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Titlebook: Information, Communication and Computing Technology; 6th International Co Mahua Bhattacharya,Latika Kharb,Deepak Chahal Conference proceedi

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41#
發(fā)表于 2025-3-28 16:33:39 | 只看該作者
42#
發(fā)表于 2025-3-28 18:55:26 | 只看該作者
Secure Data Transmission Techniques for Privacy Preserving Computation Offloading Between Fog Compute consumers brought Cloud Computing in existence. But computation on cloud is expensive and continuous expansion of this field leads to an arising security concern. This led to the creation of Fog Computing, a layer that transcends the barrier between cloud and edge devices, that operates on most of
43#
發(fā)表于 2025-3-29 01:52:18 | 只看該作者
44#
發(fā)表于 2025-3-29 07:08:06 | 只看該作者
Web-Based Real-Time Gesture Recognition with Voiceproposed application are taken in the form of hand gestural inputs with the help of webcam. This application also helps to interact with google home or smart home of google. As the gestures captured by the webcam can be given for functionality which works for google home and the application can spea
45#
發(fā)表于 2025-3-29 09:56:09 | 只看該作者
A MapReduce Approach to Automatic Key File Updates for SPT (Squeeze, Pack and Transfer) Algorithmzing the available network resources and reducing size of dataset by using inbuilt compression algorithm. This paper epitomizes the use of MapReduce for finding out symmetrical binary keys for SPT (Squeeze Pack and Transfer) algorithm from various data files available on public cloud domains. This p
46#
發(fā)表于 2025-3-29 12:05:13 | 只看該作者
Measurement of Liquid Level Using Prediction Methodologys for level measurement are also varies in every place. In this paper, work is done on video-based level measurement for scientific purpose where it requires accuracy in millimeter range. The camera for video capturing is placed at some distance and by image processing the level of liquid can be det
47#
發(fā)表于 2025-3-29 16:19:44 | 只看該作者
48#
發(fā)表于 2025-3-29 20:15:03 | 只看該作者
49#
發(fā)表于 2025-3-30 02:01:06 | 只看該作者
Empirical Laws of Natural Language Processing for Neural Language Generated Textd the text and language, it leads to a significant reduction in human involvement. Many sequence models show great work in generating human like text, but the amount of research work done to check the extent up to which their results match the man-made texts are limited in number. In this paper, the
50#
發(fā)表于 2025-3-30 07:07:11 | 只看該作者
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