A Real-Time Bike Trip Planning Policy With Self-Organizing Bike Redistribution

2021 ◽  
pp. 1-16
Author(s):  
Junheng Wang ◽  
Fan Li ◽  
Song Yang ◽  
Youqi Li ◽  
Yu Wang
Keyword(s):  
Real Time ◽  
Trip Planning ◽  
Planning Policy ◽  
Self Organizing

scholarly journals Dynamic Gesture Recognition System with Gesture Spotting Based on Self-Organizing Maps

2021 ◽  
Vol 11 (4) ◽  
pp. 1933
Author(s):  
Hiroomi Hikawa ◽  
Yuta Ichikawa ◽  
Hidetaka Ito ◽  
Yutaka Maeda
Keyword(s):  
Real Time ◽  
Gesture Recognition ◽  
Weight Vector ◽  
Recognition System ◽  
Self Organizing Map ◽  
Self Organizing Maps ◽  
Time Dynamic ◽  
System Input ◽  
Self Organizing ◽  
Gesture Spotting

In this paper, a real-time dynamic hand gesture recognition system with gesture spotting function is proposed. In the proposed system, input video frames are converted to feature vectors, and they are used to form a posture sequence vector that represents the input gesture. Then, gesture identification and gesture spotting are carried out in the self-organizing map (SOM)-Hebb classifier. The gesture spotting function detects the end of the gesture by using the vector distance between the posture sequence vector and the winner neuron’s weight vector. The proposed gesture recognition method was tested by simulation and real-time gesture recognition experiment. Results revealed that the system could recognize nine types of gesture with an accuracy of 96.6%, and it successfully outputted the recognition result at the end of gesture using the spotting result.

Computer Vision Applications of Self-Organizing Neural Networks

2013 ◽  
pp. 129-138
Author(s):  
José García-Rodríguez ◽  
Juan Manuel García-Chamizo ◽  
Sergio Orts-Escolano ◽  
Vicente Morell-Gimenez ◽  
José Antonio Serra-Pérez ◽  
...  
Keyword(s):  
Real Time ◽  
Network Models ◽  
Suitable Model ◽  
Surveillance Systems ◽  
Neural Network Models ◽  
Neural Gas ◽  
3D Data ◽  
Computer Vision Applications ◽  
Recognition Systems ◽  
Self Organizing

This chapter aims to address the ability of self-organizing neural network models to manage video and image processing in real-time. The Growing Neural Gas networks (GNG) with its attributes of growth, flexibility, rapid adaptation, and excellent quality representation of the input space makes it a suitable model for real time applications. A number of applications are presented, including: image compression, hand and medical image contours representation, surveillance systems, hand gesture recognition systems, and 3D data reconstruction.

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