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305 articles for “image pre-processing”
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Drone-based Fire Detection and Crowd Management System using Image Processing
Abstract: AbstractNowadays, fire outbreaks are common issues which cause severe damage towards nature and human properties hence fire detection system are designed to discover fires early in their development when the time will still be available for the safe evacuation of occupants. Early fire detection in the event of an outbreak is pivotal to prevent loss of life and properties. Fire is necessary and profitable to humankind life, but it also …
Published in Journal of Electronic Design Technology · Vol. 10, Issue 2, 2019 · pp. 30–34 Read article
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Shadows of Uncertainty: When Pneumonia Isn’t Pneumonia
Abstract: Pneumonia is a common medical condition encountered in hospitalized patients and remains a cause of morbidity worldwide. Identifying and initiating appropriate treatment in febrile patients who present with respiratory symptoms and radiographic infiltrates, reduce hospital stay, minimize complications, and lower healthcare costs. However, the assumption that every pulmonary infiltrate or opacity seen on a radiological imaging represents an infectious process such as pneumonia can lead to misdiagnosis, unnecessary investigations, prolonged …
Published in International Journal of Pathogens · Vol. 3, Issue 1, 2026 · pp. 24–29 Read article
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Advancements in Material Design and Motion Control: Integrating Additive Manufacturing, Fused Deposition Modeling, and Precision Systems in Modern Applications
Abstract: The interaction between material design, mechanical properties, and advanced motion control systems is vital in a range of engineering domains, including robotics, electronics, and manufacturing. This article examines two key areas: the mechanical properties and design of cutting-edge materials, focusing on composites, polymers, ceramics, and fibers, and the integration of advanced motion control systems in hand-held electronic and photographic devices. The first section delves into the mechanical behavior of various …
Published in International Journal of Electro-Mechanics and Material Behaviour · Vol. 2, Issue 2, 2024 · pp. 26–30 Read article
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Fake Product Detection Using Convolutional Neural Networks
Abstract: The widespread circulation of counterfeit products in global markets presents a significant threat to both consumer trust and the integrity of established brands. With the advancement of artificial intelligence, particularly deep learning, there is growing potential to develop more sophisticated systems to combat this issue. This study introduces a novel counterfeit detection framework using the VGG16 Convolutional Neural Network (CNN) to distinguish between authentic and counterfeit products through image analysis. …
Published in International Journal of Algorithms Design and Analysis Review · Vol. 3, Issue 2, 2025 · pp. 08–15 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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Identification of Papaya Fruit Ripening Process Using AI
Abstract: Identifying the ripening process of papaya fruit using artificial intelligence involves employing machine learning algorithms to analyze various features such as color changes, texture alterations and chemical compositions. This model is capable of analyzing visual cues to determine the stage of ripeness. The dataset compares images of papaya at various ripening stages, and our AI model demonstrated high accuracy in classifying these stages. Employing machine learning algorithms and image processing …
Published in Research & Reviews : Journal of Food Science & Technology · Vol. 13, Issue 2, 2024 · pp. 23–30 Read article
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A Study of Cloud-Enabled Deep Learning for Monitoring and Predicting Soil Health in Agriculture
Abstract: Soil health is a critical factor in ensuring sustainable agricultural practices and food security. Traditional methods for soil health assessment are often time-consuming, localized, and lack scalability. This study explores the integration of cloud-enabled deep learning techniques to monitor and predict soil health efficiently. Leveraging data from IoT sensors, satellite imagery, and lab-based analyses, a cloud-based framework is proposed to process and analyze soil health parameters such as pH, moisture …
Published in Journal of Remote Sensing & GIS · Vol. 16, Issue 2, 2025 · pp. 8–16 Read article
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Gold Nanoparticle Size, Biodistribution, and Toxicity: Insights from DualEnergy CT
Abstract: Dual-energy and spectral computed tomography (CT) have emerged as powerful platforms for noninvasive, quantitative mapping of nanoparticle biodistribution in vivo. By exploiting the energy-dependent attenuation profiles of high-atomic-number (high-Z) materials, these systems enable material decomposition and element-specific imaging, thereby distinguishing nanoparticle signals from those of soft tissues and conventional iodinated contrast agents. Photon-counting spectral CT further enhances this capability by binning individual photons into multiple energy channels, improving spatial resolution, …
Published in Nano Trends – A Journal of Nano Technology & Its Applications · Vol. 28, Issue 2, 2025 · pp. 22–34 Read article
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Convolutional Neural Network and its Architectures
Abstract: Convolutional neural network (CNN) is a type of artificial neural network (ANN) with multiple layers. From the past decades, it has been considered as a powerful classification technique as it can handle a huge amount of imagery data. It can be applied in the field of image recognition. The name CNN has been derived from the mathematical linear operation known as convolution which is performed between two matrices. CNN has …
Published in Journal of Computer Technology & Applications · Vol. 12, Issue 2, 2021 · pp. 6–14 Read article
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Image Processing and Deep CNN-based Automatic Liver Cancer Detection
Abstract: Liver cancer ranks among the leading causes of mortality for people worldwide. In the current situation, manually identifying the cancer tissue is a challenging and timeconsuming task. Treatment planning, response monitoring, tumor load assessment, and prediction are all made possible by the segmentation of liver lesions in CT scans. To address the current problem of liver cancer, the Hybridized Fully Convolutional Neural Network (HFCNN), which has been theoretically modeled, has …
Published in International Journal of Biomedical Innovations and Engineering · Vol. 3, Issue 1, 2025 · pp. 39–41 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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Attendance System Based on Facial Recognition
Abstract: Attendance management is a fundamental aspect of educational institutions and workplaces, ensuring accountability, discipline, and operational efficiency. Traditional methods, such as manual roll calls, RFID cards, and fingerprint scanners, are often time-consuming, error-prone, and susceptible to fraud. This research presents an automated attendance management system utilizing face recognition technology to address these challenges effectively. The proposed system employs OpenCV for real-time image processing, the face recognition library for accurate facial …
Published in International Journal of Electronics Automation · Vol. 3, Issue 1, 2025 · pp. 28–34 Read article
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Structural Health Monitoring of Bridges using Digital Image Correlation: A Case Study
Abstract: The rapid development of the transportation section and continuous change in traffic volume, density, and loading patterns over the last few decades have increased the probability of a hazard and reduced the life of existing bridges. Structural Health Monitoring (SHM) is a process of implementing a damage detection and characterization strategy for engineering structures. This paper presents a review of various trends and technology adopted for SHM. However, it focuses …
Published in Recent Trends in Civil Engineering & Technology · Vol. 9, Issue 3, 2019 · pp. 1–10 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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An Overview of Artificially Generated Neural Networks Inside the Brain’s Structure in an Alzheimer’s Disease Patient
Abstract: Alzheimer’s disease produces significant neuronal loss, while the precise mechanisms and timing are yet unknown. Other types of cell death, such necroptosis, parthanatosis, ferroptosis, and cuproptosis, need further investigation. Based on brain images of people with mild cognitive impairment, this study assesses artificial neural networks (ANNs) used to diagnose and predict Alzheimer’s disease (AD). This research was conducted considering growing recognition among researchers and medical professionals regarding the importance of …
Published in Research and Reviews: A Journal of Neuroscience · Vol. 15, Issue 2, 2025 Read article
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Hardware Implementation of Discrete /Inverse Discrete Cosine Transform Using Redundant Number System CORDIC Processors
Abstract: Rapid enhancement in multimedia service running on portable application has forced the development of high quality and low power implementation of complex signal processing algorithms. Image and video processing are typical application of multimedia system. Image compression and decompression using DCT/IDCT are the two algorithms commonly used in MPEG standard of image processing. For an image of N x N size, DCT/IDCT would require N4 multiplications and increases complexity. To …
Published in Journal of VLSI Design Tools and Technology · Vol. 11, Issue 1, 2021 · pp. 35–42 Read article
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Performance Analysis of 1-Bit Half Adder using Different Combinational MOS Logics
Abstract: AbstractAdder is required for many processors designing like microprocessors, digital signal processors, image processing and various VLSI applications. The overall performance of system depends upon the adder circuits due to its presence mainly in critical paths of system. This paper presents half adder circuits using different combinational MOS logics. All the circuits were analyzed to find the most suitable circuit which consumes less power without costing the speed of the …
Published in Journal of Microelectronics and Solid State Devices · Vol. 4, Issue 3, 2017 · pp. 19–27 Read article
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Automated Evaluation of Descriptive Answers
Abstract: This paper offers a smarter system of automatic evaluation of descriptive responses in educational tests. The time-consuming aspect of testing with traditional manual marking, the subjectivity of that process, and the impossibility of scaling it makes it inapplicable, particularly to large academic environments. To resolve the issues, the proposed solution combines the methods of Natural Language Processing (NLP) and hybrid image-text processing on the responses of handwriting and typed answers. …
Published in Emerging Trends in Languages · Vol. 3, Issue 2, 2026 · pp. 1–9 Read article
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Blind Image Quality Assessment: An Overview
Abstract: We have develop an efficient model for improving image quality using IQA and NSS based on blind image Quality Assessment.. This algorithm does computation for the parameters which user expect at output. The certain extracted features approach relies on a simple Bayesian inference model to predict image quality scores. The project features are based on statistic scenes of discrete cosine transform for images. The estimated parameters of the model are …
Published in Journal of Electronic Design Technology · Vol. 12, Issue 3, 2021 · pp. 1–3 Read article
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Sensor Technologies in Robotics: A Review of Vision, Tactile, and Proximity Sensing Systems
Abstract: Robotics has undergone remarkable advancements in recent decades, largely driven by the integration of cutting-edge sensor technologies. Sensors serve as crucial for allowing robots to precisely logic, interpret, and react to the world around them. Among the most essential sensor types used in robotics are vision sensors, tactile sensors, and proximity sensors. These technologies strengthen a robot’s capacity for successful navigation, for example, object manipulation, and contact with people and …
Published in International Journal of Robotics and Automation in Mechanics · Vol. 3, Issue 1, 2025 · pp. 31–37 Read article