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150 articles for “convolutional neural network processing”
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Detect Fraud Bank Checks with Convolutional Neural Network Processing Algorithm
Abstract: AbstractThe purpose of this study is to design and build a fraud check detection system with a Convolutional Neural Network (CNN) algorithm to quickly and easily detect a fraud or altered bank check in real time. A MATLAB Deep Learning Toolbox with related CNN algorithm is used to assist this study to quickly detect any fraud or altered bank check when it is deposited and scanned by a scanner in …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 7, Issue 3, 2020 · pp. 18–29 Read article
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Real-world Pothole Detection Using Image Processing and Deep Learning Convolutional Neural Network Model
Abstract: Potholes are a major problem of concern in many parts of the cities across the country. Road accidents are one of the causes that significantly affect humanity and result in damage to vehicles and road surface. Potholes are dangerous for pedestrians who walk along the road and vehicular traffic on busy roads. Road accidents are caused due to improper maintenance of roads, and it is imperative to attend to such …
Published in Journal of Computer Technology & Applications · Vol. 14, Issue 3, 2023 · pp. 95–103 Read article
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DeMe-Net Model to Diagnose Skin Cancer Disease from Skin Lesion
Abstract: Skin cancer is a quite common disease in the world and Melanoma is one of the serious types of skin cancer. It begins in melanocyte cells. Skin irritation or tanning due to UV radiation triggers changes in melanocytes, leading to uncontrolled growth of cells. It can potentially develop and spread if it is not treated early. The biopsy is a traditionally used method to diagnose skin cancer in which a …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 8, Issue 3, 2021 · pp. 10–20 Read article
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Digital Entry of Bank Related Slips Using Character Recognition
Abstract: Standing in long queues in bank for small work like depositing the money is very frustrating and also wastes a lot of time. The bank employee handles all the work such as making the entry of money deposited or credit from the account manually by typing information such as account number, amount, etc. and due this creates long queues in banks for such small tasks. Thus, we have come up …
Published in Trends in Opto-electro & Optical Communication · Vol. 11, Issue 3, 2021 · pp. 30–35 Read article
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Vegetation Classification Based on Leaf Pattern
Abstract: In this current world, vital species of plants are going to be lost day by day. To command, this phenomenon, steps are first discovering then restoring and retain them. Among them, spotting of plant is giving up challenging. Usually, plants are recognizing from their leaves. In this paper, a deep neural network model is implemented which will extract the hidden pattern form leaf images. A classifier named as Convolutional Neural …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 8, Issue 3, 2021 · pp. 9–16 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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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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Heart Disease Evaluation Through Echocardiography Using CNN, ResetNet50, VGG16, and Image Processing
Abstract: Heart conditions stand out as primary contributors to untimely mortality among adults aged 30 and above, notably among those grappling with elevated cholesterol levels and diabetes. Detecting such ailments often necessitates the use of an echocardiogram, providing an intricate portrayal of the heart. However, precise analysis hinges on both the proper functioning of the echocardiogram apparatus and the proficiency of a skilled radiologist, a condition not always met. Manual scrutiny …
Published in International Journal of Information Security Engineering · Vol. 2, Issue 2, 2024 · pp. 25–35 Read article
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Automated Crop Disease Detection Using Convolutional Neural Networks
Abstract: Crop diseases contribute to major losses in agricultural production worldwide generating enormous economic costs. This study investigates the possibility of Convolutional Neural Networks (CNN) imaging techniques to auto-detect diseases associated with plants through image processing. A model was developed and trained on a publicly available plant disease dataset containing labeled images of several diseases. The CNN could classify various plant diseases with accuracy of 95%, precision of 92%, and recall …
Published in International Journal of Cheminformatics · Vol. 3, Issue 2, 2025 · pp. 7–15 Read article
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Examining the Crowd in Real-time with Deep Learning
Abstract: In this research, a model is proposed that can be used to estimate crowd density in a specific region and to establish social distances in accordance with predetermined rules. This is accomplished utilizing a multi-source model-based approach. In a small public gathering where hand counting is impossible, this technique conducts a survey. To do this, input video frames are extracted, each frame is processed, and then passed to the model …
Published in Journal of Computer Technology & Applications · Vol. 14, Issue 1, 2023 · pp. 41–45 Read article
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Detection of Driver Emotion Using Deep Learning
Abstract: High level Driver-Help Frameworks (ADASs) are utilized for expanding security in the auto space, yet momentum ADASs quite work without considering drivers' states, e.g., whether she/he is genuinely able to drive. Feelings are a significant way of behaving of people and may emerge in driving circumstances. Uncontrolled feelings can prompt unsafe impacts. To control and decrease the adverse consequence of conduct. In this paper we will distinguish the driver’s conduct. …
Published in International Journal of Electronics Automation · Vol. 1, Issue 1, 2023 · pp. 01–06 Read article
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Deep-globe Challenge for Road Extraction Using Convolution Neural Network
Abstract: High-resolution lackey pictures contain a riches of information. They're too intense to decipher. For various operations, it's vital to snappily and straightforwardly distinguish streets from fawning pictures. The thought is to create a bracket demonstration to prize street systems from today’s pictures. The technique of the proposed strategy is grounded on the pre-processing of the disciple information to enhance the picture quality, which in turn comes about in superior comes …
Published in International Journal of Satellite Remote Sensing · Vol. 2, Issue 1, 2024 · pp. 1–10 Read article
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Crop Disease Prediction Using Image Processing
Abstract: For any country in the world, its livelihood depends on agriculture. However, crop diseases affect the production and food supply of any country because we are unable to detect crop diseases. This paper presents a machine learning CNN (convolutional neural network) model, which uses images of crops to detect diseases. This model detects the diseases in the early stage and provides us with a solution to the crop diseases. It …
Published in Research and Reviews : Journal of Crop science and Technology · Vol. 15, Issue 2, 2026 · pp. 9–16 Read article
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Machine Learning Approach to Detect and Analyze Attention-Deficit/Hyperactivity Disorder
Abstract: Attention-Deficit/Hyperactivity Disorder (ADHD) is a neurodevelopmental disorder characterized by difficulties with attention, impulse control, behavioral regulation, and daily functioning that persist across childhood and adulthood. Clinical diagnosis is predominantly based on behavioral assessments and expert interpretation, which may result in subjectivity and delayed clinical decisions. To reduce reliance on subjective evaluation, this study introduces an automated ADHD identification framework that integrates resting-state functional Magnetic Resonance Imaging (rs-fMRI) with advanced machine …
Published in Research and Reviews: A Journal of Neuroscience · Vol. 16, Issue 2, 2026 · pp. 22–26 Read article
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Greenhouse Automation
Abstract: The demand has been increasing in the automation sector, to successfully nurture and grow a plant yield. The most important thing here is to moniter the plants during their growth cycle. In this system image processing is used to monitor the disease on leaf after the image of the infected leaf is captured by a robot. For the classification purpose convolutional neural network is used. It can work with a …
Published in Journal of Operating Systems Development & Trends · Vol. 7, Issue 2, 2020 · pp. 14–18 Read article
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Mood Mate: A Solid-State Edge-AI System for Real-Time Facial Emotion Recognition
Abstract: Recent progress in solid-state electronics and embedded vision systems has enabled real-time emotion-aware applications at the edge. This paper presents MoodMate, a solid-state edge-AI framework for real-time facial emotion recognition using camera-based sensing and embedded processing. The proposed system integrates a solid-state image sensor with an AI- driven emotion classification pipeline optimized for low-latency and resource-constrained environments. Intelligent, emotion-aware apps can now be deployed right at the network edge thanks …
Published in International Journal of Solid State Innovations & Research · Vol. 3, Issue 2, 2025 · pp. 24–30 Read article
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Avian Echoes: Convolutional Neural Network for Bird Vocalization Detection
Abstract: Bird species identification is a complex task within ornithology that demands advanced technological solutions. This research presents an approach leveraging Convolutional Neural Networks (CNNs) for bird species recognition based on identification of bird sound, each employing unique datasets and methodologies. The objective involves a two-stage identification process, beginning with the construction of an ideal dataset. The crucial step involves converting 1D audio waveforms to 2D spectrograms, enhancing CNNs' ability to …
Published in Journal of Aerospace Engineering & Technology · Vol. 14, Issue 2, 2024 · pp. 26–37 Read article
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Synopsis of Plant Disease Detection Methodologies and their effect on Environment
Abstract: Agriculture is the primary occupation in India. It accounts for 18% GDP and provides employment to 50% of country’s labour’s. However, due to climate change, yield of crops is reducing and affecting Indian economy. One of the reason behind this is increase in number of plant diseases. So, disease detection becomes vital. But it needs huge personnel, additional processing time, extensive knowledge on plants and their diseases. Hence, machine learning …
Published in Journal of Energy, Environment & Carbon Credits · Vol. 10, Issue 3, 2020 · pp. 16–21 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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An AI-Driven IoT Framework for Autonomous Quality Assurance in Optical Lens Manufacturing
Abstract: The evolution of high-precision optics—ranging from smartphone micro-lenses to high-end astronomical glass—demands unprecedented accuracy in manufacturing. Traditional inspection methods, reliant on manual sampling or static automated optical inspection (AOI), often fail to bridge the gap between high-speed production and the detection of microscopic surface aberrations. This paper introduces an integrated architecture combining the Internet of Things (IoT) and Deep Learning-based decision-making systems to revolutionize lens quality control. By deploying an …
Published in International Journal of Optical Innovations & Research · Vol. 4, Issue 1, 2026 · pp. 36–41 Read article