ISBN:
9789811636905
Language:
English
Pages:
1 Online-Ressource(XX, 1671 p. 986 illus., 741 illus. in color.)
Edition:
1st ed. 2022.
Series Statement:
Lecture Notes in Electrical Engineering 783
Parallel Title:
Erscheint auch als
Parallel Title:
Erscheint auch als
Parallel Title:
Erscheint auch als
Keywords:
Computational intelligence.
;
Information technology.
;
Business—Data processing.
;
Artificial intelligence.
;
Neural networks (Computer science).
;
Computer engineering.
;
Internet of things.
;
Embedded computer systems.
;
Computer software.
Abstract:
Automatic Notes Generation From Lecture Videos -- Correlation between Code Smells for Open Source Java Projects -- Throughput Improvement in Energy Efficient Heterogeneous Wireless Sensor Network -- Deep Learning Models for Rubik’s cube with Entropy Modelling -- Detecting Diabetic Retinopathy Using Deep Learning Technique with RESNET-50 -- Restoration of Rician Corrupted MR Data using Improved Hybrid Model -- Flight Delay Prediction using Random Forest Classifier -- A framework using Markov-Baye’s model for Intrusion Detection in Wireless Sensor Network -- Effective text comment classification using Novel ML algorithm - Modified Lazy Random Forest -- Unraveling Deep Learning Performance in Cross-Sensor Iris Recognition -- Travelling Salesman Problem Using GA-ACO Hybrid Approach: A Review -- Efficient and Robust Indian Number Plate Recognition through Modified and Tuned LPRNet -- An Improved Machine Learning Prediction Model for Diabetes.
Abstract:
This book gathers selected high-impact articles from the 2nd International Conference on Data Science, Machine Learning & Applications 2020. It highlights the latest developments in the areas of artificial intelligence, machine learning, soft computing, human–computer interaction and various data science and machine learning applications. It brings together scientists and researchers from different universities and industries around the world to showcase a broad range of perspectives, practices and technical expertise.
DOI:
10.1007/978-981-16-3690-5
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