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In this paper, a new scene recognition system IMSI is proposed, which based on partially connected neural evolutionary model and codal module. This module innovatively applies a new unit called codal module to connect several partially connected neural networks together. IMSI is effective for the multi-class scene recognition without feature extraction and solves the neural network oversizing problem...
The vehicle license plate detection is challenging first step in license plate recognition system. The license plate region is in the characteristics of gradient and frequent changes. This paper proposes High-pass filter to extract the gradient and frequent changes regions. Then merge adjacent regions as license plate candidates. Combined with the geometric features of license plates and the ratio...
A novel locating vehicle license plate (VLP) method is proposed in this paper. Firstly, preprocessing is used on the license image. Then a series of morphological operations are used to extract important contrast features to find out all license plates candidates. As a result of the noise, more than one candidate will be extracted after the morphological operations, so the auto -correlation based...
Vehicle license plate location is an important part of a license plate recognition system. This paper proposed a new location method for plate under complex scenes based on horizontal gradient and morphological operation. Firstly, horizontal gradient image was obtained by horizontal difference on the grayscale image. Secondly, an adaptive threshold proposed in this paper was used to segment the gradient...
To explore the method for the building of artificial brain, by combing neural network and genetic algorithm, Parcone model (partially connected neural evolutionary model) was proposed and represented, especially for its partially connected structure and evolution algorithm. Comparing with fully connected model, Parcone model can substantially decrease computing amount, while remain strong classification...
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