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491 articles for “Detection Challenges”
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Implementation of Kalman Filter Using TDC and PLL for Object Detection and Tracking in Signal Processing
Abstract: The measurement uncertainty of GPS receivers is dependent on a wide range of external factors, including receiver clock precision, thermal noise, atmospheric influences, and minute variations in satellite positions. Estimating hidden states precisely and accurately in the face of uncertainty is one of the main problems facing tracking and control systems. Among the most significant and widely used estimate methods is the Kalman Filter. It uses imprecise and erratic measurements …
Published in Current Trends in Signal Processing · Vol. 13, Issue 2, 2023 · pp. 38–47 Read article
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Improving Dataset Integrity Through Automated Data Cleaning Techniques
Abstract: High-quality data is a fundamental requirement in data science for producing trustworthy analytical insights and effective machine learning models. Problems, including incomplete records, inconsistent entries, duplicate observations, and anomalous values, can severely reduce the accuracy and robustness of predictive systems. As modern datasets continue to expand in both volume and structural complexity, relying on manual data cleaning methods become time-consuming and error-prone, highlighting the growing importance of automated data preprocessing …
Published in International Journal of Data Structure Studies · Vol. 4, Issue 1, 2026 · pp. 40–45 Read article
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The Integration of AI Technologies in Automating Cyber Defense Mechanisms for Cloud Services
Abstract: The swift growth of cloud computing has transformed how organizations handle and store data, providing greater scalability and adaptability. However, the transition to cloud-based environments has heightened the complexity of cybersecurity challenges, especially in detecting and responding to security incidents. Conventional methods of incident response, which heavily depend on manual efforts, are no longer adequate to address the rapidly evolving and complex nature of modern cyber threats. This study explores …
Published in Journal of Operating Systems Development & Trends · Vol. 12, Issue 1, 2025 · pp. 1–14 Read article
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Automated Car License Plate Detection and Recognition Using Deep Learning
Abstract: The use of automated license plate detection and recognition (ALPR) systems to automate processes such as number plate detection is gaining popularity in traffic control, security, and law enforcement. This research focuses on achieving more accurate and efficient detection and recognition of number plates by leveraging deep learning techniques. The systems outlined in this study aim to improve the effectiveness of ALPR systems using advanced convolutional neural networks (CNNs) and …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 13, Issue 1, 2026 · pp. 23–29 Read article
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DDoS Detection Using Cascade Correlation for Improving Network Resources in Cloud Environment
Abstract: Intrusion detection is critical for protecting network security from emerging cyber threats. This study describes a unique intrusion detection system (IDS) based on the Random Forest algorithm. Random Forests are used as an effective classifier to identify patterns linked with malevolent behaviour. This technique uses Random Forests to improve the accuracy and efficiency of intrusion detection systems. The suggested methodology's value is shown by its performance on the benchmark KDD …
Published in International Journal of Wireless Security and Networks · Vol. 3, Issue 2, 2025 · pp. 17–22 Read article
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Development of Solar Powered Automatic Cotton Picking Machine Using Movable Robotic Arm: A Review
Abstract: Cotton harvesting is a labor-intensive process, with traditional manual methods being inefficient and costly. Mechanized systems, such as spindle pickers and strippers, offer higher productivity but are expensive, bulky, and prone to crop damage. Robotic cotton-picking systems, integrated with artificial intelligence (AI) and computer vision, provide a promising alternative for selective and precise harvesting. This review examines advancements in robotic arm-based cotton picking, focusing on boll detection using AI, challenges …
Published in Journal of Advancements in Robotics · Vol. 12, Issue 3, 2025 Read article
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Harnessing IoT for Water Quality Surveillance and Management
Abstract: This paper provides an overview of IoT technology's integration in water quality management, focusing on real time monitoring of key parameters like pH, dissolved oxygen, turbidity, and temperature. Since it directly affects people's health and well-being, agriculture's viability, and the preservation of our natural environment, water quality is extremely important. However, as the world's population and industrialization grow, so does the need for water sources, making maintaining their purity extremely …
Published in Recent Trends in Fluid Mechanics · Vol. 10, Issue 3, 2023 · pp. 27–35 Read article
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Analysis and Identification of Malicious Mobile Applications Using Machines Learning
Abstract: Over the past few years, malware attacks on the Android platform have surged, posing significant risks to users' financial security, personal information, and device integrity. In the first half of 2019 alone, approximately 25 million smartphones were infected, highlighting the severity of these threats. The model ranks manifest features based on their frequency in normal and malicious apps, identifying key components that distinguish benign from malicious applications. To improve detection …
Published in Journal of Microcontroller Engineering and Applications · Vol. 12, Issue 2, 2025 · pp. 17–24 Read article
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Network Intrusion Detection System using Machine Learning and Deep Learning Approach
Abstract: Networks play a significant part in today’s world; fast internet and communication industries result in vast network size and data expansion. Furthermore, attackers aiming to launch various cyberattacks inside the system cannot be neglected. An IDS keeps track of the network’s software and hardware security to preserve its privacy, integrity, and accessibility. Despite the significant efforts of the researchers, current IDS continue to confront challenges in terms of accuracy rate, …
Published in Journal Of Network security · Vol. 10, Issue 1, 2022 · pp. 7–34 Read article
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Advancements in Intrusion Detection: Tackling Imbalanced Network Traffic with Machine Learning and Deep Learning Techniques
Abstract: Malicious cyberattacks can frequently hide enormous amounts of typical data in unbalanced network traffic. It is very stealthy and obfuscating in cyberspace, which makes it challenging for Network Intrusion Detection Systems (NIDS) to guarantee the precision and promptness of detection. This essay investigates. Machine learning and deep learning are utilized for intrusion detection in imbalanced network traffic. It offers a novel method for addressing the problem of class imbalance termed …
Published in Recent Trends in Electronics Communication Systems · Vol. 11, Issue 2, 2024 · pp. 18–24 Read article
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Enhancing IoT Network Security with Hybrid Deep Learning Classifiers for DDoS Attack Detection
Abstract: The security and operational dependability of Internet of Things (IoT) networks are seriously threatened by the growing susceptibility to Distributed Denial of Service (DDoS) assaults brought about by their rapid expansion. The intricacy and dynamic character of these advanced attacks can provide a challenge to conventional intrusion detection systems. This study presents a novel method for strengthening IoT network security by combining Convolutional Neural Networks (CNNs) and Long Short-Term Memory …
Published in Journal of Web Engineering & Technology · Vol. 13, Issue 1, 2026 · pp. 23–33 Read article
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Recognition and Detection of Content in Video Using OpenCV
Abstract: The emergence and continued reliance on the Internet and related technologies has resulted in massive amounts of data that can be analysed. Humans, on the other hand, do not have the cognitive abilities to comprehend such vast amounts of data. Machine learning (ML) is a mechanism that enables humans to process large amounts of data, gain insights into the data's behaviour, and make more informed decisions based on the analysis's …
Published in International Journal of Image Processing and Pattern Recognition Read article
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Detection of Brain Tumor from MRI using MATLAB
Abstract: Brain Tumor is an abnormal growth of cells in the brain which can affect the functioning of the brain and at times can be fatal. The detection of brain tumor is challenging because of the complex structure of brain. This paper discusses about the detection of brain tumor using MATLAB through image processing. Magnetic Resonance Imaging (MRI) plays an important role in analysis, diagnosis and treatment planning of brain tumor. …
Published in Journal of Microelectronics and Solid State Devices · Vol. 4, Issue 1, 2017 · pp. 28–31 Read article
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IoT-Based Manhole Detection and Monitoring System
Abstract: Urban drainage systems face numerous challenges, including blockages, harmful gas accumulation, and flooding, which pose risks to public safety and environmental health. This project introduces an IoT-enabled solution designed to monitor and address these issues efficiently. The system incorporates sensors to detect critical parameters such as gas levels, temperature, water presence, and nearby obstacles. A unique lifting mechanism ensures the hardware adapts to challenging conditions, maintaining uninterrupted operation. The system …
Published in Journal of Remote Sensing & GIS · Vol. 16, Issue 3, 2025 · pp. 1–6 Read article
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Network Security Secure Communication in Industrial Networks
Abstract: In an era dominated by rapid industrial digitization, ensuring the security of communication in industrial networks has become a critical challenge. Industrial networks, which facilitate seamless communication between machines, devices, and systems, are increasingly targeted by cyber threats that can disrupt operations, compromise sensitive data, and jeopardize safety. This article delves into the key aspects of secure communication in industrial networks, emphasizing the role of advanced encryption techniques, robust authentication …
Published in International Journal of Wireless Security and Networks · Vol. 3, Issue 1, 2025 · pp. 1–8 Read article
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Quasar: Quantum-Accelerated Sustainable Anomaly Recognition in Climate Systems
Abstract: Accurate detection of climate anomalies is vital for disaster alleviation and policy making in a sustainable manner, but customary detection methods face the challenges of computational inefficiency and physical inconsistency. In this study, we propose a novel approach called Quantum-Optimized Fuzzy Physics-Informed Neural Networks (QFuzzy-PINNs), which integrates quantum computing, fuzzy logic, and physics-informed deep learning. As a first step, we employ quantum annealing for conventional optimization to adjust multiple Gaussian …
Published in International Journal of Climate Conditions · Vol. 2, Issue 2, 2025 · pp. 18–27 Read article
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Sustainable Cotton Crop Productivity through Precision Weed Detection: A Deep Learning-Based Approach with UAV Integration
Abstract: Weeds present a major challenge to crop productivity by competing with crops for vital resources, including water, sunlight, and nutrients, often resulting in significant yield reductions. On a global scale, weeds are responsible for approximately 13.2% of annual crop losses, a quantity sufficient to feed nearly one billion people. These invasive plants disrupt agricultural systems and adversely impact crop yields. Given their uneven distribution in fields, ground or aerial robots …
Published in Journal of Aerospace Engineering & Technology · Vol. 15, Issue 1, 2025 · pp. 19–26 Read article
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Scaling of Machine Learning Techniques in Medical Imagining and Biomedical Applications Concerning Healthcare
Abstract: Machine learning refers to a field within computer science enabling computers to learn without explicit programming. Stemming from artificial intelligence's study of pattern recognition and computational learning theory, machine learning develops algorithms capable of learning from vast datasets and making predictions. Its applications span diverse computing tasks like email filtering, network intrusion detection, optical character recognition, and computer vision, where conventional algorithm design proves challenging. Notably, in computer vision, a …
Published in Journal of Computer Technology & Applications · Vol. 15, Issue 1, 2024 · pp. 41–44 Read article
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Grid Integrated Micro Inverter for PV Module with Anti-Islanding and MPPT Schemes
Abstract: From the economic perspective, densely populated areas can generate great amounts of electric power by installing PV panels on its rooftops and it can be fed in to the grid. This study describes a grid tied micro inverter for photovoltaic applications. The system consists of a Cuk converter connected with a full-bridge current source inverter. The connection of micro inverter systems to the grid can raise several challenges as the …
Published in Journal of Power Electronics and Power Systems · Vol. 8, Issue 3, 2018 · pp. 39–45 Read article
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Identification and Categorization of Brain Tumors
Abstract: Brain tumors are a serious and aggressive disease that can lead to a reduced life expectancy. Strategic and well-thought-out treatment planning significantly contributes to improving a patient's overall quality of life. Many different imaging techniques, such as Magnetic Resonance Imaging (MRI), Computed Tomography (CT) and also ultrasound are used to evaluate tumors in different parts of the body, with a focus on using MRI images for brain tumors. It is …
Published in International Journal of Biomedical Innovations and Engineering · Vol. 1, Issue 2, 2023 · pp. 32–37 Read article