A real-time method that automatically creates a visual memory of a scene using the growing neural gas (GNG) algorithm is described. The memory consists of a graph where nodes encode the visual information of a video stream as a limited set of representative images. GNG nodes are automatically generated and dynamically clustered. This method could be employed by robotic platforms in exploratory and rescue missions. © 2012 The Institution of Engineering and Technology
International audienceThis paper addresses the task of segmenting moving objects in unconstrained vi...
Upsupervised, data driven, automatic feature extraction from image data is an interesting and diffic...
This paper aims to address the ability of self-organizing neural network models to manage real-time ...
A real-time method that automatically creates a visual memory of a scene using the growing neural ga...
This paper aims to address the ability of self-organizing neural network models to manage video and ...
Self-organising neural networks have shown promise in a variety of applications areas. Their massive...
Self-organising neural networks have shown promise in a variety of applications areas. Their massive...
Kortkamp M, Wachsmuth S. Continuous Visual Codebooks with a Limited Branching Tree Growing Neural Ga...
International audienceIn this paper, an original method extended from growing neural gas (GNG-T) [B....
Beyer O, Cimiano P. DYNG: Dynamic Online Growing Neural Gas for Stream Data. In: European Symposium...
This paper proposes a real-time topological structure learning method based on concentrated/distribu...
Current RGB-D sensors provide a big amount of valuable information for mobile robotics tasks like 3D...
The object recognition task on 3D scenes is a growing research field that faces some problems relati...
Key words: Brain, development, neural networks, vision, cluttered background It is mysterious how th...
Abstract in Undetermined Several recent works deal with 3D data in mobile robotic problems, e.g. map...
International audienceThis paper addresses the task of segmenting moving objects in unconstrained vi...
Upsupervised, data driven, automatic feature extraction from image data is an interesting and diffic...
This paper aims to address the ability of self-organizing neural network models to manage real-time ...
A real-time method that automatically creates a visual memory of a scene using the growing neural ga...
This paper aims to address the ability of self-organizing neural network models to manage video and ...
Self-organising neural networks have shown promise in a variety of applications areas. Their massive...
Self-organising neural networks have shown promise in a variety of applications areas. Their massive...
Kortkamp M, Wachsmuth S. Continuous Visual Codebooks with a Limited Branching Tree Growing Neural Ga...
International audienceIn this paper, an original method extended from growing neural gas (GNG-T) [B....
Beyer O, Cimiano P. DYNG: Dynamic Online Growing Neural Gas for Stream Data. In: European Symposium...
This paper proposes a real-time topological structure learning method based on concentrated/distribu...
Current RGB-D sensors provide a big amount of valuable information for mobile robotics tasks like 3D...
The object recognition task on 3D scenes is a growing research field that faces some problems relati...
Key words: Brain, development, neural networks, vision, cluttered background It is mysterious how th...
Abstract in Undetermined Several recent works deal with 3D data in mobile robotic problems, e.g. map...
International audienceThis paper addresses the task of segmenting moving objects in unconstrained vi...
Upsupervised, data driven, automatic feature extraction from image data is an interesting and diffic...
This paper aims to address the ability of self-organizing neural network models to manage real-time ...