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41 articles for “image detection”
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AI-Based Image Detection of Rice Crop Diseases Using Deep Learning and Grad-CAM
Abstract: The Indian economy relies heavily on agriculture, and rice is one of the most significant staple crops grown in the country. Nevertheless, rice cultivation faces numerous challenges due to several leaf diseases, such as bacterial leaf blight, brown spot, and leaf smut. These diseases can lead to substantial yield losses and financial burdens for farmers. Therefore, the early detection and classification of these diseases are essential to minimize crop damage …
Published in International Journal of Plant Biotechnology · Vol. 12, Issue 2, 2026 Read article
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Advanced Security System for Residential Complexes
Abstract: A sophisticated apartment safety system aimed at preventing unauthorized access and enhancing security within residential complexes. The system employs facial recognition technology to identify residents and regular visitors while capturing the pictures and data of unknown individuals upon entry. These individuals are provided with an RFID tag, enabling continuous tracking of their movement within the premises until they reach their intended destination so that we can monitor the person and …
Published in International Journal of Image Processing and Pattern Recognition · Vol. 11, Issue 1, 2025 · pp. 1–7 Read article
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Facial Expressions Detection Using Machine Learning
Abstract: Facial expressions are necessary in human communication and understanding emotions. First and foremost, identifying emotions is a critical factor for many businesses to comprehend how their customers are responding to the things they have introduced. It can also be utilized to find out if the amenities provided to their staff are meeting their needs. Additionally, it has a plethora of other applications, such as utilizing a camera to identify someone's …
Published in International Journal of Image Processing and Pattern Recognition · Vol. 10, Issue 1, 2024 · pp. 11–16 Read article
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A Review on Design and Analysis Model for Detectionand Classification of Lung Diseases Using Medical Images
Abstract: A key component of the human respiratory system, the lung regulates blood oxygen levels through gasexchange. Diseases linked to the lungs are becoming more common as pollution levels rise. In order topreserve human life, it is crucial to identify lung disorders early. In order to forecast lung disease, clinicalprofessionals analyze medical imaging, such as CT or X-rays. Clinicians identify lung disease by applyingtheir medical expertise and knowledge. Because expert knowledge …
Published in International Journal of Image Processing and Pattern Recognition · Vol. 11, Issue 2, 2025 Read article
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Advancing Early Detection of Menkes Disease Through Image Analysis and Biosensor Integration
Abstract: Menkes disease, a rare X-linked recessive disorder of copper metabolism, poses significant challenges in early diagnosis due to its nonspecific initial symptoms. This paper presents a comprehensive approach to enhance the early detection of Menkes disease by leveraging image processing techniques, pattern recognition algorithms, and innovative biosensor technologies. A novel framework is proposed that combines analysis of hair microscopy images, facial feature recognition, and copper-sensitive biosensors to create a multi-modal …
Published in International Journal of Image Processing and Pattern Recognition · Vol. 10, Issue 2, 2024 · pp. 24–34 Read article
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Comparison Analysis of Lumpy Skin Disease Detection System Using X-Ray Images of Animals with the Help of Deep Learning
Abstract: Lumpy Skin Disease (LSD), caused by the Capripoxvirus, is a highly contagious viral infection impacting cattle and other livestock, resulting in significant economic losses due to decreased productivity and mortality. Early detection is critical to mitigate its spread and reduce its impact on agriculture and dairy sectors. This study investigates the efficacy of deep learning methodologies for detecting LSD through X-ray images, offering a non-invasive diagnostic approach to identify internal …
Published in International Journal of Animal Biotechnology and Applications · Vol. 11, Issue 2, 2025 · pp. 1–5 Read article
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Advanced Classification of Diabetic Retinopathy Using GAN and Deep Residual CNN Model
Abstract: Diabetic retinopathy (DR) is a leading cause of blindness worldwide, impacting the largest number of individuals who have diabetes. Early identification of diabetic retinopathy may help to prevent severe effects; however, the very limited availability of labeled datasets, and the possibility of overfitting of the model, presents obstacles to obtaining an accurate diagnosis. In this research, a hybrid deep learning strategy is introduced, where Generative Adversarial Networks (GANs) are used …
Published in International Journal of Image Processing and Pattern Recognition · Vol. 12, Issue 1, 2026 · pp. 8–16 Read article
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AI-Driven Hybrid Neural Network Architecture for Medical Image Segmentation: A Novel Approach for Early Disease Detection
Abstract: One of the key factors in detecting early diseases is medical image segmentation. Medical image segmentation can be very complex due to the differences in image quality, noise, and specific anatomical structures of individual patients. A novel approach for a hybrid neural network structure that combines the power of convolutional neural networks, and the transformer-based models is described here for improved accuracy and robustness of medical image segmentation. Unlike traditional …
Published in International Journal of Microwave Engineering and Technology · Vol. 11, Issue 1, 2025 · pp. 1–7 Read article
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An approach for Intelligent detection of dirty PV panels using image processing with YOLOv8
Abstract: The efficiency of solar photovoltaic (PV) systems is greatly affected by the condition of panel surfaces, as dust buildup and other impurities can noticeably reduce power output. Traditional maintenance methods rely largely on manual inspection, which can be subjective, inconsistent, and impractical for large-scale installations. To address these challenges, this work investigates a deep learning-based computer vision approach for the automatic assessment of solar panel cleanliness. In this work, a …
Published in International Journal of Renewable Energy and its Commercialization · Vol. 12, Issue 2, 2026 Read article
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Real-Time Traffic Management System Utilizing Machine Learning Techniques
Abstract: AbstractThe rapid increase in the number of vehicles on roads has created significant challenges forconventional traffic management systems, which struggle to efficiently regulate traffic flow undervarying conditions. Traditional traffic signals operate on fixed timing cycles, failing to adapt tofluctuating vehicle densities across different lanes. This inefficiency results in unnecessary delays,increased congestion, longer travel times, and excessive fuel consumption. Additionally, fixed-timingsignals do not account for dynamic traffic patterns, leading to bottlenecks …
Published in International Journal of Transportation Engineering and Traffic System · Vol. 11, Issue 1, 2025 · pp. 24–31 Read article
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Enhancing Image Quality with Deep Learning Techniques for Restoration and Denoising
Abstract: Abstract: Clear and high-quality images have become more and more necessary in recent years due to the rapid development of computer vision-based autonomous systems, including autonomous driving, underwater robots, video surveillance, and medical imaging. However, real-world circumstances, such as inclement weather, underwater scenes, and moving cameras, can lead to poorer-quality photographs. These degradations, which include color distortions, noise, and blurring, hurt how well visual systems accomplish tasks like target tracking, …
Published in International Journal of Broadband Cellular Communication · Vol. 10, Issue 2, 2024 · pp. 1–6 Read article
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Detailed survey on detection of Dirtiness of PV panels using different approaches
Abstract: The accumulation of dust, dirt, bird droppings, pollen, and other environmental contaminants on photovoltaic (PV) panels significantly reduces their power generation efficiency and increases operational and maintenance costs. Therefore, timely and accurate detection of the cleanliness condition of solar panels is essential for maintaining optimal energy production, improving system reliability, and extending the operational lifespan of PV installations. In recent years, considerable research interest has been directed toward automated soiling …
Published in International Journal of Electrical Power System and Technology · Vol. 12, Issue 2, 2026 Read article
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Deep Learning for Smarter Farming: Innovations in Plant Disease Identification
Abstract: Agriculture is the backbone of global food security, yet plant diseases significantly impact crop yields and farmers' livelihoods. Traditional disease detection methods are often time-consuming and require expert intervention, making them less feasible for large-scale farming. Recent advancements in deep learning have revolutionized plant disease identification by offering automated, accurate, and efficient solutions. This article explores innovative deep learning techniques, including convolutional neural networks (CNNs) and transformer-based models, that enhance …
Published in International Journal of Microwave Engineering and Technology · Vol. 11, Issue 1, 2025 · pp. 27–32 Read article
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Facial Emotion-Based Stress Detection Using CNN and Haar Cascade Algorithms
Abstract: Understanding human conduct requires the ability to recognize facial emotions, which has applications in everything from human–computer interaction to psychological wellness monitoring. This research provides a new approach to stress detection using convolutional neural networks and Haar Cascade classifiers. The suggested method uses convolutional neural network to recognize facial expressions and Haar Cascade algorithm for face detection. The methodology begins with preliminary processing of the input photos, followed by face …
Published in International Journal of Microwave Engineering and Technology · Vol. 10, Issue 2, 2024 · pp. 1–11 Read article
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Maculopathy Detection and Recommendation using Machine Learning
Abstract: Maculopathies, a diverse group of eye diseases affecting the central portion of the retina, the macula, are a leading cause of vision loss globally. Early detection and accurate diagnosis are critical for timely intervention and preventing irreversible vision loss. However, traditional methods such as manually detecting the disease are time-consuming, tiring, and often lack sensitivity and specificity, hindering optimal patient care. Here we delve into the applications of machine learning …
Published in International Journal of Embedded Systems and Emerging Technologies · Vol. 10, Issue 1, 2024 · pp. 10–16 Read article
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Denoise Mechanism for Digital Images
Abstract: With the rapid advancement of today’s information technology, the analysis of digital images has endured rapid evolution in technology and is frequently utilized in everyday situations and enterprises. There are specific problems in the transmission process. Images are influenced by the compression of data and communication. In color image processing, a variety of well-established approaches to suppressing noise are offered. The variety of noise corrupting the image determines the nature …
Published in International Journal of Image Processing and Pattern Recognition · Vol. 10, Issue 2, 2024 · pp. 11–17 Read article
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Bone Mass Density and Osteomyelitis in Elderly-An Overview
Abstract: Bone mass density (BMD) plays a critical role in skeletal health, particularly in the elderly, where age-related bone loss increases susceptibility to infections such as osteomyelitis. Osteomyelitis, a severe bone infection often caused by Staphylococcus aureus, is more prevalent in older adults due to factors such as osteoporosis, impaired immune function, diabetes, and peripheral vascular disease. Reduced BMD weakens bone integrity, making it more vulnerable to fractures and microbial invasion, …
Published in International Journal of Geriatric Nursing · Vol. 8, Issue 1, 2025 Read article
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A Sensor-Based Soil Monitoring System for Better Crop Harvesting
Abstract: Crop productivity is strongly affected by soil health, environmental conditions, and the availability of timely and accurate monitoring data. Traditional soil testing and crop assessment methods are labor-intensive and time-consuming. They also lack real-time capabilities, which limits efficient agricultural decision-making. This paper proposes an IoT-enabled smart soil monitoring and crop management system that provides real-time analysis of important soil and environmental parameters to improve agricultural productivity. The proposed system uses …
Published in International Journal of Plant Biotechnology · Vol. 12, Issue 1, 2026 · pp. 18–24 Read article
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A Study of Segmentation Techniques for Diagnosing Melanoma in Dermoscopic Images
Abstract: Skin cancer remains among the deadliest forms of cancer, with an average survival rate ranging from 18% to 20%. Detecting and segmenting melanoma early is a challenging yet crucial undertaking. To effectively segment the lesions, several studies have presented automated and standard techniques. Likewise, traditional methods for segmentation frequently require inputs from humans and cannot be applied in automated systems. The aim of this article is to provide a comparative …
Published in International Journal of Image Processing and Pattern Recognition · Vol. 10, Issue 1, 2024 · pp. 1–10 Read article
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A Review of Real-Time Human Detection
Abstract: The real-time human detection and counting system leverages deep learning and computer vision to detect individuals, classify gender, and estimate age from live video feeds or CCTV footage. Implemented using flask as a lightweight web framework, the system manages user authentication, detection control, and real-time result display. A Python-based detection script operates asynchronously, ensuring smooth execution, while results – including counts of males, females, and total individuals – are stored …
Published in International Journal of Image Processing and Pattern Recognition · Vol. 11, Issue 2, 2025 · pp. 29–39 Read article