001451882 000__ 06052cam\a2200637\a\4500
001451882 001__ 1451882
001451882 003__ OCoLC
001451882 005__ 20230310004722.0
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001451882 019__ $$a1354993116
001451882 020__ $$a9783031215179$$q(electronic bk.)
001451882 020__ $$a3031215176$$q(electronic bk.)
001451882 020__ $$z9783031215162
001451882 020__ $$z3031215168
001451882 0247_ $$a10.1007/978-3-031-21517-9$$2doi
001451882 035__ $$aSP(OCoLC)1355216559
001451882 040__ $$aEBLCP$$beng$$cEBLCP$$dGW5XE$$dYDX$$dUKAHL
001451882 049__ $$aISEA
001451882 050_4 $$aQA76.9.D343
001451882 08204 $$a006.3/12$$223/eng/20230103
001451882 1112_ $$aMIKE (Conference)$$n(9th :$$d2021 :$$cOnline)
001451882 24510 $$aMining intelligence and knowledge exploration :$$b9th International Conference, MIKE 2021, Hammamet, Tunisia, November 1-3, 2021, Proceedings /$$cRichard Chbeir, Yannis Manolopoulos, Rajendra Prasath (eds.)
001451882 2463_ $$aMIKE 2021
001451882 260__ $$aCham :$$bSpringer,$$c2022.
001451882 300__ $$a1 online resource (248 p.).
001451882 4901_ $$aLecture notes in artificial intelligence
001451882 4901_ $$aLecture notes in computer science ;$$v13119
001451882 4901_ $$aLNCS sublibrary, SL 7, Artificial intelligence
001451882 500__ $$a"[...] as a virtual event hosted from Hammamet, Tunisia."-- Preface
001451882 500__ $$a3.2 Segmentation of Upper Modifiers
001451882 500__ $$aIncludes author index.
001451882 5050_ $$aIntro -- Preface -- Organization -- Contents -- Type 2 Diabetes Prediction from the Weighted Data -- 1 Introduction -- 2 Materials and Methods -- 2.1 Missing Values Replacement -- 2.2 Normalization -- 2.3 Feature Extraction -- 2.4 N2PS -- 2.5 Weighted Value -- 2.6 Prediction Model -- 2.7 Accuracy -- 2.8 Procedure of the Proposed Work -- 3 Experimental Results -- 4 Conclusion -- References -- Harnessing Energy of M-ary Hopfield Neural Network for Connectionist Temporal Sequence Decoding -- 1 Introduction -- 2 Hopfield Network Based Formulations -- 2.1 Basic Hopfield Network for Static Patterns
001451882 5058_ $$a2.2 M-ary Hopfield Network for Static Patterns -- 2.3 Hopfield Based Network for Sequence Storage and Retrieval -- 3 M-ary HNN for Sequence Storage and Retrieval -- 3.1 Dual Weight Learning -- 3.2 Isolated Sequence Retrieval from M-ary HNN -- 4 Connected Temporal Sequence Decoding Using Extended M-ary HNN -- 4.1 Model -- 4.2 Decoding Process -- 5 Dataset and Experiments -- 5.1 Scenario-A -- 5.2 Scenario-B -- 6 Conclusions -- References -- Integrative Analysis of miRNA-mRNA Expression Data to Identify miRNA-Targets for Oral Cancer -- 1 Introduction -- 2 Background Study -- 3 Materials and Methods
001451882 5058_ $$a3.1 Dataset Used -- 3.2 Proposed Model -- 4 Results -- 5 Conclusion -- References -- Compact Associative Classification for Up and Down Regulated Genes Using Supervised Discretization and Clustering -- 1 Introduction -- 2 Literature Review -- 3 Proposed Method -- 3.1 Data Normalization -- 3.2 Selection of Up and Down Regulated Genes -- 3.3 Discretization -- 3.4 Associative Classifier -- 3.5 Clustering Class Association Rules -- 3.6 Pseudo Algorithm -- 4 Results and Discussion -- 5 Conclusion and Future Work -- References
001451882 5058_ $$aAssessment of Brain Tumor in Flair MRI Slice with Joint Thresholding and Segmentation -- 1 Introduction -- 2 Related Research -- 3 Methodology -- 3.1 BRATS2015 Database -- 3.2 Tri-Level Thresholding -- 3.3 Automatic Segmentation -- 3.4 Performance Evaluation -- 4 Result and Discussion -- 5 Conclusion -- References -- Mayfly-Algorithm Selected Features for Classification of Breast Histology Images into Benign/Malignant Class -- 1 Introduction -- 2 Related Research -- 3 Methodology -- 3.1 Image Database -- 3.2 Feature Extraction -- 3.3 Feature Selection -- 3.4 Classification and Validation
001451882 5058_ $$a4 Result and Discussion -- 5 Conclusion -- References -- Recent Trends in Human Re-identification Techniques - A Comparative Study -- 1 Introduction -- 2 Methodologies for Human Re-identification -- 2.1 Feature Representation -- 2.2 Distance Metric Learning Methodologies -- 3 Performance Analysis -- 3.1 Comparative Analysis -- 4 Conclusion -- References -- Automatic Segmentation of Handwritten Devanagari Word Documents Enabling Accurate Recognition -- 1 Introduction -- 2 Brief Overview of Devanagari Script -- 3 Proposed Method -- 3.1 Identification and Segmentation of Shiroreakha [14]
001451882 506__ $$aAccess limited to authorized users.
001451882 520__ $$aThis book constitutes revised selected papers from the refereed proceedings of the 9th International Conference on Mining Intelligence and Knowledge Exploration, MIKE 2021, which took place in Hammamet, Tunisia, in November 2021. The 22 full papers included in this book were carefully reviewed and selected from 61 submissions. They deal with topics such as evolutionary computation, knowledge exploration in IoT, artificial intelligence, machine learning, data mining and information retrieval, medical image analysis, pattern recognition and computer vision, speech / signal processing, text mining and natural language processing, intelligent security systems, Smart and Intelligent Systems, etc.
001451882 588__ $$aOnline resource; title from PDF title page (SpringerLink, viewed January 3, 2023).
001451882 650_0 $$aData mining$$vCongresses.
001451882 655_0 $$aElectronic books.
001451882 7001_ $$aChbeir, Richard.
001451882 7001_ $$aManolopoulos, Yannis,$$d1957-
001451882 7001_ $$aPrasath, Rajendra.
001451882 77608 $$iPrint version:$$aChbeir, Richard$$tMining Intelligence and Knowledge Exploration$$dCham : Springer International Publishing AG,c2023$$z9783031215162
001451882 830_0 $$aLecture notes in computer science.$$pLecture notes in artificial intelligence.
001451882 830_0 $$aLecture notes in computer science ;$$v13119.
001451882 830_0 $$aLNCS sublibrary.$$nSL 7,$$pArtificial intelligence.
001451882 852__ $$bebk
001451882 85640 $$3Springer Nature$$uhttps://univsouthin.idm.oclc.org/login?url=https://link.springer.com/10.1007/978-3-031-21517-9$$zOnline Access$$91397441.1
001451882 909CO $$ooai:library.usi.edu:1451882$$pGLOBAL_SET
001451882 980__ $$aBIB
001451882 980__ $$aEBOOK
001451882 982__ $$aEbook
001451882 983__ $$aOnline
001451882 994__ $$a92$$bISE