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Titlebook: Advances in Signal Processing and Communication Engineering; Select Proceedings o Pradip Kumar Jain,Yatindra Nath Singh,S. P. Singh Confere

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樓主: CURD
21#
發(fā)表于 2025-3-25 04:45:14 | 只看該作者
Moderation von Gruppendiskussionen,t is the optimal grid size for RSA. In this paper, we determine suitable grid sizes with the help of connection blocking probability, bandwidth blocking probability, and spectrum efficiency as the performance parameters under different demand bandwidth distributions.
22#
發(fā)表于 2025-3-25 08:08:29 | 只看該作者
Arbeitsmethoden der Gruppendynamik, dimension based on PCA. The feature maps are then sent to a classifier to find out the class of that particular image. The proposed algorithm is compared with three existing feature extractors and shows a good classification accuracy compared to others for camouflaged images.
23#
發(fā)表于 2025-3-25 15:23:01 | 只看該作者
24#
發(fā)表于 2025-3-25 18:05:01 | 只看該作者
https://doi.org/10.1007/978-3-658-19377-5NNs) and transfer learning algorithms VGG16. This approach utilizes handwritten MODI script characters from the IEEE Dataport dataset. The Vgg16 algorithm performs better than the CNN algorithms for utilizing a handwritten Modi script characters dataset.
25#
發(fā)表于 2025-3-25 20:52:22 | 只看該作者
Die Gruppe in der Analytischen Psychologiey, gases, and current levels) continuously with respect to precise location and time. The results presented are preliminary and further work is being carried out to develop a full-fledged Reefer monitoring system that delivers continuous information to the driver and central station.
26#
發(fā)表于 2025-3-26 03:34:46 | 只看該作者
27#
發(fā)表于 2025-3-26 07:34:39 | 只看該作者
,Multiclass Classification of?Camouflage Images Using Combined WLD and?LPQ Feature Set Using a?ANN C dimension based on PCA. The feature maps are then sent to a classifier to find out the class of that particular image. The proposed algorithm is compared with three existing feature extractors and shows a good classification accuracy compared to others for camouflaged images.
28#
發(fā)表于 2025-3-26 09:43:52 | 只看該作者
,Analysis of?Image Quality and?Video Denoising Using Convolutional Neural Networks,using the same algorithm trained for image denoising. A comparative analysis of a various deep learning denoising algorithms is performed in terms of image performance parameters like Peak-Signal-to-Noise-Ratio (PSNR) and Structural Similarity Index (SSIM).
29#
發(fā)表于 2025-3-26 14:09:08 | 只看該作者
30#
發(fā)表于 2025-3-26 20:24:57 | 只看該作者
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