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536 articles for “deep network”
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Survey on Retinal OCT Image Preprocessing, Segmentation, and Deep Learning Based Classification
Abstract: Optical coherence tomography (OCT) is a non-invasive technique that generates high-resolution, detailed cross-sectional images of biological tissues. By utilizing low-coherence interferometry, OCT enables visualization of tissue microstructure with micron-scale resolution, making it useful in various medical fields such as ophthalmology, cardiology, and dermatology. In ophthalmology, OCT is extensively used for diagnosing and monitoring retinal diseases like macular degeneration and diabetic retinopathy, allowing doctors to assess changes in tissue morphology over …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 11, Issue 3, 2024 · pp. 1–9 Read article
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COVID-19 Detection using Convolutional Neural Network (CNN)
Abstract: Coronavirus disease (COVID-19) is spreading across the whole world and has habitual expressive community spread. The sudden hike in the number of patients with COVID-19, i.e. a new respiration virus has an extreme impact on the healthcare system. There are limited kits for diagnosis, hospital beds for such kind of patients, a limited number of personal protective equipment (PPE) for healthcare temporary staff and limited ventilators. A prediction system based …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 8, Issue 2, 2021 · pp. 22–30 Read article
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Ramifications of Artificial Intelligence and Cyber Security
Abstract: Artificial intelligence (AI) has pros and cons for cyber security: AI can improve network security, anti-malware, and fraud detection. AI can simulate cyberattacks, automate responses, and analyse enormous databases. AI-powered phishing and deepfakes are cyber risks. AI can potentially be attacked and become a liability for corporations. AI has transformed cyber security, bringing both new opportunities and challenges. AI-powered tools discover abnormalities faster, automate threat responses, and improve threat detection …
Published in International Journal of Information Security Engineering · Vol. 3, Issue 1, 2025 · pp. 40–45 Read article
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Dual-Stream Deep Learning Framework for Brain CT Image Classification and Implications for Polymer Composite Neuro Implant Evaluation
Abstract: Early and accurate classification of brain CT images is critical for diagnosing conditions such as aneurysms, tumors, and related lesions. We present a dual-stream image-classification framework that fuses convolutional neural network (CNN) features with handcrafted Histogram of Oriented Gradients (HOG) descriptors to jointly capture global semantics and local textural cues. The pipeline begins with modality unification via pixel-wise averaging to form a fused input, which is then processed in parallel …
Published in Journal of Polymer & Composites · Vol. 13, Issue 6, 2025 · pp. 172–179 Read article
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Advances in Deep Learning for Medical Image Analysis in the Era of Precision Medicine
Abstract: Medical imaging is fundamental to modern healthcare but analyzing the high-dimensional data requires advanced techniques. Manual image interpretation is time-consuming, subjective and limited in detecting complex patterns and minute details. Recent breakthroughs in Deep Learning offer transformative advances for unlocking clinically relevant information from medical images. This paper provides a comprehensive 6000+ word review of the current state-of-the-art Deep Learning techniques for medical image analysis including detailed coverage of key …
Published in Research and Reviews : Journal of Computational Biology · Vol. 12, Issue 2, 2023 · pp. 10–23 Read article
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Neuro-fuzzy Control Systems: A Cross-domain Review
Abstract: This paper presents a comprehensive review of the application of neuro-fuzzy control systems in various industries. Using the combined strengths of neural networks and fuzzy logic, neural-fuzzy control systems emerge as versatile tools to solve challenging control challenges It begins with clarifying the theoretical basis of neural fuzzy systems, and emphasizing their scalability, definition, and robustness. Specific examples in each domain highlight the effectiveness of neuro-fuzzy control in solving real …
Published in International Journal of Electro-Mechanics and Material Behaviour · Vol. 2, Issue 1, 2024 · pp. 28–37 Read article
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Evolving Perspectives: Innovations in Object Detection and Identification
Abstract: One of the most important developments in computer vision has been the creation of object detection and identification systems, which have allowed robots to perceive and understand visual data similarly to humans. These systems locate each object by drawing a bounding box around it, in addition to detecting and classifying every object in an image or video. This study suggests a novel method for item identification and detection that makes …
Published in Trends in Opto-electro & Optical Communication · Vol. 13, Issue 3, 2023 · pp. 23–27 Read article
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Virtual Reality Based Decentralized Educational Art Gallery
Abstract: One can experience the forefront of education by engaging with our virtual reality (VR) powered decentralized educational art gallery. This groundbreaking platform seamlessly integrates VR technology with decentralized networks, crafting an unmatched learning journey. Curated collections of art from diverse cultures and eras can be explored, accompanied by interactive educational modules that deepen one’s understanding of each piece. One can engage with fellow learners in real time, fostering collaboration and …
Published in Journal of Multimedia Technology & Recent Advancements · Vol. 11, Issue 2, 2024 · pp. 31–37 Read article
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Advancing EEG Technology for Affordable and Effective Epilepsy Detection
Abstract: For a proper diagnosis and prompt treatment, epilepsy, a neurological condition marked by recurring seizures, needs to be continuously monitored. Manual interpretation is frequently used in traditional approaches for identifying epileptic seizures from electroencephalogram (EEG) signals, which can be laborious and error-prone. In this research, a novel method for automatically detecting epilepsy from EEG data using deep learning algorithms is presented. According to centers for disease control and prevention (CDC) …
Published in Trends in Opto-electro & Optical Communication · Vol. 14, Issue 3, 2024 · pp. 11–18 Read article
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An Automated Facial Mask Detection System for Minimizing COVID-19 using Multi-Task Cascaded CNN Model
Abstract: An outbreak triggered by a new coronavirus has continued to spread over the globe till today. Nearly every area of development has felt the effects of COVID-19. The state of healthcare is now quite problematic. One of the many preventative steps adopted to limit the spread of this illness is the use of a mask. To limit the spread of COVID-19, we propose a system that identifies persons who are …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 9, Issue 2, 2022 · pp. 1–13 Read article
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Wireless Sensor Network: A Review
Abstract: Abstract The intersection of shoddy wireless communication, detecting and calculation has created another gathering of keen gadgets and by utilizing a great many these sorts of gadgets in self-arranging net-works has shaped another innovation that is called remote sensor systems (WSNs). WSNs utilize sensor hubs that set in open regions or in broad daylight places and with a tremendous number that makes numerous issues for the specialists and system fashioner, …
Published in Journal Of Network security · Vol. 5, Issue 3, 2017 · pp. 26–29 Read article
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Network Pharmacological Studies in Biological Interactions of Thymoquinone
Abstract: Thymoquinone, a bioactive phytochemical compound belonging to the class of benzoquinones, is prominently present in the plant Nigella sativa. Despite its widespread use, the precise molecular mechanisms underlying its beneficial effects remain elusive. To address this gap, we employed network pharmacology to investigate the actions of Thymoquinone (TQ). Our methodology encompassed the utilization of diverse bioinformatic tools to scrutinize this molecule of interest comprehensively. Initially, we retrieved the chemical structure, …
Published in Research and Reviews : Journal of Crop science and Technology · Vol. 12, Issue 3, 2023 · pp. 18–25 Read article
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Brain Stroke Detection Using Deep Learning and Grad-CAM Explainability Framework
Abstract: Seconds matter when a brain stroke occurs; it is a race against time where rapid, precise intervention is the only way to preserve a patient’s quality of life. This research introduces a deep learning framework designed to act as a vital ally for clinicians, providing automated, high-speed stroke detection through brain MRI analysis. At the heart of our approach is EfficientNetB0, a sophisticated neural network chosen for its ability to …
Published in Research and Reviews: A Journal of Neuroscience · Vol. 16, Issue 2, 2026 · pp. 8–14 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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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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AI-Driven IoT Ecosystems for Real-Time Thermo-Chemical Decision Making
Abstract: The efficient management of thermo-chemical processes is a critical challenge in modern industry, where maintaining precision, operational safety, and energy efficiency directly influences productivity and sustainability. The convergence of the Internet of Things (IoT) and Artificial Intelligence (AI) has transformed conventional industrial systems into intelligent, data-driven environments capable of continuous monitoring, predictive analysis, and autonomous decision-making. By integrating interconnected sensors, edge computing, cloud platforms, and advanced machine learning algorithms, industries …
Published in International Journal of Photochemistry and Photochemical Research · Vol. 4, Issue 2, 2026 · pp. 10–15 Read article
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Controlling Media Player Through Hand Gesture Recognition System Using CNN and RNN Models
Abstract: Artificial intelligence markup language (AIML) project represents a pioneering endeavor in the realm of media player control through hand gesture recognition, merging advanced technologies like convolutional neural networks (CNN) and recurrent neural networks (RNN). By harnessing the image analysis capabilities of CNN, our system ensures accurate, real-time detection, and interpretation of intricate hand gestures, enabling users to interact with their media content naturally and seamlessly. What sets our project apart …
Published in Journal of Computer Technology & Applications · Vol. 15, Issue 1, 2024 · pp. 29–34 Read article
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Parkinson’s Disease Detection on Spiral Images Using CNN with Meta-Classifiers
Abstract: In this work, we provide a detailed method for identifying Parkinson’s Disease (PD) by integrating Convolutional Neural Network (CNN) and meta-classifiers. Through the utilization of a varied dataset consisting of handwritten spiral images, our methodology demonstrates commendable accuracy across a range of models. Specifically, our CNN model with meta-classifiers surpasses alternative approaches, achieving an impressive accuracy rate of 95.07%. By utilizing pre-established VGG16 and ResNet50 architectures as bases, the region-based …
Published in Journal of Computer Technology & Applications · Vol. 16, Issue 1, 2025 · pp. 55–66 Read article
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A Physics-Informed Graph Neural Network Framework for Real- Time Thermal-Aware Fault Prediction and Adaptive Power Optimization in Heterogeneous System-on-Chip Architectures
Abstract: Heterogeneous System-on-Chip (SoC) architectures are increasingly adopted in edge computing, artificial intelligence, autonomous systems, and high-performance embedded platforms due to their superior computational efficiency and flexibility. However, increasing integration density and workload diversity introduce severe thermal hotspots, accelerated device degradation, and unexpected hardware faults that adversely affect system reliability and energy efficiency. This study proposes a Physics-Informed Graph Neural Network (PI-GNN) framework for real-time thermal- aware fault prediction and adaptive …
Published in Journal of VLSI Design Tools and Technology · Vol. 16, Issue 2, 2026 · pp. 19–28 Read article
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Innovative CNN Strategies for Superior Handwritten Digit Recognition
Abstract: Handwritten digit recognition is a fundamental problem in the field of computer vision and machine learning with numerous applications, such as postal code recognition, bank check processing, and digitizing historical documents. Convolutional Neural Networks have demonstrated remarkable success in various image recognition tasks, making them a popular choice for digit recognition. In this study, we present an enhanced approach to handwritten digit recognition using CNNs. Handwritten digit recognition plays a …
Published in International Journal of VLSI Circuit Design & Technology · Vol. 2, Issue 1, 2024 · pp. 27–34 Read article