Convolutional neural network bootstrapped by dynamic segmentation and stigmergy-based encoding for real-time human activity recognition in smart homes

HIGHLIGHTS

• who: Houda Najeh and collaborators from the Lab-STICC, IMT Atlantique, Brest, France have published the paper: Convolutional Neural Network Bootstrapped by Dynamic Segmentation and Stigmergy-Based Encoding for Real-Time Human Activity Recognition in Smart Homes, in the Journal: Sensors 2023, 23, 1969. of /2023/
• what: In this work an online human activity recognition (HAR) framework on streaming sensor is proposed. In this 8 of 18 paper, a DWN and its related matrix are investigated to represent the stigmergic trajectory. The authors rely on the method presented to determine the DWN for each segment . . .
  

   

  

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