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Titlebook: Advances in Signal Processing and Intelligent Recognition Systems; 6th International Sy Sabu M. Thampi,Sri Krishnan,Jagadeesh Kannan R. Con

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41#
發(fā)表于 2025-3-28 17:36:19 | 只看該作者
1865-0929 rs and 5 revised short papers presented were carefully reviewed and selected from 50 submissions.?The papers cover?wide research fields including information retrieval, human-computer interaction (HCI), information extraction, speech recognition..978-981-16-0424-9978-981-16-0425-6Series ISSN 1865-0929 Series E-ISSN 1865-0937
42#
發(fā)表于 2025-3-28 19:44:03 | 只看該作者
43#
發(fā)表于 2025-3-29 00:29:00 | 只看該作者
Acoustic Prediction of Elephants for Localization and Movement Tracking Using Sensors and Distance M Euclidean distance measure had been applied in determining the distance between the sensors positioned for object movement tracking. The results of the proposed work shows that the elephant localization results had been more accurate and their movements were tracked compared to the existing approaches.
44#
發(fā)表于 2025-3-29 03:21:42 | 只看該作者
45#
發(fā)表于 2025-3-29 10:51:00 | 只看該作者
46#
發(fā)表于 2025-3-29 13:02:24 | 只看該作者
Tobias Klenze,Sam Bayless,Alan J. Hu produce the boundaries with the desired accuracy. The process of generation of data for input to the model and an operating procedure for the generation of parcel boundaries is described. The generated boundaries are quite satisfactory and will assist in automated recording of the boundaries. This will also reduce the labor-intensive field tasks.
47#
發(fā)表于 2025-3-29 15:48:09 | 只看該作者
48#
發(fā)表于 2025-3-29 20:27:04 | 只看該作者
Markov Chains and Unambiguous Büchi Automataemory (LSTM). The suggested hybrid model (CNN?+?LSTM) obtained accuracies of 85.5% and 99.3% using the ParkinsonHW and HandPD datasets, respectively. We conclude that the quantitative evaluation provided by our model may be considered a helpful tool in the clinical detection of Parkinson’s disease.
49#
發(fā)表于 2025-3-30 01:15:30 | 只看該作者
A Leak Detection in Water Pipelines Using Discrete Wavelet Decomposition and Artificial Neural Netwos of leakage. In addition, the proposed framework discovers the location of the leakage. The experiment results show that the proposed model is effective for detection of water leakage in the system. The evaluation results indicates that the percent of accuracy is 100%.
50#
發(fā)表于 2025-3-30 07:44:18 | 只看該作者
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