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Titlebook: Advances in Data-driven Computing and Intelligent Systems; Selected Papers from Swagatam Das,Snehanshu Saha,Jagdish Chand Bansal Conference

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51#
發(fā)表于 2025-3-30 09:36:33 | 只看該作者
https://doi.org/10.1007/978-94-6091-719-6llowers may see each other’s ideas and sentiments, which may spread to more users in the future. Therefore, this research proposes a concept named “sentiment community”. The purpose is to explore the feelings and interactions of users on social networking sites. We have used graphs for the modelling
52#
發(fā)表于 2025-3-30 15:39:32 | 只看該作者
Anita Hussenius,Kathryn Scantlebury. Electroencephalogram (EEG) trials from eight channels collected during an oddball experiment were used in this analysis. All the trials were divided into non-target (non-P300) and target (P300) trial cohorts. Data-driven correlated component analysis (CorrCA) was applied to both cohorts separately
53#
發(fā)表于 2025-3-30 19:46:52 | 只看該作者
Sherry A. Southerland,Sibel Uysal Bahbaht there should exist a system that can handle the queries raised by a farmer in regional language and respond to queries asked with minimal human involvement. The proposed framework accepts the farmers‘ queries spoken in Kannada language and translates the Kannada query into English query. The trans
54#
發(fā)表于 2025-3-30 21:18:57 | 只看該作者
M.-H. Chiu,P. J. Gilmer,D. F. Treagusts based on their speech features extracted from the speech utterances. After the recent developments of deep learning (DL) models, deep convolutional neural networks (DCNNs) have been widely used for solving the SI tasks. A CNN model consists of mainly two parts, deep convolutional feature extractio
55#
發(fā)表于 2025-3-31 01:05:14 | 只看該作者
https://doi.org/10.1007/978-3-030-50797-8 speech processing. It plays a vital role in various real-life applications such as Internet of things (IoT) devices and assistive technology to name a few. The deep learning models like convolutional neural networks (CNNs) have shown the potential ability to solve SCR tasks. However, these models’
56#
發(fā)表于 2025-3-31 08:03:59 | 只看該作者
https://doi.org/10.1007/978-3-030-50797-8n and prevention measures help in improving the farm productivity. Internet of Things (IoT)-based monitoring techniques are required to reduce the manual efforts and improve the precision in decision making. Sensor-based Internet of Things (SBIoT) is capable of providing a framework for remote monit
57#
發(fā)表于 2025-3-31 10:00:25 | 只看該作者
58#
發(fā)表于 2025-3-31 16:33:20 | 只看該作者
59#
發(fā)表于 2025-3-31 21:28:06 | 只看該作者
60#
發(fā)表于 2025-4-1 01:37:51 | 只看該作者
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