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Titlebook: Computer Vision and Image Processing; 4th International Co Neeta Nain,Santosh Kumar Vipparthi,Balasubramanian Conference proceedings 2020 S

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發(fā)表于 2025-3-28 14:47:58 | 只看該作者
https://doi.org/10.1007/978-1-4302-0071-0ignatures and abundance fractions. A novel algorithm called Energy-based Convex Set (ECS) is presented for unsupervised endmember extraction from hyperspectral data in this paper. The algorithm uses the concept of band-energy and convex geometry for extraction of endmembers. The advantage of the pro
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發(fā)表于 2025-3-28 20:51:47 | 只看該作者
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發(fā)表于 2025-3-29 01:43:04 | 只看該作者
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發(fā)表于 2025-3-29 07:47:11 | 只看該作者
The Definitive Guide to MySQL 5of these approaches are flexible enough to be deployed in the real-time environment with limited computational capabilities. Inference latency is a major factor that limits the application of such methods to the real world scenarios where high end GPUs cannot be deployed. Six models based on three a
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發(fā)表于 2025-3-29 14:25:29 | 只看該作者
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發(fā)表于 2025-3-30 00:38:03 | 只看該作者
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發(fā)表于 2025-3-30 05:06:20 | 只看該作者
Real-World Application Development,processing techniques. In this proposed method we have applied Neural network based feature extraction method along with Support Vector Machine (SVM) based linear classifier to classify normal CT- scan images and kidney stone images. All the CT scan kidney images are initially preprocessed to filter
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