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1045 articles for “U-net”
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Emotion Recognition from Electroencephalogram Signal and Eye Movement Based on Deep Learning
Abstract: Emotion recognition from electroencephalogram (EEG) signals has gained significant attention due to its potential in human- computer interaction (HCI), mental health monitoring, and personalized content delivery. This paper presents the use of Convolutional neural networks (CNNs) to classify emotions such as happiness, sadness, fear, neutral, and disgust by leveraging a fusion of EEG signals and eye movements data. Compared to conventional methods of emotion detection, such as those that rely …
Published in International Journal of Optical Innovations & Research · Vol. 3, Issue 2, 2025 · pp. 8–15 Read article
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Network Monitoring Tool in Shell Programming
Abstract: Network monitoring is the systematic effort of a computer network to detect slow or failing network components such as overloaded or crashed/frozen servers, failing routers, failed switches, or other problematic devices. The network monitoring system notifies the network administrator in the event of a network failure or other outage. Network management is a subset of network monitoring. Network monitoring is typically accomplished through the use of software applications and tools. …
Published in Journal of Advances in Shell Programming Read article
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Quantum-Inspired Neural Networks: Accelerating AI for Large-Scale Data Processing
Abstract: Recently, the world of artificial intelligence has been buzzing with exciting ideas inspired by quantum computing, especially when it comes to processing large amounts of data. Introducing the Quantum-Inspired Neural Network (QINN), a novel approach to conventional neural networks that blends concepts from quantum mechanics with machine learning techniques. Unlike typical networks that rely on neurons, QINNs utilize qubit-based representations, enabling them to perform computations in a more flexible and …
Published in Journal of Software Engineering Tools & Technology Trends · Vol. 12, Issue 3, 2025 · pp. 12–17 Read article
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Advancing Brain Tumor MRI Segmentation
Abstract: Segmentation of brain tumors in MRI scans is an integral part of neuroimaging carried out for diagnostic and therapeutic interventions. Given that manual segmentation is cumbersome and highly variable, there arises a need for automated, more precise segmentation solutions. This project, ‘Machine Learning and Deep Neural Networks to Advance Brain Tumor MRI Segmentation’ will develop a better, efficient, and accurate segmentation model to help clinicians identify brain tumors with greater …
Published in Recent Trends in Electronics Communication Systems · Vol. 12, Issue 2, 2025 · pp. 28–33 Read article
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Optimizing Routing and Placement of VLSI Circuits with Differential Algorithms and Neural Networks
Abstract: The performance of modern VLSI systems is heavily influenced by power constraints, necessitating precise power estimation and effective optimization techniques. Traditional methods, such as gate-level simulations, are often slow and computationally intensive. This paper introduces DRPENN (Differential Algorithm for Routing and Placement Optimization using Neural Networks), an innovative solution that combines a Switching Activity Estimator (SAE) with a neural network-assisted differential algorithm. By leveraging toggle rates from simulations to train …
Published in Journal of VLSI Design Tools and Technology · Vol. 14, Issue 2, 2024 · pp. 14–20 Read article
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Analysis of Losses in Geostationary Intersatellite Optical Wireless Communication Links
Abstract: The effective method to create a link between satellites is inter-satellite communication. Data is transmitted from one side to the other via a laser in this groundbreaking method. Optical networks, which offer continuous data transport over vast distances, are networks with high bandwidth efficiency. Inter-satellite optical wireless communication (Is-OWC) is a common method to transfer high-speed data between various satellites in free space. Is-OWC networks have undoubtedly innovated satellite communications …
Published in International Journal of Satellite Remote Sensing · Vol. 2, Issue 2, 2024 · pp. 1–18 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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Centrality in Social Network Analysis: A Comprehensive Review for Students
Abstract: Centrality, a fundamental concept in social network analysis (SNA), plays a pivotal role in understanding the structural dynamics and information flow within networks. This studyoffers an extensive examination of centrality metrics and their utilization in diverse fields. We begin by defining centrality and exploring its significance in characterizing the importance of nodes within a network. Subsequently, we delve into the literature review by different authors and most employed centrality metrics, …
Published in International Journal of Data Structure Studies · Vol. 1, Issue 2, 2023 · pp. 1–8 Read article
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Border Security Alert for Soldiers
Abstract: Secure a nation by protecting its people and the country’s borders. Soldiers guarding remote and hostile areas of the border experience very difficult situations when confronted with the possibility of arms and/or people crossing the border without permission and environmental conditions or obstacles that can impede communication. The proposed project titled, “Border Security Alert for Soldiers”, is an attempt to assist soldiers in their border surveillance efforts by using an …
Published in Journal of Microcontroller Engineering and Applications · Vol. 13, Issue 2, 2026 Read article
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Digital Transformation of Urban Infrastructure with the Help of AI Guardians
Abstract: The construction industry continues to face challenges related to quality control, safety protocols, and meeting project deadlines. These issues often result in significant cost overruns and project delays. Traditional inspection and site management approaches rely heavily on manual work and individual judgment. As a result, human errors can easily occur, and these methods provide only limited snapshots of site conditions over time. This paper presents a comprehensive framework that uses …
Published in Recent Trends in Civil Engineering & Technology · Vol. 16, Issue 1, 2026 · pp. 16–25 Read article
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Lung Cancer Detection and Classification Using Deep Learning
Abstract: Lung cancer is a disease that can be effectively treated if detected early. Various technologies, such as magnetic resonance imaging, isotopes, X-rays, and computed tomography scans, are employed for diagnosis. One of the most crucial strategies in combating cancer is early detection, which greatly enhances a patient’s likelihood of survival; this is where artificial intelligence plays a significant role. The approach proposed in this study leverages historical medical data to …
Published in Research and Reviews: Journal of Oncology and Hematology · Vol. 13, Issue 3, 2024 · pp. 11–17 Read article
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Analysis of Security in Cloud Computing
Abstract: These days, cloud computing is expanding quickly in the IT sector, offering a fresh approach to managing various information systems. The rapid pace of technological advancement highlights the importance of embracing and leveraging its advantages. Organizations transitioning to cloud-based information archiving demonstrate several key characteristics. These include enhanced IT infrastructure, the ability to manage remote access from any location in the world with a stable Internet connection, and the cost …
Published in Recent Trends in Parallel Computing · Vol. 11, Issue 1, 2024 · pp. 35–40 Read article
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Deep Plate: A Deep Learning Approach to Recipe Generation from Food Images
Abstract: In the deep learning era, image understanding is advancing in sophistication, encompassing both semantic interpretation and the generation of meaningful image descriptions. To achieve this, deep neural networks must undergo specific cross-model training; these networks must be both simple enough to handle a wide range of inputs and complex enough to encode the fine contextual information associated with the image. An appropriate example of the previously described picture comprehension problem …
Published in Journal of Operating Systems Development & Trends · Vol. 11, Issue 2, 2024 · pp. 15–22 Read article
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An Innovative Fuzzy-Enhanced Black Widow Spider Optimization for Energy-Efficient Cluster Communication Through the Selection of the Ideal Cluster Head
Abstract: This paper presents a novel approach to enhance energy efficiency in cluster-based wireless sensor networks (WSNs) by integrating fuzzy logic with the black widow spider optimization (BWSO) algorithm. The focus of the suggested fuzzy-enhanced BWSO approach is on cluster head selection, which is essential for lowering energy consumption and enhancing network performance. The program uses fuzzy logic to assess a number of factors, including network density, node proximity, and energy …
Published in International Journal of Wireless Security and Networks · Vol. 2, Issue 2, 2024 · pp. 28–34 Read article
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Spectral Intuitionistic Fuzzy Hypergraph Operators and Dominance Kernels for Resilient Discrete Network Design
Abstract: A new discrete-mathematical framework is developed for resilient network design on intuitionistic fuzzy hypergraphs, where uncertainty is explicitly represented through membership, non-membership, and hesitation degrees associated with both vertices and hyperedges. These three components are systematically integrated into an effective incidence operator that captures the underlying uncertain relationships within complex hypergraph structures. Based on this operator, both un-normalised and normalized Laplacian matrices are formulated to characterize the spectral properties and …
Published in Recent Trends in Mathematics · Vol. 3, Issue 2, 2026 · pp. 41–48 Read article
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Optimized Sentiment Analysis Through TextBlob and Hybrid RNN Models
Abstract: In today’s world, analyzing people’s feelings from what they write online has become very important. This is because there is a large amount of content created by users. To make this analysis accurate and fast, we present a method. This method uses a mix of two approaches: one that looks up words in a dictionary and another that uses computer learning. TextBlob is an affordable tool for getting an initial …
Published in International Journal of Computer Science Languages · Vol. 4, Issue 1, 2026 · pp. 29–28 Read article
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ML Associated DoS and DDoS Attack Observation in Protection
Abstract: DoS and DDoS assaults are significant risks to the availability and integrity of online services and networks. Attack traffic might come from a variety of geographical regions, making it difficult to filter and neutralize the attack. DDoS attacks are far more sophisticated and powerful than DoS attacks. They use a network of compromised devices, known as a botnet, to launch a coordinated attack on a target. Monitoring and evaluating the …
Published in International Journal of Satellite Remote Sensing · Vol. 2, Issue 1, 2024 · pp. 18–26 Read article
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An Integrated Satellite and Underwater IoT Framework for Real-Time Oceanic Disaster Monitoring and Resilient Communication
Abstract: Ocean-based environmental disasters such as tsunamis and underwater earthquakes pose significant risks to human life, coastal infrastructure, and regional stability. However, traditional communication networks often collapse during such events, leading to delayed alerts and uncoordinated response efforts. This study presents an integrated framework that combines underwater Internet of Things (IoT) systems with satellite communication technologies to enable real-time oceanic disaster monitoring and reliable emergency communication. The system connects underwater sensor …
Published in Recent Trends in Electronics Communication Systems · Vol. 12, Issue 2, 2025 · pp. 34–40 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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Advanced Anomaly Detection in Cloud Infrastructures Using Deep Learning Algorithms
Abstract: It is critical to guarantee the stability and security of cloud environments as cloud computing is becoming the backbone of contemporary IT infrastructures. Neglecting to quickly identify and resolve anomalies, which might point to security breaches, performance problems, or system breakdowns, can lead to disastrous outcomes. The increasing size and complexity of cloud infrastructures are challenging the effectiveness of traditional anomaly detection methods. These approaches often depend on rule-based systems …
Published in Journal of Computer Technology & Applications · Vol. 16, Issue 1, 2025 · pp. 1–11 Read article