligence, and Athlete Performance Optimization in Volleyball
Abstract: The rapid advancement of Artificial Intelligence (AI) has profoundly transformed sports analytics, enabling deeper insights, real-time data analysis, and enhanced performance predictions. Noticeable results have been seen by enabling automated analysis of complex gameplay patterns along with athlete performance. Volleyball is a dynamic and strategic sport, which requires continuous tactical adjustments and constant monitoring of the player’s performance. This paper presents VolleyNexis AI, which is a multimodal artificial intelligence framework …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 13, Issue 2, 2025 Read article
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A Voice Based Framework in Medical Emergency and Essential Services Using NLP (In Special Reference to People with Writing Disability)
Abstract: Natural Language Processing (NLP) has become increasingly popular in recent years as a means of organising and structuring knowledge for tasks such as translation, summarization, named entity recognition, relationship extraction, and audio recognition. The processing efficiency of NLP based systems has increased significantly with the introduction of deep learning algorithms. The COVID-19 pandemic has posed a challenge to medical research, information technology operations, corporate procedures, and the global economy. Several …
Published in Recent Trends in Programming languages · Vol. 9, Issue 2, 2022 · pp. 1–7 Read article
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Accelerating Drug Discovery with AI: Transforming the Pharmaceutical Pipeline
Abstract: The revolutionary potential of artificial intelligence (AI) is examined in this essay the pharmaceutical industry, highlighting its application across the drug development lifecycle. Artificial Intelligence, specifically via deep learning models and machine learning (ML) such as GANs, RNNs, and transformers, enhances drug discovery, formulation, toxicity prediction, and clinical trials. It streamlines processes like identification of targets, virtual screening, modelling of structure-activity relationships, and medication repurposing. AI is also employed in …
Published in Research & Reviews: A Journal of Drug Design & Discovery · Vol. 12, Issue 2, 2025 · pp. 77–84 Read article
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A Review of Machine Learning Applications in Web Data Mining
Abstract: The rapid development of Internet technology has resulted in a rapidly changing and intricate digital environment that requires new methods for organizing and evaluating online data. This study examines the use of machine learning (ML) in web data mining, focusing on its ability to extract relevant insights from huge amounts of online data. Web data mining, which is divided into three categories: content mining, structure mining, and use mining, uses …
Published in International Journal of Data Structure Studies · Vol. 3, Issue 1, 2025 · pp. 39–47 Read article
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Deep Learning Architectures for Predictive Modeling in Financial Time Series
Abstract: This study investigates the application of deep learning architectures, particularly convolutional neural networks (CNNs), to the challenging task of financial time series forecasting. Financial markets are inherently complex and influenced by a range of factors, making accurate prediction of price movements a difficult problem. In this research, historical financial data including stock prices, volumes, and other relevant indicators are used to train CNN models aimed at capturing the underlying patterns …
Published in Current Trends in Signal Processing · Vol. 15, Issue 3, 2025 · pp. 45–55 Read article
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Advancements in AI-Driven Diagnostics for Dental Health: A Comprehensive Review
Abstract: Dental diseases, also known as oral diseases or dental conditions, encompass a range of health problems affecting the teeth, gums, mouth, and associated structures. These conditions can lead to pain, discomfort, and severe complications if left untreated. Early detection and accurate diagnosis are crucial for effective treatment and prevention of further complications. This comprehensive literature review aims to identify common dental problems such as Tooth Decay (Cavities), Gingivitis, Periodontitis, and …
Published in Current Trends in Signal Processing · Vol. 14, Issue 2, 2024 · pp. 1–7 Read article
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Generative Design of Bioactive Orthopedic Composites for Fracture Repair Using an Integrated Conditional GAN–Transformer Framework: A Multi-Objective Approach
Abstract: Orthopedic composite implants for fracture repair must simultaneously satisfy conflicting mechanical and biological demands: high fracture toughness, sufficient compressive stiffness, and bioactive surface chemistry enabling osteoblast adhesion and mineralization. Existing design approaches rely on trial-and-error experimentation, yielding sub-optimal trade-offs between these objectives. This paper presents an integrated conditional Generative Adversarial Network–Transformer (cGAN-T) framework for fully computational, multi-objective generative design of hydroxyapatite (HA)-reinforced polymer composite microstructures targeting Orthopedic fracture repair. A …
Published in Journal of Polymer & Composites · Vol. 14, Issue 4, 2026 · pp. 21–35 Read article
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Applications of Machine Learning Algorithms in Health Data Science (HDS) for Next Research Directions: A Survey Report
Abstract: At present time, data science is the big trend in computer science. The functioning of this technology is purely based on other advanced technology known as machine learning (ML). Data science and ML are subsets of artificial intelligence (AI). When a process of data science is used in healthcare systems, the new system is known as health data science (HDS). HDS is a branch of data science used to handle …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 11, Issue 1, 2024 · pp. 16–21 Read article
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AI for Cybersecurity: Deploying Machine Learning for Network Traffic Anomaly Detection
Abstract: The growing sophistication of cyberattacks and the growth of network traffic necessitate sophisticated anomaly detection methods. This study overviews the use of artificial intelligence (AI) and machine learning (ML) to counter these challenges, as noted in current studies. It analyses supervised learning (SVM, Decision Trees), unsupervised learning (K-means, DBSCAN), and deep learning (CNNs, RNNs, Auto-encoders) approaches, considering their strengths and weaknesses. The research integrates current developments in AI/ML-based network anomaly …
Published in International Journal of Computer Science Languages · Vol. 3, Issue 2, 2025 · pp. 1–10 Read article
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Revolutionizing Vaccine Development:The Transformative Role of Bioinformatics in Designing Next-Generation Immunotherapies
Abstract: Vaccines have long been central to the prevention and control of infectious diseases, dramatically reducing morbidity and mortality worldwide. In the modern era, the integration of bioinformatics has revolutionized vaccine development by enabling rapid, precise, and cost-effective identification of potential vaccine targets. This seminar explores the multifaceted applications of bioinformatics in vaccinology, including antigen discovery, epitope prediction, structural modeling, molecular docking, and immunoinformatics-driven vaccine design. Special emphasis is placed on …
Published in Research & Reviews: A Journal of Bioinformatics · Vol. 12, Issue 3, 2025 · pp. 19–33 Read article
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Innovations in Civil Engineering: Advancing Infrastructure through AI Technology
Abstract: A comprehensive exploration of the intersection of civil engineering and artificial intelligence (AI) technology, highlighting the transformative impact of AI on infrastructure development, management, and sustainability. The journal encompasses a wide array of research articles, case studies, and reviews that demonstrate the integration of AI into various facets of civil engineering, including but not limited to smart infrastructure, predictive maintenance, structural analysis, and urban planning. By showcasing cutting-edge applications and …
Published in Journal of Structural Engineering and Management · Vol. 11, Issue 2, 2024 · pp. 1–11 Read article
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A Comprehensive Tool for Authenticating Instagram Profiles Using Instaloader
Abstract: With the rapid growth of Instagram as a dominant social media platform, there is an increasing need for tools that allow users to extract, analyze, and monitor profile data efficiently. Instagram has become one of the leading platforms for personal branding, influencer marketing, business promotion, and public communication. As businesses and individuals seek to better understand their presence and influence on this platform, the need for reliable data extraction tools …
Published in Journal of Computer Technology & Applications · Vol. 16, Issue 2, 2025 · pp. 93–98 Read article
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E-Commerce Clothing Platform with Virtual Try-On
Abstract: The inability to physically evaluate garments remains a major limitation in online clothing commerce. Customers often depend on static product images and generalized sizing charts, which do not accurately represent individual body proportions. This frequently leads to uncertainty during purchase decisions and increased product return rates. To address this limitation, this research proposes a web-based clothing e-commerce platform integrated with an intelligent virtual try-on mechanism. The system allows users to …
Published in E-Commerce for Future & Trends · Vol. 13, Issue 1, 2026 · pp. 17–24 Read article
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Customer Preference About Tourism using Opinion Based Mining/Sentiment Analysis
Abstract: The article can help researchers and practitioners who want to collect, gather and analyse social media data. Innovation and the Internet have significantly modified how travel is booked, the relationship between travellers and the travel industry, and how vacationers share their travel experiences. Because of this assortment of choices, mass the travel industry markets have been scattering. Be that as it may,the worldwide interest has not fallen; a remarkable opposite, …
Published in Journal of Mobile Computing, Communications & Mobile Networks · Vol. 8, Issue 3, 2021 · pp. 24–28 Read article
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e-learning Platforms in Higher Education: An Analysis of Institutional Planning, Implementation and Evaluation Strategies
Abstract: This quantitative study investigates the impact of e-learning platforms on student learning outcomes in higher education, focusing on institutional planning, implementation, and evaluation strategies. A descriptive-correlational research design was employed, surveying 100 administrators, faculty, and students from various higher education institutions. The results show significant positive correlations between platform organization, user-friendliness, instructor feedback, technical support, and student motivation. Well-structured platforms with clear communication of learning objectives, quality technical support, and …
Published in International Journal of Education Sciences · Vol. 2, Issue 2, 2025 · pp. 41–49 Read article
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Performance Analysis of Deep CNN Architectures
Abstract: A Convolutional Neural Network (CNN) is an artificial neural network renowned for its remarkable ability to handle large image datasets effectively, particularly excelling in tasks such as image recognition and classification. The fundamental structure of a CNN relies on mathematical convolution operations, comprising essential components such as convolutional layers, activation functions, pooling layers, and fully connected layers. These components work synergistically to extract and learn hierarchical features from input data, …
Published in Journal of Communication Engineering & Systems · Vol. 14, Issue 2, 2024 · pp. 1–8 Read article
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Enhancing Image Classification Performance with Deep Neural Networks
Abstract: Classifying images is useful in many domains, including the study of plant diseases and the analysis of human expressions. Image categorization employing the idea of a “deep neural network” helps to compact otherwise cumbersome photos. It is possible to classify images by using the idea of a “deep neural network”. Self-driving cars, medical diagnosis, automatic translation, etc., all make use of Deep Neural Networks. Recently, excellent results have been achieved …
Published in Journal of Telecommunication, Switching Systems and Networks · Vol. 11, Issue 1, 2024 · pp. 13–23 Read article
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A Split and Merge UNet: A Deep Learning Assisted UNet Model to Segment Corpus Callosum of Brain for Automatic Autism Detection
Abstract: In recent years, deep learning techniques have shown remarkable performance in various image analysis applications, particularly in the domain of medical image processing. Among these, image segmentation plays a critical role, as it helps in isolating and analyzing specific regions within medical images. The proposed study focuses on segmenting the corpus callosum, a vital structure in the human brain, using a novel optimization technique known as the Split and Merge …
Published in Journal of Multimedia Technology & Recent Advancements · Vol. 11, Issue 3, 2024 · pp. 1–9 Read article
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AI-Driven Prediction of Square-Hole Laser Trepanning Performance in AA7075/15%SiC/15% Glass Fiber Hybrid Composites Using Taguchi–ANOVA and Deep Neural Networks
Abstract: Hybrid AA7075 composites reinforced with 15% silicon carbide (SiC) and 15% glass fiber were fabricated via the stir casting technique to improve machining and structural performance. The addition of dual reinforcements into the aluminum matrix was aimed at enhancing hardness, thermal stability, and surface quality during non-traditional drilling operations. Square-hole drilling was performed using a laser trepanning process, and the key responses—hole size accuracy, surface roughness, and taper angle—were systematically …
Published in Journal of Polymer & Composites · Vol. 14, Issue 1, 2026 · pp. 1932–1943 Read article