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001449585 001__ 1449585
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001449585 005__ 20230310004408.0
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001449585 008__ 220924s2022\\\\si\\\\\\o\\\\\100\0\eng\d
001449585 019__ $$a1344489829
001449585 020__ $$a9789811948312$$q(electronic bk.)
001449585 020__ $$a9811948313$$q(electronic bk.)
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001449585 0247_ $$a10.1007/978-981-19-4831-2$$2doi
001449585 035__ $$aSP(OCoLC)1344541041
001449585 040__ $$aEBLCP$$beng$$cEBLCP$$dGW5XE$$dYDX$$dEBLCP$$dOCLCF$$dOCLCQ
001449585 049__ $$aISEA
001449585 050_4 $$aQ334
001449585 08204 $$a006.3$$223/eng/20220926
001449585 1112_ $$aInternational Conference on Advances and Applications of Artificial Intelligence and Machine Learning$$d(2021)
001449585 24510 $$aApplications of artificial intelligence and machine learning :$$bselect proceedings of ICAAAIML 2021 /$$cBhuvan Unhelker, Hari Mohan Pandey, Gaurav Raj, editors.
001449585 2463_ $$aICAAAIML 2021
001449585 260__ $$aSingapore :$$bSpringer,$$c2022.
001449585 300__ $$a1 online resource (792 p.).
001449585 4901_ $$aLecture notes in electrical engineering ;$$vv. 925
001449585 500__ $$aIdentification of Wheat and Foreign Matter Using Artificial Neural Network and Genetic Algorithm
001449585 504__ $$aReferences -- Exploring Practical Deep Learning Approaches for English-to-Hindi Image Caption Translation Using Transformers and Object Detectors -- 1 Background -- 2 Dataset, Methodology and Experimental Setup -- 2.1 Dataset -- 2.2 Experimental Setup -- 2.3 Pre-processing Dataset -- 2.4 Run-Time Data Handling -- 2.5 Training and Evaluation -- 3 Model Architectures and Configurations Tested -- 3.1 Class A (Seq2Seq Caption Translation) -- 3.2 Class B (Transformer Caption Translation) -- 3.3 Class C (Pre-trained Transformer Caption Translation) -- 4 Results -- 5 Comparison with Existing Work
001449585 5050_ $$aIntro -- Contents -- About the Editors -- Firefly Algorithm and Deep Neural Network Approach for Intrusion Detection -- 1 Introduction -- 1.1 Research Goals and Contributions -- 1.2 Structure of the Paper -- 2 Theoretical Background and Literature Review -- 3 Proposed Method -- 3.1 Enhanced FA Metaheuristics -- 4 The eFA and DNN Framework for IDS Classification Experiments -- 5 Conclusion -- References -- Dimensionality Reduction Method for Early Detection of Dementia -- 1 Introduction -- 2 Related Works -- 3 Methodology -- 3.1 Materials and Subjects -- 3.2 Pre-processing
001449585 5058_ $$a3.3 Feature Reduction -- 4 Result and Discussion -- 5 Conclusion -- References -- Prognostication in Retail World: Analysing Using Opinion Mining -- 1 Introduction -- 2 Literature Survey -- 3 Proposed Model -- 3.1 Sentimental Analysis -- 3.2 Classification Model -- 3.3 Techniques and Tools -- 4 Data -- 5 Evaluation Outcome -- 6 Conclusion -- References -- Impact of Resolution Techniques on Chlorophyll Fluorescence Wheat Images Using Classifier Models to Detect Nitrogen Deficiency -- 1 Introduction -- 2 Related Work -- 3 Experimental Setup -- 4 Results and Discussions -- 5 Conclusions
001449585 5058_ $$a6 Conclusion -- References -- Saving Patterns and Investment Preferences: Prediction Through Machine Learning Approaches -- 1 Introduction -- 2 Review of Literature and Hypothesis Development -- 3 Data Analysis -- 3.1 Regression Equation and Data -- 4 Result Analysis and Discussion -- 4.1 Effect of Eight Independent Variables on the Saving Patterns -- 4.2 Effect of Eight Independent Variables on the Investment Preferences -- 4.3 Discussion -- 5 Conclusion -- References -- A Machine Learning Based Approach for Detection of Distributed Denial of Service Attacks -- 1 Introduction -- 2 Related Work
001449585 5058_ $$a3 Proposed Framework for DDoS Attack Detection -- 3.1 Problem Definition -- 3.2 The Framework -- 3.3 Proposed Algorithm -- 3.4 Metrics for Performance Evaluation -- 4 Experimental Results -- 5 Conclusion and Future Work -- References -- Convolutional Neural Network Based Automatic Speech Recognition for Tamil Language -- 1 Introduction -- 2 Literature Review -- 3 Convolution Neural Network -- 4 Experimental Setup -- 4.1 Feature Extraction -- 4.2 Convolutional Neural Network Model -- 5 Result and Discussion -- 6 Conclusion -- References
001449585 506__ $$aAccess limited to authorized users.
001449585 520__ $$aThe book presents a collection of peer-reviewed articles from the International Conference on Advances and Applications of Artificial Intelligence and Machine Learning ICAAAIML 2021. The book covers research in the areas of artificial intelligence, machine learning, and deep learning applications in health care, agriculture, business, and security. This book contains research papers from academicians, researchers as well as students. There are also papers on core concepts of computer networks, intelligent system design and deployment, real-time systems, wireless sensor networks, sensors and sensor nodes, software engineering, and image processing. This book is a valuable resource for students, academics, and practitioners in the industry working on AI applications.
001449585 588__ $$aOnline resource; title from PDF title page (SpringerLink, viewed September 26, 2022).
001449585 650_0 $$aArtificial intelligence$$vCongresses.
001449585 650_0 $$aMachine learning$$vCongresses.
001449585 655_0 $$aElectronic books.
001449585 655_7 $$aConference papers and proceedings.$$2fast$$0(OCoLC)fst01423772
001449585 7001_ $$aUnhelkar, Bhuvan.
001449585 7001_ $$aPandey, Hari Mohan.
001449585 7001_ $$aRaj, Gaurav.
001449585 77608 $$iPrint version:$$aUnhelker, Bhuvan$$tApplications of Artificial Intelligence and Machine Learning$$dSingapore : Springer,c2022$$z9789811948305
001449585 830_0 $$aLecture notes in electrical engineering ;$$vv. 925.
001449585 852__ $$bebk
001449585 85640 $$3Springer Nature$$uhttps://univsouthin.idm.oclc.org/login?url=https://link.springer.com/10.1007/978-981-19-4831-2$$zOnline Access$$91397441.1
001449585 909CO $$ooai:library.usi.edu:1449585$$pGLOBAL_SET
001449585 980__ $$aBIB
001449585 980__ $$aEBOOK
001449585 982__ $$aEbook
001449585 983__ $$aOnline
001449585 994__ $$a92$$bISE