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BuchGebunden
126 Seiten
Englisch
Springererschienen am21.11.20201st ed. 2021
The book introduces some challenging methods and solutions to solve the human activity recognition challenge. This book highlights the challenge that will lead the researchers in academia and industry to move further related to human activity recognition and behavior analysis, concentrating on cooking challenge.mehr
Verfügbare Formate
BuchGebunden
EUR181,89
BuchKartoniert, Paperback
EUR181,89
E-BookPDF1 - PDF WatermarkE-Book
EUR171,19

Produkt

KlappentextThe book introduces some challenging methods and solutions to solve the human activity recognition challenge. This book highlights the challenge that will lead the researchers in academia and industry to move further related to human activity recognition and behavior analysis, concentrating on cooking challenge.
Zusammenfassung
Introduces some challenging methods and solutions to solve the human activity recognition challenge

Presents 10 chapters from 13 institutes and 8 countries

Serves as a reference resource for researchers and academicians
Details
ISBN/GTIN978-981-15-8268-4
ProduktartBuch
EinbandartGebunden
Verlag
Erscheinungsjahr2020
Erscheinungsdatum21.11.2020
Auflage1st ed. 2021
ReiheSmart Innovation, Systems and Technologies
Seiten126 Seiten
SpracheEnglisch
Gewicht339 g
IllustrationenXIV, 126 p. 43 illus., 31 illus. in color.
Artikel-Nr.16257145

Inhalt/Kritik

Inhaltsverzeichnis
Chapter 1. Summary of the Cooking Activity Recognition Challenge.- Chapter 2. Activity Recognition from Skeleton and Acceleration Data Using CNN and GCN.- Chapter 3. Let´s not make it complicated - Using only LightGBM and Naive Bayes for macro and micro activity recognition from a small dataset.- Chapter 4. Deep Convolutional Bidirectional LSTM for Complex Activity Recognition with Missing Data.- Chapter 5. SCAR-Net: Scalable ConvNet for Activity Recognition with multi-modal Sensor Data.- Chapter 6. Multi-Sampling Classifiers for the Cooking Activity Recognition Challenge.- Chapter 7. Multi-class Multi-label Classification for Cooking Activity Recognition.- Chapter 8. Cooking Activity Recognition with Convolutional LSTM using Multi-label Loss Function and Majority Vote.- Chapter 9. Identification of Cooking Preparation Using Motion Capture Data: A Submission to the Cooking Activity Recognition Challenge.- Chapter 10. Cooking Activity Recognition with Varying Sampling Rates using Deep Convolutional GRU Framework.mehr

Autor

Md Atiqur Rahman Ahad, SMIEEE, is Professor, University of Dhaka (DU), and Specially Appointed Associate Professor, Osaka University. He did B.Sc. (Honors) & Masters (DU), Masters (University of New South Wales), and Ph.D. (Kyushu Institute of Technology) and is JSPS Postdoctoral Fellow and Visiting Researcher. His authored books are "Motion History Images for Action Recognition and Understanding," in Springer; "Computer Vision and Action Recognition," in Springer; "IoT-sensor based Activity Recognition," in Springer (in press). He has been authoring/editing a few more books. He published 130+ peer-reviewed papers, 60+ keynote/invited talks, 25+ Awards/Recognitions. He is Editorial Board Member of Scientific Reports, Nature; Associate Editor of Frontiers in Computer Science; Editor of the International Journal of Affective Engineering; Editor-in-Chief: International Journal of Computer Vision & Signal Processing; General Chair: 9th ICIEV; 4th IVPR; 2nd ABC; Guest-Editor: Pattern Recognition Letters, Elsevier; JMUI, Springer; JHE, Hindawi; IJICIC; Member: OSA, ACM, IAPR.
Paula Lago has a Ph.D. from Universidad de los Andes, Colombia. She received her Bachelor's and Master's degree in Software Engineering from the same university. From 2018 to 2020, she was a Postdoctoral Researcher at Kyushu Institute of Technology, Japan. Her current research is on how to improve the generalization of activity recognition in real-life settings taking advantage of data collected in controlled settings. In 2016, she was an invited researcher in the Informatics Laboratory of Grenoble, where she participated in smart home research in collaboration with INRIA. She has served as Reviewer for MDPI Sensors and ACM IMWUT journal and for several conferences. She is a Co-Organizer of the HASCA Workshop, held at Ubicomp yearly. She currently volunteers for ACM SIGCHI.
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