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398 articles for “Neural Network Techniques”
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Hybrid Numerical–Artificial Neural Network Study of Chemically Reactive MHD Nanofluid Flow Incorporating Thompson–Troian Slip and Stefan Blowing
Abstract: Boundary layer behaviour in chemically reactive nanoliquid is significantly affected by surface conditions, magnetic fields, heat and mas transfer mechanisms. However, the combined impact of Stefan blowing and nonlinear Thompson–Troian slip under inclined magnetic fields remains mostly unexplored, particularly in mixed convection flows. In this research work, the flow of a chemically reactive nanoliquid over a permeable surface is investigated by considering the Troian slip, inclined magnetic fields, Stefan blowing, …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 409–425 Read article
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ANN Controlled Plasma Spray Process by using Industrial Waste
Abstract: Plasma spray coating process has become a subject of intense research because it becomes an affordable solution for many industrial applications. The present work aims at developing and studying the industrial wastes (Flay-ash powder mixture) as the coating material, which is to be deposited on Mild Steel and Cupper substrates. To increase the coating deposition efficiency and to decrease the cost of coating process, one of the artificial intelligence (AI) …
Published in Journal of Materials & Metallurgical Engineering · Vol. 3, Issue 3, 2013 · pp. 1–6 Read article
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Artificial Intelligence Based Plant Disease Detection
Abstract: This paper analyses the advanced Neural Network (NN) techniques for hyperspectral data processing, with a particular focus on detecting plant disease. To initiate, we will discuss the NN mechanism, types, models, and classifiers that are used to process the hyperspectral data using different algorithms. Following that, this project discusses the current state of imaging and non-imaging hyperspectral data for early screening and diagnosis of Disease. The NN-hyperspectral hybridization method has …
Published in Recent Trends in Programming languages · Vol. 8, Issue 3, 2021 · pp. 11–24 Read article
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COVID-19 Detection through Deep Learning Models using Chest X-ray
Abstract: Detection of COVID-19 in a minimum amount of time is one of the biggest challenges in front of us because COVID-19 is a rapidly spreading disease. Patients are increasing in a rapid amount of time. Hence, we proposed an AI-technique based deep-convolutional neural network to detect COVID-19 patients using real-world data. In our proposed system, chest X-ray images are used to find out COVID- 19 patients. X-rays are available very …
Published in Journal of Advancements in Robotics · Vol. 8, Issue 2, 2021 · pp. 11–16 Read article
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Fault Identification by Wavelet Feature Extraction in Self Aligning Rolling Element Bearings Using Neural Networks
Abstract: This paper aims to present a comparison of different individual defects in self aligning ball bearings by the use of statistical tools and machine learning techniques like artificial neural network (ANN). The results generated are analyzed, and more realistic conformance to the theoretical observations has been drawn. Vibration analysis of a fault affected component gives a good understanding of machine diagnostics. Inner race and outer race defects have been studied …
Published in Trends in Mechanical Engineering & Technology · Vol. 7, Issue 2, 2017 · pp. 11–17 Read article
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Implementation of Human Gesture Recognition Using CNN
Abstract: A gesture popularity system based entirely on convolutional neural networks (CNNs). Preprocessing techniques include segmentation, polygonal approximation, contour construction, morphological filters, and resource characteristic extraction. Various convolutional neural networks are employed for training and testing, with results compared to existing architectures and protocols. All generated measurements and convergence graphs produced at any point during education are examined and contested in order to verify the reliability of the approach offered. Our …
Published in Journal of Control & Instrumentation · Vol. 15, Issue 2, 2024 · pp. 24–37 Read article
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Data Mining Techniques Used in Prediction of Heart Diseases
Abstract: AbstractHeart disease is a big life minatory ailment that cause to demise. It has deep long-term incompetence. There is a huge amount of data available within our system. Nevertheless, we are unable to find hidden relationship and prosperity in data. KDD (knowledge discovery in database) process, data mining consists of various techniques to convert these mounds of data into useful decision-making information. Data mining takes less time for the prediction …
Published in Journal of Advanced Database Management & Systems · Vol. 6, Issue 3, 2019 · pp. 9–11 Read article
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Speech Emotion Recognition using Convolutional Neural Networks
Abstract: This research work presents an assortment of techniques in Speech Emotion Recognition with the help of spectrograms and handcrafted Deep learning architecture: Convolutional Neural Networks (CNN). Emotional kingdom detection is a crucial part of human-device interplay studies. To make interaction between man and machine more natural, many milestones are conquered in speech emotion recognition, but still this process requires more up-to-the-mark results. To make an attempt for the same, this …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 8, Issue 3, 2021 · pp. 26–32 Read article
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Review Paper on Efficient Quality Inspection of Food Products Using Neural Network Classification
Abstract: AbstractWith the increasing competiveness in the field of food production growing at a faster pace across the globe, quality is one of the most desirable features that a product should possess. The ability to produce quality as well as safety food is the most prerequisite factors for both, national and international market. This paper explains the recently developed approaches and latest research efforts related to the assessment of the quality …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 4, Issue 1, 2017 · pp. 1–14 Read article
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Feature Fusion Based Iris and Retina Recognition System Using Kohonon Self-Organizing Mapping Neural Network Algorithm
Abstract: This paper proposes a model of biometric security with feature fusion based iris and retina recognition system. Though, a lot of research works have done for iris recognition system and it is not new for the fusion of multimodal iris recognition in the area of biometric security and authentication system. But, it is a relatively new idea of mixing iris and retina features for human authentication. Here, the features of …
Published in Trends in Electrical Engineering · Vol. 5, Issue 2, 2015 · pp. 22–26 Read article
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AI-Based House Price Prediction
Abstract: The housing market is one of the most dynamic and significant sectors of any economy, influencing both individual wealth and broader economic stability. Buyers, sellers, investors, and policymakers all rely on accurate housing price predictions. With the advent of artificial intelligence (AI) technologies, particularly machine learning algorithms, the task of house price prediction has seen remarkable advancements. This study provides a detailed overview of AI-based techniques for house price prediction. …
Published in Current Trends in Signal Processing · Vol. 13, Issue 3, 2023 · pp. 1–7 Read article
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Prediction of Compressive Strength of Concrete Using Machine Learning Techniques
Abstract: Compressive strength of concrete is an important parameter for designing any concrete structure. Compressive strength of concrete is a complex nonlinear function of its ingredients. Prediction of Concrete compressive strength plays a vital role in pre design phases of the structure and quality control of construction. The conventional methods of compressive strength determination are time consuming, so the use of data mining methods to predict the strength beforehand is helpful. …
Published in Journal of Construction Engineering, Technology & Management · Vol. 5, Issue 3, 2015 · pp. 34–41 Read article
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Automated Crop Disease Detection Using Convolutional Neural Networks
Abstract: Crop diseases contribute to major losses in agricultural production worldwide generating enormous economic costs. This study investigates the possibility of Convolutional Neural Networks (CNN) imaging techniques to auto-detect diseases associated with plants through image processing. A model was developed and trained on a publicly available plant disease dataset containing labeled images of several diseases. The CNN could classify various plant diseases with accuracy of 95%, precision of 92%, and recall …
Published in International Journal of Cheminformatics · Vol. 3, Issue 2, 2025 · pp. 7–15 Read article
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Interpretable Skin Cancer Detection via Optimized CNN Models for Smart Healthcare Solutions
Abstract: Skin cancer is a common and potentially life-threatening condition, highlighting the importance of reliable and efficient diagnostic techniques. Recently, convolutional neural networks (CNNs) have demonstrated significant potential in automating the classification of skin cancer using thermoscopic images. Despite these advancements, the lack of interpretability in these models poses a barrier to their widespread use in clinical settings. In this study, we propose an interpretable CNN architecture optimized for skin cancer …
Published in Research & Reviews: A Journal of Bioinformatics · Vol. 12, Issue 1, 2025 · pp. 41–45 Read article
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Achieving Multi-objectives Using a Single Neural Network
Abstract: Achieving multi-objectives using a single neural network is a research area that aims to develop techniques to optimize multiple objectives simultaneously using a single neural network. This approach can be applied in various fields, such as image and speech recognition, robotics, and natural language processing, to achieve better performance and reduce the complexity of the models. The key challenge in this area is to balance the trade-off between different objectives …
Published in Research & Reviews: Discrete Mathematical Structures · Vol. 9, Issue 3, 2022 · pp. 1–15 Read article
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EMBEDDED CONTROLLER FOR ENERGY EFFICIENT OCCUPANCY MONITORING
Abstract: Air conditioning systems are the important part for providing ambient atmosphere inside buildings, for that building energy management systems (BEMS) are used. Ambient atmosphere means temperature control, humidity control, electronic equipment’s control, etc. The system consists of an embedded processor with an Internet of things (IoT) platform integrated with IR sensor and camera systems. The IoT devices have several sensors for measuring various parameters like temperature, humidity, inlet air coming …
Published in Journal of Software Engineering Tools & Technology Trends · Vol. 5, Issue 1, 2018 · pp. 6–11 Read article
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Heart Disease Evaluation Through Echocardiography Using CNN, ResetNet50, VGG16, and Image Processing
Abstract: Heart conditions stand out as primary contributors to untimely mortality among adults aged 30 and above, notably among those grappling with elevated cholesterol levels and diabetes. Detecting such ailments often necessitates the use of an echocardiogram, providing an intricate portrayal of the heart. However, precise analysis hinges on both the proper functioning of the echocardiogram apparatus and the proficiency of a skilled radiologist, a condition not always met. Manual scrutiny …
Published in International Journal of Information Security Engineering · Vol. 2, Issue 2, 2024 · pp. 25–35 Read article
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Integrating AI and ML in Tribology: A Review of Current Trends and Future Prospects
Abstract: This review paper explores the growing integration of artificial intelligence (AI) and machine learning (ML) within the field of tribology. Tribology, the study of friction, wear, and lubrication, is crucial for Improving the performance and longevity of mechanical systems. This review explores the role of AI and machine learning techniques, including artificial neural networks (ANNs), support vector machines (SVMs), and physics-informed machine learning (PIML)can be used to solve difficult tribological …
Published in Recent Trends in Fluid Mechanics · Vol. 12, Issue 3, 2025 · pp. 56–60 Read article
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AI-Based Discovery of High-Performance Energy Storage Polymer Composites: A Comprehensive Review
Abstract: The accelerating global demand for high-performance energy storage systems has stimulated significant research into advanced polymer composites as next-generation electrolytes, electrode binders, and functional membranes for batteries, supercapacitors, and photovoltaic devices. However, the vast compositional and structural design space of polymer materials presents formidable challenges for conventional trial-and-error discovery strategies, which remain slow, costly, and biased by prior expert knowledge. Machine learning (ML) and artificial intelligence (AI) have emerged as …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 1083–1097 Read article
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Digital Entry of Bank Related Slips Using Character Recognition
Abstract: Standing in long queues in bank for small work like depositing the money is very frustrating and also wastes a lot of time. The bank employee handles all the work such as making the entry of money deposited or credit from the account manually by typing information such as account number, amount, etc. and due this creates long queues in banks for such small tasks. Thus, we have come up …
Published in Trends in Opto-electro & Optical Communication · Vol. 11, Issue 3, 2021 · pp. 30–35 Read article