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513 articles for “deep network”
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Wearable Biosensor Technology—An Innovative Review
Abstract: Wearable biosensors have made drastic change in the trends of health monitoring over the past many years. The use of wearable biosensors makes easy to monitor the real time physiological parameters continuously and accurately. The suitability, easiness, lower cost, utility, performance etc. of the biosensors for health monitoring of patient/user are attracting the researchers to work in the field of healthcare industry. The present study will discuss the various evolutions/researches, …
Published in Research and Reviews : A Journal of Medical Science and Technology · Vol. 7, Issue 1, 2018 · pp. 1–8 Read article
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IoT-based Patient Fall Detection and Alerting System for Patient Safety
Abstract: This paper presents an Internet of Things (IoT) based patient fall detection and alerting system designed to enhance patient safety in healthcare settings. Falls among patients, especially in hospitals or care facilities, can lead to severe injuries and complications. The proposed system utilizes wearable sensors integrated with IoT technology to continuously monitor the movements and activities of patients. Machine learning algorithms are employed to analyze sensor data in real time, …
Published in Journal of Microcontroller Engineering and Applications · Vol. 11, Issue 3, 2024 · pp. 9–14 Read article
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Review of Deep Learning in Medical Imaging
Abstract: In the past few years, computer-aided analysis has fallen quickly behind. Organ categorization and segmentation is a key stage in computer-aided diagnosis. In recent years, there has been a lot of interest in the division of abdominal organs such as the liver, stomach, kidney, pancreas, and bladder from various picture modalities. Radiologists or medical specialists analyze abdominal pictures the majority of the time. Due to subjectivity, intricacy of the picture, …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 9, Issue 3, 2022 · pp. 16–24 Read article
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Application of Artificial Neural Networks in Optimizing Polyhouse Roof Truss Design
Abstract: Polyhouses are specialised agricultural structures developed to maintain controlled environmental conditions for crop cultivation, thereby ensuring consistent productivity even under adverse climatic circumstances. The performance of these systems largely relies on the structural stability and cost efficiency of the roof truss, which must achieve an effective balance between strength, adaptability, and economy. In this research, an Artificial Neural Network (ANN)-based modelling framework is introduced to optimise the members of polyhouse …
Published in Recent Trends in Civil Engineering & Technology · Vol. 16, Issue 2, 2026 · pp. 15–25 Read article
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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
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Analysis of Dispersion Compensation System for PON using Different Schemes
Abstract: In this paper, dispersion compensation techniques are discussed for better communication. Different schemes like pre-compensation, post- compensation and symmetrical compensation of DCF with NRZ and Manchester modulation format. To compensate the dispersion of fiber, DCF is used. Simulations have been analysed by using OptiSystem 7.0 simulator. Results are compared in terms of BER, Q-factor and total received power.Keywords: Dispersion Compensation, Dispersion Compensation Fiber (DCF), Passive Optical Network (PON), Q-factor, BER.Cite …
Published in Journal of Communication Engineering & Systems · Vol. 9, Issue 3, 2019 · pp. 28–34 Read article
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Deep Learning-Based Alzheimer’s Disease Detection: A CNN Approach
Abstract: Alzheimer’s disease (AD) is a neurological condition that worsens with time and impairs a patient’s quality of life by causing cognitive loss. For prompt intervention and management of AD, early identification is essential. In this work, we propose a deep learning-based method for automatically classifying Alzheimer’s disease from medical imaging data using convolutional neural networks (CNNs). Our algorithm is intended to evaluate brain MRI images and detect anatomical variations suggestive …
Published in Research and Reviews: A Journal of Neuroscience · Vol. 15, Issue 3, 2025 · pp. 24–31 Read article
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Leveraging Standards and Deep Learning Approaches to Secure Internet of Things (IoT) Devices from Cyber Attack
Abstract: The widespread adoption of Internet of Things (IoT) devices between 2019 and 2024 has significantly grows in various sectors in Japan, including healthcare, manufacturing, and the development of smart cities. Although this growth offers many advantages, it also makes these devices more vulnerable to cyber threats. High-profile security breaches in Japan have sparked discussions about the requirement for enhanced security measures to protect the rapidly evolving IoT technologies. This study …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 13, Issue 1, 2025 Read article
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Communication Strategies and Designs for Patient Monitoring over Wireless Body Area Network-A Review
Abstract: As a significant technology for short assortment communication around the humanoid body, WBAN, a contemporary intelligent monitoring system, is envisioned to unbridle an upsurge of personalized, innovative and integrated uses in the field of medical, fitness, sports, entertainment, military and purchaser electronics. In WBAN, only few sensors are used which are implanted in body or positioned on the body. These tiny sensors placed on patient’s body measure main signs like …
Published in Journal of Advances in Shell Programming · Vol. 2, Issue 3, 2015 · pp. 5–15 Read article
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Handwritten Sanskrit Word Recognition: A Deep Learning Approach Using AlexNet
Abstract: Handwritten Sanskrit word recognition poses significant challenges due to the intricate structure of the script and the considerable variations in handwriting across individuals. To address these challenges, this research introduces a novel methodology employing transfer learning with the AlexNet convolutional neural network. The study utilized two distinct datasets: a specifically curated Sanskrit word image dataset containing 2616 samples, alongside a broader Devanagari character dataset used for validation purposes. The established …
Published in Current Trends in Signal Processing · Vol. 15, Issue 2, 2025 · pp. 33–43 Read article
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Image Processing Techniques for Detecting and Classification of Leaf Diseases
Abstract: Plants are the way to make a living. From the factors of our daily life to breathing we are totally dependent on plants. Therefore, plant care must be proper. Plant diseases involve, of instance, algae, bacteria, and viruses. Several researchers have to classify plant diseases but it is time consuming to manually identify them. Image processing techniques are used to detect various diseases of the plant. There are several steps …
Published in Trends in Opto-electro & Optical Communication · Vol. 11, Issue 2, 2021 · pp. 1–6 Read article
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Automatic Lightning and Control System
Abstract: This study describes the design and execution of a novel Automatic Lightning and Control System, which turns on and off electrical devices, including lighting circuits, automatically when people are present and off when they are not. Improving the electrical system's dependability and efficiency is the system's goal. Most universities squander a large amount of electrical energy turning on and off fans, computers, and other devices. This system is designed to …
Published in Trends in Mechanical Engineering & Technology · Vol. 14, Issue 3, 2024 Read article
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FACE EMOTION RECOGNITION TO DETECT DEPRESSION
Abstract: In the current competitive world, one of the most familiar and grave mental illness we encounter in humans is Depression also called as major depression or major depressive disorder. It makes you feel depressed and disinterested all the time, which has a bad impact on your thoughts and behaviour. Thus affecting not only the victim but also people associated with them, such as family, friends and society. If not treated …
Published in Current Trends in Signal Processing · Vol. 14, Issue 1, 2024 · pp. 1–14 Read article
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Advancements in Handwriting Recognition: A Deep Learning Approach
Abstract: This article provides detailed information about handwriting text recognition. Some human characteristics are unique to the individual. Writing is one of the scientifically proven habits that is different for everyone. Handwriting Text Recognition (HTR) is responsible for identifying written characters and converting them into digital text. HTR is an intensively researched area, but improvements can still be made in accuracy and efficiency. Digitization of manuscripts is very useful in today's …
Published in International Journal of Radio Frequency Innovations · Vol. 2, Issue 1, 2024 · pp. 28–34 Read article
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Artificial Neural Network and Its Application to Diagnosis
Abstract: In this paper, we are giving an excellent idea for the designing of the standard diagnosis key diagnosis systems, which security is based on the well known number theoretic problem, i.e., elliptic curve discrete logarithm problem in multiplicative group of the finite field. But now we are moving in the revolutionary idea, “The Automatic groups G converted into the multiplicative groups G’ of the finite field Zp* of the order …
Published in Journal of Advancements in Robotics · Vol. 7, Issue 2, 2020 · pp. 15–22 Read article
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Digital Sampling and Testing of COVID-19 to Reduce Lab Procedures Further Decreasing Carbon Emission: Review
Abstract: The COVID-19 pandemic has caused a new virus known as severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) that primarily infects the lungs and can lead to serious respiratory illnesses such as ARDS and pneumonia caused by coronavirus. Declared a pandemic by the World Health Organization (WHO), the disease belongs to the family of coronaviruses that can cause cold and flu, making it a highly contagious disease. Chest imaging tests such …
Published in Journal of Open Source Developments · Vol. 10, Issue 1, 2023 · pp. 19–25 Read article
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Using Convolutional Neural Networks (CNN) for Age and Gender Prediction
Abstract: The network, security, and care have all become more dependent on age and gender identification. It's commonly used for children's access to age-appropriate content. To expand its reach, social media uses it to provide layered adverts and marketing. Face recognition has progressed to the point where we need to map it out further in order to achieve more usable results using various methodologies. In this study, we suggest using deep …
Published in Journal of Instrumentation Technology & Innovations · Vol. 12, Issue 1, 2022 · pp. 27–32 Read article
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An Analysis of Machine Learning Models for Early Cardiac Risk Stratification
Abstract: The paper shows an in-depth study of machine learning and artificial intelligence solutions to early cardiac risk stratification which has a crucial necessity because cardiovascular disease (CVD) prediction remains a significant issue that needs to be improved beyond the conventional risk score. Since CVD is the most serious disease killer in the world, claiming 17.9 million deaths every year, there is a strong need to get the most sophisticated predictive …
Published in Research & Reviews: A Journal of Bioinformatics · Vol. 13, Issue 2, 2026 Read article
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Optimizing Machinability in Wire EDM of AISI P20 Steel Employing Composite Material Wires with Hybrid Neural Network Approach
Abstract: AISI P20+Ni steel is extensively used for forging dies, plastic moulds, and automotive die components due to its excellent polishability, hardness, and homogeneity. This research utilizes Wire Electrical Discharge Machining (WEDM) to process pre-hardened AISI P20+Ni steel, focusing on minimizing both recast layer thickness (RLT) and kerf width (KW). The performance of wires made from composite materials, including zinc-coated brass wire (ZBW), cryogenically treated ZBW (CZBW), and ultrasonic vibration-assisted brass …
Published in Journal of Polymer & Composites · Vol. 14, Issue 1, 2026 · pp. 1120–1133 Read article
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Forecasting Commodity Prices Using Deep Learning Techniques: An Empirical Evidence from India
Abstract: Commodity price forecasting is instrumental in financial markets, providing framework for investment choices and risk management practices. Traditional models, including statistical and machine learning approaches, have limitations in capturing the nonlinear and volatile nature of commodity prices. Deep learning (DL) techniques have emerged as promising alternatives, leveraging advanced neural networks to enhance predictive accuracy. This study presents a thorough and comprehensive examination of deep learning applications in commodity price prediction, …
Published in Journal of Computer Technology & Applications · Vol. 16, Issue 3, 2025 · pp. 08–12 Read article