03206oam 2200481 450 991048301320332120210505152617.0981-15-8269-610.1007/978-981-15-8269-1(CKB)4100000011586031(MiAaPQ)EBC6403762(DE-He213)978-981-15-8269-1(PPN)252504356(EXLCZ)99410000001158603120210505d2021 uy 0engurnn|008mamaatxtrdacontentcrdamediacrrdacarrierHuman activity recognition challenge /Md Atiqur Rahman Ahad, Paula Lago, Sozo Inoue, editors1st ed. 2021.Gateway East, Singapore :Springer,[2021]©20211 online resource (XIV, 126 p. 43 illus., 31 illus. in color.) Smart Innovation, Systems and Technologies,2190-3018 ;199981-15-8268-8 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. .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. Current activity recognition systems focus on recognizing either the complex label (macro-activity) or the small steps (micro-activities) but their combined recognition is critical for analysis like the challenge proposed in this book. It has 10 chapters from 13 institutes and 8 countries (Japan, USA, Switzerland, France, Slovenia, China, Bangladesh, and Columbia).Smart Innovation, Systems and Technologies,2190-3018 ;199Human activity recognitionHuman activity recognition.006.3Ahad Md. Atiqur RahmanLago PaulaInoue SozoCaPaEBRCaPaEBRUtOrBLWBOOK9910483013203321Human activity recognition challenge2854506UNINA