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7 articles for “Image Clustering Method”
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Comparative Study of Change Detection Methods in High Resolution Images
Abstract: Natural phenomena including weathering, erosion, volcanic eruptions, and plate tectonics, as well as human activities like agriculture, deforestation, and urbanization, cause the Earth's surface to change continuously. In many different applications, such as environmental monitoring, disaster management, urban planning, agriculture and forestry, climate change studies, resource management, and infrastructure monitoring, it may be extremely beneficial to detect and track these changes. There are various algorithms and methods proposed by many …
Published in Journal of Remote Sensing & GIS · Vol. 15, Issue 2, 2024 · pp. 1–5 Read article
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Image Preprocessing and Analysis on Eye Fundus Images Segmentation by Using Density Clustering Methods
Abstract: In order to do an automated evaluation of various retinal illnesses such as Diabetic retinopathy, Glaucoma, and Macular Edema, fundus images must be pre-processed first. For many reasons, it's difficult to accurately detect the optic disc. Many blood vessels cross the optic disc, making it difficult to discern the disc's boundaries in fundus images. Lesion regions in diabetic retinopathy look very much like an optic disc's colour and texture, so …
Published in Recent Trends in Sensor Research & Technology Read article
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Eye Disease Classification Using K-means Clustering Algorithm and Ensemble Classification Approach
Abstract: In this study, we present a comprehensive approach for the classification of eye diseases, specifically targeting normal, cataract, glaucoma, and diabetic retinopathy conditions. This research uses a dataset from Kaggle, which provides a wide and varied collection of retinal images to ensure good representation. The methodology encompasses advanced image processing and machine learning techniques to ensure accurate diagnosis and prediction. The preprocessing phase involves a series of image enhancement techniques …
Published in International Journal of Bioinformatics and Computational Biology · Vol. 3, Issue 2, 2025 · pp. 15–27 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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Classification and Detection of Brain Tumor using Convolutional Neural Network
Abstract: Tumors are masses created when brain cells multiply uncontrollably. A brain tumor is the medical term for this condition. Brain tumors are a serious and aggressive disease that can lead to a reduced life expectancy. Developing a treatment plan is essential to raising a patient's standard of living. Tumors in different regions of the body are evaluated using a variety of imaging techniques, with MRI pictures being utilized mostly for …
Published in International Journal of Cheminformatics · Vol. 1, Issue 1, 2023 · pp. 8–13 Read article
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Optical Image Sensing and Analysis of Iron Ore Pellets: A Machine Learning Approach
Abstract: The present work is aimed to improve quality control in steel production using SEM imaging and machine learning. High-resolution SEM images of iron ore pellets, primarily composed of hematite and magnetite, are analyzed to understand their microstructural features, which significantly impact pellet performance during reduction processes. Traditional microstructure analysis is manual, time- consuming, and prone to inconsistencies. This study proposes an automated approach using K-Means Clustering, Canny Edge Detection, DBSCAN, …
Published in Journal of Instrumentation Technology & Innovations · Vol. 15, Issue 3, 2025 · pp. 7–18 Read article
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Mechanical & Tribological Characterization of Al2024-Alumina-Graphite Reinforced Monolithic and Hybrid Composites
Abstract: This work investigates the mechanical characteristics of Al2024-Al2O3-Graphite reinforced monolithic and hybrid composites fabricated by the stir casting method. Exploratory work involved the fabrication of monolithic composites with varying Al2O3 contents (5-8 wt%) and hybrid composites with the ratios of Al2O3 (2-6 wt%) and Graphite (1-3 wt%) in matrix Al2024. For improving their dispersion, preheated reinforcement particles were introduced in matrix alloy at controlled stirring rates. A homogeneous particle distribution …
Published in Journal of Polymer & Composites · Vol. 14, Issue 1, 2026 · pp. 823–836 Read article