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- W137453652 abstract "This paper presents a novel approach for the segmentation of ground based images of rocks using artificial neural network architecture. Artificial neural network as a color classifier allows a vigorous categorization even under various colors saturation variations, brightness, and non-homogeneous ambient illumination conditions. The designed system actually identifies the possible minerals by analyzing the surface color of the rocks. The rocks in Balochistan are very hard and defined. Such rocks are typically full of minerals. The rocks in Balochistan are peculiar in their shape and surface colour. Usually, these colours are developed due to the reaction of the particles of the minerals with air. The upper layer if dust upon these rocks can be really useful in identifying the possible minerals concealing inside the rocks. The designed mechanism outperforms conventional artificial neural networks since it allows the network to learn to solve the task through a dynamic adaptation of its classification context. The designed system is trained by providing it the basic information related to the physical features of various mineral and types of rocks." @default.
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- W137453652 date "2006-01-01" @default.
- W137453652 modified "2023-09-22" @default.
- W137453652 title "Prediction of Minerals by Identifying Various Types of Rocks using Neural Networks" @default.
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