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607 articles for “images”
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Sensors based Human Visual System: e-Retina
Abstract: This study explores the potential of bio-inspired sensor design to replicate the adaptive and highly efficient nature of the human visual system and e-retina. This study presents a novel sensor array incorporating foveated vision principles and dynamic range adaptation mechanisms. Our study demonstrates the improved performance of this system in complex visual scenes, particularly in low illumination and high-contrast scenarios. This study highlights the advantages of mimicking biological principles in …
Published in Trends in Opto-electro & Optical Communication · Vol. 15, Issue 1, 2025 · pp. 14–22 Read article
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Intrusion Eye Detector
Abstract: Uncertainty about security risks and illegal access are becoming more prevalent in a variety of settings, such as private homes, business buildings, and critical government buildings. Conventional security systems, which may not offer real-time warnings or prompt reactions, frequently rely on passive monitoring, including CCTV cameras and motion sensors. Artificial intelligence (AI) and computer vision-based intelligent systems are becoming more and more popular as a means of improving security and …
Published in International Journal of Optical Innovations & Research · Vol. 3, Issue 1, 2025 · pp. 28–32 Read article
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Integrated Dam Automation: Real-Time Monitoring and Controlling Using IoT
Abstract: Dam automation is a critical area in water resource management, especially given the rising demand for sustainable and safe water control systems. An integrated approach to dam automation involves implementing advanced sensors and monitoring systems to improve structural safety, water quality, and resource management. This paper presents a comprehensive automation model that combines crack detection, convolutional neural networks (CNNs), water level monitoring, turbidity sensing, and rainfall data to ensure real-time …
Published in Journal of Microcontroller Engineering and Applications · Vol. 12, Issue 1, 2025 · pp. 31–38 Read article
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Multimodal Disease Detection Using Deep Learning
Abstract: Artificial Intelligence (AI) is playing an increasingly pivotal role in modern healthcare, particularly in improving the speed and accuracy of disease detection. With the evolution of Machine Learning (ML), Deep Learning (DL), and high-performance computing, AI-based solutions are now capable of processing extensive medical datasets, ranging from patient records to diagnostic images, with remarkable efficiency. These systems offer immense potential for early intervention, improved clinical decision-making, and alleviating pressure on …
Published in Journal of Computer Technology & Applications · Vol. 16, Issue 2, 2025 · pp. 129–139 Read article
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Plant Disease Detection Using Machine Learning
Abstract: Plant diseases significantly threaten global crop yields and affect both nutritional safety and farmer income. Accurate and early detection of plant diseases is essential for effective intervention and treatment. In this study, we used the CNN model (convolutional neural network) to explore a deep learning-based approach for plant disease classification. The model was trained and evaluated on a large dataset encompassing 38 different classes of plant disease, including healthy leaves. …
Published in Journal of Multimedia Technology & Recent Advancements · Vol. 12, Issue 2, 2025 · pp. 07–19 Read article
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Classification of Plant Leaf Diseases Using Deep Learning Concepts
Abstract: Agriculture is vital to the economy of a country like India, where 70% of the workforce is employed in this sector. Plants suffering from illnesses experience a significant reduction in output. Delays in the identification of plant diseases lead to decreased yield and plant mortality. The cost of manufacturing is increased since it takes a big number of experts to manually detect plant diseases over several acres of land. The …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 12, Issue 3, 2025 · pp. 46–55 Read article
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Comprehensive Review of Nanomaterials Synthesis Methods, Characterization and Multifaceted Applications in Medical Field
Abstract: Nanomaterials associated by special qualities derived from their nanoscale size nanomaterials have tremendous potential in a variety of industries like, medicine & healthcare. Due to today busy life & unhealthy life schedule many abnormal cell growth take place in our body & affect the other organ. Sometimes it may leads to cancer & others dangerous diseases, nanomaterials such as nanotubes, liposomes & polymeric micelles are help for designing the drugs …
Published in Journal of Polymer & Composites · Vol. 13, Issue 5, 2025 · pp. 657–669 Read article
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Alzheimer’s Disease Classification Based on Transfer Learning of New-CNN Model
Abstract: The long-term, irreversible brain disorder “Alzheimer’s disease (AD)” currently has no known cure. Nonetheless, current medications may impede their advancement. Globally, those over 65 are the primary population affected by Alzheimer’s disease. Accurate detection of this condition requires early diagnosis. Because there are so many people who come with an ailment, manual diagnosis by health specialists is laborious and prone to error. Early detection of AD is a difficult undertaking …
Published in Research and Reviews: A Journal of Neuroscience · Vol. 15, Issue 3, 2025 · pp. 16–23 Read article
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A Dual-Model Deep Learning Framework for Early Alzheimer’s Detection Using Clinical Data and Neuroimaging with Architectural Performance Analysis
Abstract: Alzheimer’s disease (AD) poses a significant global health challenge due to its increasing prevalence and the absence of definitive cures. Early diagnosis is crucial for effective intervention and management. This study presents a dual-model deep learning framework for the early detection and classification of AD using both structured clinical data and neuroimaging datasets. Model 1 utilizes a greedy layer-wise autoencoder approach applied to structured data, achieving optimal binary classification accuracy …
Published in Research and Reviews: A Journal of Neuroscience · Vol. 16, Issue 1, 2026 · pp. 1–12 Read article
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Photonic Diagnostics: Harnessing Optical Sensing for Non-Invasive Assessment of Coronary Obstruction
Abstract: Cardiovascular diseases (CVDs) remain the leading cause of mortality globally, with coronary artery blockages primarily atherosclerosis representing a critical challenge. The gold standard for diagnosing coronary artery disease remains invasive coronary angiography, a procedure that, while precise, carries inherent patient risks, high costs, and logistical burdens. Optical sensors, leveraging the principles of light-tissue interaction, offer real-time, high-resolution insights into vascular health, paving the way for early detection of arterial stenoses …
Published in International Journal of Optical Innovations & Research · Vol. 4, Issue 1, 2026 · pp. 25–30 Read article
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Recent Development to Track Contraband using Muon
Abstract: The muon is one of nature’s fundamental particles discovered in 1937 by Carl Anderson. A muon is an elementary subatomic particle similar to electron, but with a mass approximately 207 times greater and, sometimes it is called as a “heavy electron”. Muons are generated naturally when cosmic rays collide with atoms in earth’s upper atmosphere and, then raining down all the times upon the surface of earth. Muons can be …
Published in International Journal of Universe · Vol. 2, Issue 1, 2026 · pp. 23–34 Read article
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Diffusion-Based Enhancement of Low-SNR Time- Frequency Signals
Abstract: Traditional enhancing techniques are useless in low signal-to-noise ratio (LSNR) situations because noise drastically interferes with communication signals. Based on an enhanced DiffBIR model, this paper suggests a dual-stage signal improvement approach that combines diffusion with deep learning. By combining the Inception module for multi-scale feature extraction with the Pixel Fusion Attention (PFA) module for significant region highlighting, the model improves signal recovery in the time- frequency domain. Experiments show …
Published in Current Trends in Signal Processing · Vol. 17, Issue 2, 2026 Read article
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The Evolution of Bio Crypt Keys: From Concept to Implementation
Abstract: With the rapid increase in data exfiltration due to cyber-attacks, Covert Timing Channels (CTCs) have emerged as a significant and sophisticated network security threat. These channels exploit inter-arrival times of data packets to exfiltrate sensitive information from targeted networks. Detecting CTCs increasingly relies on machine learning techniques, which use statistical metrics to differentiate between malicious (covert) and legitimate (overt) traffic flows. However, as cyber-attacks become more adept at evading detection …
Published in Journal of Control & Instrumentation · Vol. 15, Issue 2, 2024 · pp. 38–45 Read article
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Digital Resurrection: Restoring Fragile Documents with OCR
Abstract: In creating a typical Optical Character Recognition (OCR) system, several steps are involved, such as preprocessing, segmentation, feature extraction, and classification. Preprocessing, which is a particularly interesting and challenging aspect of Document Analysis and Recognition (DAR), deals with converting scanned or photographed images containing machine-printed or handwritten text, including numbers, letters, and symbols, into a format that the system can understand. Segmentation is a crucial task in any OCR system, …
Published in Trends in Opto-electro & Optical Communication · Vol. 14, Issue 2, 2024 · pp. 29–35 Read article
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Pneumonia Detection and Classification Using Deep Learning
Abstract: Pneumonia, an infectious lung disease primarily caused by bacteria, often exacerbated by environmental factors, leads to the accumulation of pus in the lung’s alveoli. Accurate diagnosis through chest X-rays, ultrasounds, or lung biopsies is crucial to avoid misdiagnosis and ensure proper treatment, crucial for patients’ quality of life. Diagnostic capacities have been greatly improved by deep learning advances, especially with convolutional neural networks (CNNs). This research presents a robust CNN-based …
Published in Journal of Microwave Engineering and Technologies · Vol. 11, Issue 3, 2024 · pp. 9–19 Read article
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CBCT: A Boon in Periodontics – A Review
Abstract: Periodontal disease is an inflammatory disease that can be diagnosed mainly based on clinical signs and symptoms. Two-dimensional radiographs are valuable diagnostic tools as an adjunct to the clinical examination in assessing periodontal bone level. Two-dimensional images do not provide accurate bone levels due to its limitations like projection geometry, superimposition of adjacent anatomic structures, leading to the need for three-dimensional imaging that overcomes these limitations. The diagnosis and treatment …
Published in Research and Reviews: A Journal of Dentistry · Vol. 15, Issue 3, 2024 · pp. 7–13 Read article
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Magnetic ZnxFe2–xO3 Nanoparticles Enhanced Nanobiosensor Integrated with MOSFETs for Efficient Detections of Biomolecules and Cancerous Cells
Abstract: The human brain is mostly responsible for intelligence and consciousness. An artificial equivalence of this action is nanobiosensor, which is used in artificial intelligence. The need for nanodiagnostics platforms for detecting diseases at the genetic, molecular, and cellular level has triggered the development of nanobiosensors integrated with MOSFETs. This device enables simple, inexpensive rapid tests, accurate imaging methods, and accurate molecular diagnosis at point-of-care (POC). This device is seen as …
Published in Journal of Nanoscience, NanoEngineering & Applications · Vol. 14, Issue 3, 2024 · pp. 33–44 Read article
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Comparative Study of AI-Driven Fashion Trend Prediction System Using AI and ML: A Review
Abstract: To overcome the challenges in fashion trend forecasting, researchers have introduced several advanced and data-driven approaches. One such method uses a long short-term memory (LSTM) model combined with an encoder-decoder architecture to extract meaningful fashion content and recognize styles from product images. This model achieves higher accuracy in predicting upcoming fashion trends by incorporating varying price intervals and has shown impressive results when evaluated on the Amazon fashion dataset. Another …
Published in E-Commerce for Future & Trends · Vol. 12, Issue 2, 2025 · pp. 35–41 Read article
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Implementation of Drone Technology to Prepare a Contour Map of Nesave Village
Abstract: Nowadays modern surveying techniques or instruments like DGPS, LiDAR and Drones are widely used as they cover more area in less time for surveying. Such techniques can even be used where visiting survey areas are tough or not possible. Drones are used instead of traditional surveying in a village named Nesave. Drones are used to capture images and process them using specialized software such as Agisoft Metashape Professionals and QGIS …
Published in Journal of Geotechnical Engineering · Vol. 12, Issue 2, 2025 · pp. 1–13 Read article
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Magnetic and Radioactive Nanoparticles for Improved Theranostics and AI Assisted Radiation Therapy
Abstract: Nanoparticles based therapeutic and theranostics technique is becoming an active area of research in nanomedicine. The sensitivity, biocompatibility, and stability of magnetic and radioactive nanoparticles determine their functionality. This research highlights the impacts of magnetic and radioactive nanoparticles on therapeutic techniques namely, cell therapy, gene therapy, and tissue regeneration. Then, it is intended to brief a principal role of these therapeutic techniques to envisage theranostics medicine and radiation therapy using …
Published in International Journal of Advance in Molecular Engineering · Vol. 3, Issue 2, 2025 · pp. 10–21 Read article