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This paper proposes a recognition approach for Semaphore flag signaling (SFS). We use the improved convolutional neural network (CNN) to classify the SFS. In the experiment we made Semaphore flag signaling system (SFSS), which based on CNN. The image can be directly input into the SFSS. Each alphabetic character or control signal is indicated by a particular flag pattern. We shoot the SFS videos by...
Blind deblurring attempts to recover the latent sharp image from a blurred one. Such task is a well-known ill-posed inverse problem and is therefore usually solved as a posteriori probability estimation, incorporating prior information on natural images. In this paper, we propose a general blind noisy deblurring model based on hyper Laplacian (HL) in gradient domain and kernel spectra prior. This...
Speech recognition, as the man-machine interface, plays a very important role in the field of artificial intelligence. Traditional speech recognition methods are shallow learning structure, and have their limitations. This paper uses the Convolution Neural Networks (CNNs) to realize speech recognition. It is an alternative type of neural network that can reduce spectral variation and model spectral...
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