{"id":54747,"date":"2023-08-26T05:29:49","date_gmt":"2023-08-26T05:29:49","guid":{"rendered":"https:\/\/www.inspirenignite.com\/anna-university\/gi3019-pattern-recognition-satellite-aerial-uav-syllabus-for-geo-2021-regulation-professional-elective-iii\/"},"modified":"2023-08-26T05:29:49","modified_gmt":"2023-08-26T05:29:49","slug":"gi3019-pattern-recognition-satellite-aerial-uav-syllabus-for-geo-2021-regulation-professional-elective-iii","status":"publish","type":"post","link":"https:\/\/www.inspirenignite.com\/anna-university\/gi3019-pattern-recognition-satellite-aerial-uav-syllabus-for-geo-2021-regulation-professional-elective-iii\/","title":{"rendered":"GI3019: Pattern Recognition (Satellite, Aerial, UAV) syllabus for Geo 2021 regulation (Professional Elective-III)"},"content":{"rendered":"

Pattern Recognition (Satellite, Aerial, UAV) detailed syllabus for Geoinformatics Engineering (Geo) for 2021 regulation curriculum has been taken from the Anna Universities<\/a> official website and presented for the Geo students. For course code, course name, number of credits for a course and other scheme related information, do visit full semester subjects post given below. <\/p>\n

For Geoinformatics Engineering 5th Sem scheme and its subjects, do visit Geo 5th Sem 2021 regulation scheme<\/a>. For Professional Elective-III scheme and its subjects refer to Geo Professional Elective-III syllabus scheme<\/a>. The detailed syllabus of pattern recognition (satellite, aerial, uav) is as follows. <\/p>\n

Course Objectives:<\/h4>\n

Download the iStudy App for all syllabus and other updates.<\/a>
\"Get<\/a><\/h4>\n

Unit I<\/h4>\n

PATTERN CLASSIFIER\tOverview of Pattern Recognition, Types of Pattern recognition – Discriminant Functions -Supervised Learning – Parametric Estimation – Maximum Likelihood Estimation – Bayes Theorem – Bayesian Belief Network, Naive Bayesian Classifier, non-parametric density estimation, histograms, kernels, window estimators.\n<\/p>\n

Unit II<\/h4>\n

CLUSTERING\tUnsupervised learning – Clustering Concept – Hierarchical Clustering Procedures – Partitional Clustering – Clustering of Large Data Sets – EM Algorithm – Grid Based Clustering – Density Based Clustering.\n<\/p>\n

Unit III<\/h4>\n

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\"Get<\/a><\/h4>\n

Unit IV<\/h4>\n

HIDDEN MARKOV MODELS AND SUPPORT VECTOR MACHINES\tState Machines – Hidden Markov Models: Maximum Likelihood for the HMM, The Forward and Backward Algorithm, Sum-Product Algorithm for the HMM, Scaling Factors, The Viterbi Algorithm, Extensions Of The Hidden Markov Model – Support Vector Machines: Maximum Margin Classifiers, Relevance Vector Machines.\n<\/p>\n

Unit V<\/h4>\n

RECENT ADVANCES\tFuzzy Classification: Fuzzy Set Theory, Fuzzy And Crisp Classification, Fuzzy Clustering, Fuzzy Pattern Recognition – Introduction to Neural Networks: Elementary Neural Network For Pattern Recognition, Hebbnet, Perceptron, ADALINE, Back Propagation.\n<\/p>\n

Course Outcomes:<\/h4>\n

\u2022On completion of the course, the student is expected to<\/p>\n

    \n
  1. Provide basic knowledge about the fundamentals of pattern recognition and its applications.<\/li>\n
  2. Understand about unsupervised algorithms suitable for pattern classification.<\/li>\n
  3. Familiarize with the feature selection algorithms and methods of implementing them in applications.<\/li>\n
  4. Learn about the basis of algorithms used for training and testing the dataset.<\/li>\n
  5. Learn basic fuzzy system and neural network architectures, for applications in pattern recognition, image processing, and computer vision.<\/li>\n<\/ol>\n

    Text Books:<\/h4>\n

    Download the iStudy App for all syllabus and other updates.<\/a>
    \"Get<\/a><\/h4>\n

    Reference Books:<\/h4>\n
      \n
    1. C. M. Bishop, \u201cPattern Recognition and Machine Learning\u201d, Springer, Second Edition, 2011.<\/li>\n
    2. R. O. Duda, P. E. Hart, D. G. Stork, \u201cPattern Classification\u201d, John Wiley, 2001.<\/li>\n
    3. Narasimha Murthy, V. Susheela Devi, \u201cPattern Recognition\u201d, Springer 2011.<\/li>\n
    4. Menahem Friedman, Abraham Kandel, \u201cIntroduction to Pattern Recognition Statistical,<\/li>\n

      Structural, Neural and Fuzzy Logic Approaches\u201d, World Scientific publishing Co. Ltd, 2020.<\/p>\n

    5. Robert J. Schalkoff, \u201cPattern Recognition Statistical, Structural and Neural Approaches\u201d, John Wiley & Sons Inc., 1992.<\/li>\n
    6. S. Theodoridis, K. Koutroumbas, \u201cPattern Recognition\u201d, Fourth Edition, Academic Press, 2009.<\/li>\n<\/li>\n<\/ol>\n

      For detailed syllabus of all the other subjects of Geoinformatics Engineering 5th Sem, visit Geo 5th Sem subject syllabuses for 2021 regulation<\/a>. <\/p>\n

      For all Geoinformatics Engineering results, visit Anna University Geo all semester results<\/a> direct link. <\/p>\n","protected":false},"excerpt":{"rendered":"

      Pattern Recognition (Satellite, Aerial, UAV) detailed syllabus for Geoinformatics Engineering (Geo) for 2021 regulation curriculum has been taken from the Anna Universities official website and presented for the Geo students. […]<\/p>\n","protected":false},"author":2297,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_bbp_topic_count":0,"_bbp_reply_count":0,"_bbp_total_topic_count":0,"_bbp_total_reply_count":0,"_bbp_voice_count":0,"_bbp_anonymous_reply_count":0,"_bbp_topic_count_hidden":0,"_bbp_reply_count_hidden":0,"_bbp_forum_subforum_count":0,"footnotes":""},"categories":[80],"tags":[],"class_list":["post-54747","post","type-post","status-publish","format-standard","hentry","category-geo"],"_links":{"self":[{"href":"https:\/\/www.inspirenignite.com\/anna-university\/wp-json\/wp\/v2\/posts\/54747","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.inspirenignite.com\/anna-university\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.inspirenignite.com\/anna-university\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.inspirenignite.com\/anna-university\/wp-json\/wp\/v2\/users\/2297"}],"replies":[{"embeddable":true,"href":"https:\/\/www.inspirenignite.com\/anna-university\/wp-json\/wp\/v2\/comments?post=54747"}],"version-history":[{"count":0,"href":"https:\/\/www.inspirenignite.com\/anna-university\/wp-json\/wp\/v2\/posts\/54747\/revisions"}],"wp:attachment":[{"href":"https:\/\/www.inspirenignite.com\/anna-university\/wp-json\/wp\/v2\/media?parent=54747"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.inspirenignite.com\/anna-university\/wp-json\/wp\/v2\/categories?post=54747"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.inspirenignite.com\/anna-university\/wp-json\/wp\/v2\/tags?post=54747"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}