000 | 03901nam a22006135i 4500 | ||
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001 | 978-981-19-4687-5 | ||
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_a9789811946875 _9978-981-19-4687-5 |
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_a10.1007/978-981-19-4687-5 _2doi |
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_aData, Engineering and Applications _h[electronic resource] : _bSelect Proceedings of IDEA 2021 / _cedited by Sanjeev Sharma, Sheng-Lung Peng, Jitendra Agrawal, Rajesh K. Shukla, Dac-Nhuong Le. |
250 | _a1st ed. 2022. | ||
264 | 1 |
_aSingapore : _bSpringer Nature Singapore : _bImprint: Springer, _c2022. |
|
300 |
_aIX, 705 p. 314 illus., 235 illus. in color. _bonline resource. |
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336 |
_atext _btxt _2rdacontent |
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337 |
_acomputer _bc _2rdamedia |
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_aonline resource _bcr _2rdacarrier |
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_atext file _bPDF _2rda |
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490 | 1 |
_aLecture Notes in Electrical Engineering, _x1876-1119 ; _v907 |
|
505 | 0 | _a1. Medical Assistance Chatbot using Deep Learning -- 2. Distortion Controlled Secure Reversible Data Hiding in H.264 videos -- 3. A Method for improving Efficiency and Security of FANET using Chaotic Black Hole Optimization based Routing (BHOR) Technique -- 4. Machine Learning Techniques for Intrusion Detection System: A Survey -- 5. Software Fault Detection by using Rider Optimization Algorithm (ROA) based Deep Neural Network (DNN) -- 6. An Approach for Predicting Admissions in Post Graduate Program by using Machine Learning -- 7. A Survey on Various Representation Learning of Hypergraph for Unsupervised Feature Selection -- 8. A brief study of time series forecasting technique using linear regression, SVM, LSTM, ARIMA and SARIMA -- 9. Adoption of Blockchain Technology for Storage & Verification of Educational Documents -- 10. Obstacle Collision Prediction model for Path Planning Using Obstacle Trajectory Clustering. | |
520 | _aThe book contains select proceedings of the 3rd International Conference on Data, Engineering, and Applications (IDEA 2021). It includes papers from experts in industry and academia that address state-of-the-art research in the areas of big data, data mining, machine learning, data science, and their associated learning systems and applications. This book will be a valuable reference guide for all graduate students, researchers, and scientists interested in exploring the potential of big data applications. | ||
650 | 0 |
_aEngineering _xData processing. |
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650 | 0 |
_aInformation technology _xManagement. |
|
650 | 0 | _aMachine learning. | |
650 | 0 | _aBig data. | |
650 | 1 | 4 | _aData Engineering. |
650 | 2 | 4 | _aComputer Application in Administrative Data Processing. |
650 | 2 | 4 | _aMachine Learning. |
650 | 2 | 4 | _aBig Data. |
700 | 1 |
_aSharma, Sanjeev. _eeditor. _4edt _4http://id.loc.gov/vocabulary/relators/edt |
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700 | 1 |
_aPeng, Sheng-Lung. _eeditor. _4edt _4http://id.loc.gov/vocabulary/relators/edt |
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700 | 1 |
_aAgrawal, Jitendra. _eeditor. _4edt _4http://id.loc.gov/vocabulary/relators/edt |
|
700 | 1 |
_aShukla, Rajesh K. _eeditor. _4edt _4http://id.loc.gov/vocabulary/relators/edt |
|
700 | 1 |
_aLe, Dac-Nhuong. _eeditor. _4edt _4http://id.loc.gov/vocabulary/relators/edt |
|
710 | 2 | _aSpringerLink (Online service) | |
773 | 0 | _tSpringer Nature eBook | |
776 | 0 | 8 |
_iPrinted edition: _z9789811946868 |
776 | 0 | 8 |
_iPrinted edition: _z9789811946882 |
776 | 0 | 8 |
_iPrinted edition: _z9789811946899 |
830 | 0 |
_aLecture Notes in Electrical Engineering, _x1876-1119 ; _v907 |
|
856 | 4 | 0 | _uhttps://doi.org/10.1007/978-981-19-4687-5 |
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