This paper describes the novel use of agent and cellular neural Hopfield network techniques in the design of a self-contained, object detecting retina. The agents, which are used to detect features within an image, are trained using the Hebbian method which has been modified for the cellular architecture. The success of each agent is communicated with adjacent agents in order to verify the detection of an object. Initial work used the method to process bipolar images. This has now been extended to handle grey scale images. Simulations have demonstrated the success of the method and further work is planned in which the device is to be implemented in hardware
Blind or visually impaired people are usually unaware of the danger that they are facing in their da...
For decades, numerous scientists have examined the following questions: “How do humans see the worl...
International audienceDevelopments in neurophysiology focusing on foveal vision have characterized m...
Abstract- In this paper, a bioinspired neural model for detecting object motion based on retina comp...
This paper describes our recent efforts to develop biologically-inspired spiking neural network soft...
Machine vision is an active branch of Artificial Intelligence. An important problem in this area is ...
Abstract—For decades, numerous scientists have examined the following questions: “How do humans see ...
This paper investigates the use of a hybrid neurocomputing approach to detect and then recognise ima...
A neural behavior initiating agent (BIA) is proposed to integrate relevant compressed image informat...
We have developed a system for detecting and tracking human face and eye in an unstructured environm...
The model of a recently identified mammalian retina circuit, responsible for identifying looming or ...
This thesis deals with biologically-inspired interactive neural networks for the task of object reco...
AbstractIn this paper the design of recognition system for retinal images using neural network is co...
The retina is one of the most developed sensing organs in the hu- man body. However, the knowledge o...
International audienceIn this paper, we propose a spiking neural network model for edge detection in...
Blind or visually impaired people are usually unaware of the danger that they are facing in their da...
For decades, numerous scientists have examined the following questions: “How do humans see the worl...
International audienceDevelopments in neurophysiology focusing on foveal vision have characterized m...
Abstract- In this paper, a bioinspired neural model for detecting object motion based on retina comp...
This paper describes our recent efforts to develop biologically-inspired spiking neural network soft...
Machine vision is an active branch of Artificial Intelligence. An important problem in this area is ...
Abstract—For decades, numerous scientists have examined the following questions: “How do humans see ...
This paper investigates the use of a hybrid neurocomputing approach to detect and then recognise ima...
A neural behavior initiating agent (BIA) is proposed to integrate relevant compressed image informat...
We have developed a system for detecting and tracking human face and eye in an unstructured environm...
The model of a recently identified mammalian retina circuit, responsible for identifying looming or ...
This thesis deals with biologically-inspired interactive neural networks for the task of object reco...
AbstractIn this paper the design of recognition system for retinal images using neural network is co...
The retina is one of the most developed sensing organs in the hu- man body. However, the knowledge o...
International audienceIn this paper, we propose a spiking neural network model for edge detection in...
Blind or visually impaired people are usually unaware of the danger that they are facing in their da...
For decades, numerous scientists have examined the following questions: “How do humans see the worl...
International audienceDevelopments in neurophysiology focusing on foveal vision have characterized m...