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    Advances in Data Science and Artificial Intelligence: ICDSAI 2022, IIT Patna, India, April 23 ? 24

    Advances in Data Science and Artificial Intelligence by Misra, Rajiv; Kesswani, Nishtha; Rajarajan, Muttukrishnan;

    ICDSAI 2022, IIT Patna, India, April 23 ? 24

    Sorozatcím: Springer Proceedings in Mathematics & Statistics; 403;

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    A termék adatai:

    • Kiadás sorszáma 2023
    • Kiadó Springer
    • Megjelenés dátuma 2023. május 14.
    • Kötetek száma 1 pieces, Book

    • ISBN 9783031161773
    • Kötéstípus Keménykötés
    • Terjedelem524 oldal
    • Méret 235x155 mm
    • Súly 969 g
    • Nyelv angol
    • Illusztrációk 1 Illustrations, black & white
    • 503

    Kategóriák

    Rövid leírás:

    With the intriguing development of technologies in several industries along with the advent of accrescent and ubiquitous computational resources, it creates an ample number of opportunities to develop innovative intelligence technologies in order to solve the wide range of uncertainties, imprecision, and vagueness issues in various real-life problems. Hybridizing modern computational intelligence with traditional computing methods has attracted researchers and academicians to focus on developing innovative AI techniques using data science. International Conference on Data Science and Artificial Intelligence (ICDSAI) 2022, organized on April 23-24, 2022 by the Indian Institute of Technology, Patna at NITIE Mumbai (India) in collaboration with the International Association of Academicians (IAASSE) USA collected scientific and technical contributions with respect to models, tools, technologies, and applications in the field of modern Artificial Intelligence and Data Science, coveringthe entire range of concepts from theory to practice, including case studies, works-in-progress, and conceptual explorations.

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    Hosszú leírás:

    With the intriguing development of technologies in several industries along with the advent of accrescent and ubiquitous computational resources, it creates an ample number of opportunities to develop innovative intelligence technologies in order to solve the wide range of uncertainties, imprecision, and vagueness issues in various real-life problems. Hybridizing modern computational intelligence with traditional computing methods has attracted researchers and academicians to focus on developing innovative AI techniques using data science. International Conference on Data Science and Artificial Intelligence (ICDSAI) 2022, organized on April 23-24, 2022 by the Indian Institute of Technology, Patna at NITIE Mumbai (India) in collaboration with the International Association of Academicians (IAASSE) USA collected scientific and technical contributions with respect to models, tools, technologies, and applications in the field of modern Artificial Intelligence and Data Science, coveringthe entire range of concepts from theory to practice, including case studies, works-in-progress, and conceptual explorations.

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    Tartalomjegyzék:

    Sky Detection in Outdoor Spaces (S. Rajguru).- Defining, Measuring and Utilizing Student?s Learning in a course (T. Garg).- Holistic Features and Deep Guided Depth Induced Mutual Attention based Complex Salient Object Detection (R. Singh).- Machine Learning based Decision Support System for Resilient Supplier Selection (A. Dixit).- An Adaptive Task Offloading Framework for Mobile Edge Computing Environment: Towards Achieving Seamless Energy-Efficient Processing (M. Rasool).- Road Surface Classification and Obstacle Detection for Visually Impaired People (S. Shilaskar).- A Survey on Semantic Segmentation Models for Underwater Images (S. K. Anand).- An Interactive dashboard for Intrusion Detection in Internet of Things (M. Vishwakarma).- An Analous Review of the Challenges and Endeavor in Suspense Story Generation Technique (V. Kowsalya).- Friend recommendation using transfer learning in the autoencoder (A. Karande).- Analysis on the Efficacy of ANN on Small Imbalanced Datasets(B. Shah).- Lightweight and Homomorphic Security Protocols for IoT (I. Singh).- Tool based approach on Digital Vulnerability Management Hub using The-Hive Platform (S. R. Babu).- Performance Analyzer for Blue Chip Companies (I. Badole).- Strengthening Deep Learning Based Malware Detection Models Against Adversarial Attacks (R. Pai).- Video-based Micro  Expressions Recognition using Deep Learning and Transfer Learning (S. Kapadia).- Trustworthiness of COVID-19 News and Guidelines (S. Singh).- Detection of moving object using modified fuzzy C- means clustering from the complex and Non-Stationary background scenes (R. Sangle) .- Deterrence Pointer for Distributed Denial of Service (DDoS) attacks by utilizing Watchdog Timer and Hybrid Routing Protocol (S. J. Kumar).- Modelling Logistic Regression and Neural Network for Stock Selection With BSE 500 - A Comparative Study (S. Simon).- Landslide Detection with Ensemble-of-Deep Learning-Classifiers trained with Optimal Features(A. Kumar).- A Survey Paper on Text Analytics Methods for Classifying Tweets (C. Agrawal).- A Survey on Threat Intelligence Techniques for Constructing, Detecting, and Reacting to Advanced Intrusion Campaigns (A. Anand).- Generalizing a secure framework for Domain Transfer Network for Face antispoofing (A. Rana).- Survey on Game Theory Based Security Framework for IoT (P. Joshi).- Intrusion Detection for IoT (S. L. Poojitha).- Human-in-the-loop control and security for intelligent Cyber-Physical Systems (CPS) and IoT (S. Sundarrajan).- Survey: Neural Network authentication and tampering detection (P. Ashwin).- Misinformation Detection through Authentication of Content Creators (K. K. Sudhama).- End-to-end network slicing for 5G and beyond communications (R. K. Gupta).- Transparency in Content and Source Moderation (A. R. Chandrassery).- A New Chaotic-Based Analysis of Data Encryption and Decryption (Md M. Rahman).- Trust and Identity Management in IOT (A. Tony).- Plant Pests Detection a Deep Learning Approach (N. More).- S.A.R.A (Smart AI Refrigerator Assistant) (S. Kirkire).- A Location Based Cryptographic Suite For Underwater Acoustic Networks(V. S. Katasani).

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