Search
10 articles for “geometric deep learning”
-
Harnessing Artificial Intelligence for Precision Physics: A Machine Learning Framework for Data Reconstruction in Support of India's Deep-Tech Missions
Abstract: India's emergence as a global leader in deep-tech innovation is driven by ambitious scientific megaprojects, including the Laser Interferometer Gravitational-Wave Observatory (LIGO)-India, the X-ray Polarimeter Satellite (XPoSat), the Aditya-L1 solar observatory, and the National Quantum Mission (NQM). However, the unprecedented scale and complexity of the observational data generated by these missions present severe computational bottlenecks. Traditional analytical frameworks struggle with non-stationary noise transients, diffusion blurring, and the exponential scaling limits …
Published in Research & Reviews : Journal of Physics · Vol. 15, Issue 2, 2026 · pp. 48–55 Read article
-
A Study on Various Approaches in Remote Sensing
Abstract: AbstractThis paper studies the various approaches used in the remote sensing. The importance of Remote Sensing is that to learn to extract valuable information from it. The traditional approach has been to analyse RS images and then construct information-extraction models, these approaches are able to construct spectral, textural and geometric attributes of images. The various approaches using machine language, deep learning, Zigbee platform and microwave sensing is discussed here.Keywords: RS …
Published in Journal of Telecommunication, Switching Systems and Networks · Vol. 7, Issue 2, 2020 · pp. 32–37 Read article
-
Intelligent Brain Tumor Diagnosis with AI-Based Classification* * Harnessing Deep and Machine Learning for Tumor Identification
Abstract: Brain tumors have become a leading cause of cancer- related deaths, posing significant health risks to many patients. This urgent medical challenge calls for rapid, automated, and reliable techniques to detect brain tumors accurately. Timely and precise tumor identification is crucial for devising effective medical plans that have the potential to save lives and improve patient outcomes. By leveraging advanced image processing methods, healthcare professionals can enhance their diagnostic capabilities …
Published in International Journal of Cell Biology and Cellular Functions · Vol. 4, Issue 1, 2026 Read article
-
Facial Emotion Detection and Its Applications
Abstract: Facial emotion detection (FED) is an interdisciplinary field that integrates artificial intelligence, computer vision, and machine learning to recognize and interpret human emotions based on facial expressions. The development of FED systems has been propelled by advancements in deep learning, particularly convolutional neural networks (CNNs) and recurrent neural networks (RNNs), which enhance recognition accuracy. Feature extraction techniques, including geometric and appearance-based methods, play a crucial role in classifying emotional states. …
Published in International Journal of Optical Innovations & Research · Vol. 3, Issue 1, 2025 · pp. 8–12 Read article
-
ML-Driven Optimization Framework for the Analysis, Design, and Development of Efficient Wireless Power Transfer Systems for EV Charging
Abstract: The fast uptake of electric vehicles (EVs) has heightened the necessity of effective, dependable and convenient charging systems. The Wireless Power Transfer (WPT) systems can be taken as a potential solution as they allow charging cells without contact, without any risks, and without any overcrowding; the efficiency of the system is strongly influenced by the alignment of coils, the fluctuations of air-gaps, the conditions of the loads, and geometrical arrangements …
Published in International Journal of Manufacturing and Production Engineering · Vol. 4, Issue 1, 2026 · pp. 1–9 Read article
-
Autonomous Agentic AI for Adaptive Cure Optimization and Defect Prevention in Thermoset Polymer Composite Manufacturing
Abstract: Thermoset polymer composites occupy a central position in modern structural manufacturing, from aircraft fuselages to wind-turbine blades. Despite progress in resin chemistry and fiber architecture, the “cure process” that transforms compliant preforms into load-bearing structures remains difficult to manage. Manufacturers encounter ‘voids’, “interlaminar delaminations”, and “spring-back distortion” when curing complex or thick-section parts. The cause is not ignorance of the relevant physics, but rather that ‘temperature’, ‘chemistry’, ‘rheology’, and ‘mechanics’ …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 301–320 Read article
-
Intelligent Electromagnetic Synthesis: An AI-Driven IoT Framework for Adaptive Antenna Design in Missile Navigation
Abstract: The rapid evolution of hypersonic and long-range tactical missile systems necessitates antenna architecture capable of maintaining robust communication links under extreme thermal, mechanical, and signal-jamming environments. Traditional antenna design methodologies often relying on iterative simulation cycles and static optimization are increasingly insufficient for the real-time requirements of modern aerospace navigation. This paper proposes an AI-driven, IoT- integrated framework that facilitates autonomous antenna design and performance optimization. By deploying a distributed …
Published in International Journal of Radio Frequency Innovations · Vol. 4, Issue 1, 2026 Read article
-
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
-
Comparative Analysis of Data Augmentation Techniques in CNN-based Classification of Atelectasis
Abstract: This research delves into the critical issue of atelectasis, its causes, and potential complications if left untreated. Leveraging deep learning algorithms, particularly convolutional neural networks (CNN), the paper explores their application in medical image analysis, focusing on the detection of atelectasis using the “chestX-ray8” database. The study compares various data augmentation techniques for improved accuracy, showcasing the importance of augmentation in enhancing model generalization. Through meticulous experimentation and evaluation, the …
Published in Journal of Microwave Engineering and Technologies · Vol. 11, Issue 3, 2024 · pp. 1–8 Read article
-
Artificial Intelligence in Trigonometry: Innovations, Applications, and Future Prospects
Abstract: Artificial Intelligence (AI) has transformed numerous scientific fields, yet its integration with classical mathematics such as trigonometry is still emerging. This paper explores how AI enhances trigonometric problem solving, learning, and real-world applications. We analyse AI-driven tools for teaching trigonometry, AI in geometric and spatial reasoning, usage in robotics and computer vision, and future directions for research. Key challenges, methodologies, and case studies are discussed to provide a comprehensive overview …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 13, Issue 3, 2025 Read article