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001446121 001__ 1446121
001446121 003__ OCoLC
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001446121 019__ $$a1311464911$$a1311568896$$a1312168583
001446121 020__ $$a9783031039188$$q(electronic bk.)
001446121 020__ $$a3031039181$$q(electronic bk.)
001446121 020__ $$z9783031039171$$q(print)
001446121 020__ $$z3031039173$$q(print)
001446121 0247_ $$a10.1007/978-3-031-03918-8$$2doi
001446121 035__ $$aSP(OCoLC)1312269593
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001446121 049__ $$aISEA
001446121 050_4 $$aQ342
001446121 08204 $$a006.3/1$$223/eng/20220425
001446121 1112_ $$aAMLTA (Conference)$$n(8th :$$d2022 :$$cCairo, Egypt)
001446121 24514 $$aThe 8th International Conference on Advanced Machine Learning and Technologies and Applications (AMLTA2022) /$$cAboul Ella Hassanien, Rawya Y. Rizk, Václav Snášel, Rehab F. Abdel-Kader, editors.
001446121 2463_ $$aAMLTA 2022
001446121 264_1 $$aCham, Switzerland :$$bSpringer,$$c2022.
001446121 300__ $$a1 online resource (1 volume) :$$billustrations (black and white, and color).
001446121 336__ $$atext$$btxt$$2rdacontent
001446121 337__ $$acomputer$$bc$$2rdamedia
001446121 338__ $$aonline resource$$bcr$$2rdacarrier
001446121 4901_ $$aLecture notes on data engineering and communications technologies ;$$vvolume 113
001446121 500__ $$aIncludes author index.
001446121 5050_ $$aIntro -- Preface -- Organization -- Honorary Chair -- General Chairs -- Co-chairs -- International Advisory Board -- Publication Chair -- Program Chairs -- Publicity Chairs -- Technical Program Committee -- Local Arrangement Chairs -- Contents -- Deep Learning and Applications -- Plant Leaf Diseases Detection and Identification Using Deep Learning Model -- 1 Introduction -- 2 Related Works -- 3 Proposed Method -- 4 Experimental Results -- 5 Conclusions -- References -- Reinforcement Learning for Developing an Intelligent Warehouse Environment -- 1 Introduction -- 2 Machine Learning Techniques
001446121 5058_ $$a3 Results and Discussion -- 4 Conclusion and Future Research -- References -- A Low-Cost Multi-sensor Deep Learning System for Pavement Distress Detection and Severity Classification -- 1 Introduction -- 2 Related Work -- 3 Proposed Methodology -- 3.1 Overall System Architecture -- 3.2 Deep Learning Distress Detection -- 3.3 Dataset and Training Information -- 3.4 Projection onto the Depth 3D Point Cloud and ROI Filtering -- 4 Case Study: Pothole Severity Classification -- 5 Experimental Results -- 5.1 Results for the Distress Detection -- 5.2 Results for Pothole Severity Classification
001446121 5058_ $$a6 Conclusion -- References -- An Intrusion Detection Model Based on Deep Learning and Multi-layer Perceptron in the Internet of Things (IoT) Network -- 1 Introduction -- 2 Related Work -- 2.1 Multi Agent Systems for IDS -- 2.2 Fuzzy Systems for IDS -- 2.3 Game Theory Models for IDS -- 3 Architecture of the Proposed Intrusion Detection System -- 3.1 Pre-processing and Feature Engineering -- 3.2 Deep Learning Layer -- 3.3 Evaluation Layer -- 4 The Experimental Results -- 5 Comparison Between Proposed Models and the Others -- 6 Conclusion -- References
001446121 5058_ $$aTransfer Learning and Recurrent Neural Networks for Automatic Arabic Sign Language Recognition -- 1 Introduction -- 2 Related Work -- 3 Arabic Sign Language Dataset -- 4 Methodology -- 4.1 Prepare the Dataset -- 4.2 Extract the Spatial Features -- 4.3 Extract the Temporal Features -- 4.4 Video Augmentation -- 5 Experimental and Results -- 5.1 Experiment Settings -- 5.2 Models Results -- 6 Conclusion and Future Works -- References -- Robust Face Mask Detection Using Local Binary Pattern and Deep Learning -- 1 Introduction -- 2 Related Works -- 3 Proposed Method -- 4 Experimental Results
001446121 5058_ $$a5 Conclusion -- References -- Steganography Adaptation Model for Data Security Enhancement in Ad-Hoc Cloud Based V-BOINC Through Deep Learning -- 1 Introduction -- 1.1 Ad-Hoc Cloud Computing -- 1.2 Deep Steganography -- 1.3 Contribution -- 1.4 Paper Organization -- 2 Literature Review -- 3 Proposed Solution -- 4 Experiment -- 5 Discussion and Analysis -- 6 Conclusion -- References -- Performance of Different Deep Learning Models for COVID-19 Detection -- 1 Introduction -- 2 Deep Learning (DL) -- 2.1 The DL-Algorithms Steps in COVID-19 Diagnosis -- 2.2 DL-Models for COVID-19 Detection
001446121 506__ $$aAccess limited to authorized users.
001446121 520__ $$aThis book constitutes the refereed proceedings of the 8th International Conference on Advanced Machine Learning Technologies and Applications, AMLTA 2022, held in Cairo, Egypt, during May 5-7, 2022. The 8th edition of AMLTA will be organized by the Scientific Research Group in Egypt (SRGE), Egypt, collaborating with Port Said University, Egypt, and VSB-Technical University of Ostrava, Czech Republic. AMLTA series aims to become the premier international conference for an in-depth discussion on the most up-to-date and innovative ideas, research projects, and practices in the field of machine learning technologies and their applications. The book covers current research on advanced machine learning technology, including deep learning technology, sentiment analysis, cyber-physical system, IoT, and smart cities informatics and AI against COVID-19, data mining, power and control systems, business intelligence, social media, digital transformation, and smart systems.
001446121 588__ $$aDescription based on print version record.
001446121 650_0 $$aMachine learning$$vCongresses.
001446121 650_0 $$aArtificial intelligence$$vCongresses.
001446121 650_6 $$aApprentissage automatique$$vCongrès.
001446121 650_6 $$aIntelligence artificielle$$vCongrès.
001446121 655_7 $$aConference papers and proceedings.$$2fast$$0(OCoLC)fst01423772
001446121 655_0 $$aElectronic books.
001446121 7001_ $$aHassanien, Aboul Ella,$$eeditor.
001446121 7001_ $$aRizk, Rawya Y.,$$eeditor.
001446121 7001_ $$aSnášel, Václav,$$d1957-$$eeditor.$$1https://isni.org/isni/0000000122819840
001446121 7001_ $$aAbdel-Kader, Rehab F.,$$eeditor.
001446121 77608 $$iPrint version:$$aAMLTA (Conference) (8th : 2022 : Cairo, Egypt), creator.$$t8th International Conference on Advanced Machine Learning and Technologies and Applications (AMLTA2022).$$dCham : Springer, 2022$$z9783031039171$$w(OCoLC)1308493966
001446121 830_0 $$aLecture notes on data engineering and communications technologies ;$$vv. 113.
001446121 852__ $$bebk
001446121 85640 $$3Springer Nature$$uhttps://univsouthin.idm.oclc.org/login?url=https://link.springer.com/10.1007/978-3-031-03918-8$$zOnline Access$$91397441.1
001446121 909CO $$ooai:library.usi.edu:1446121$$pGLOBAL_SET
001446121 980__ $$aBIB
001446121 980__ $$aEBOOK
001446121 982__ $$aEbook
001446121 983__ $$aOnline
001446121 994__ $$a92$$bISE