Superresolution for ultrasonic imaging in air using neural networks

Winters,

doi:10.1109/icnn.1988.23897

Cited by 8 publications

(1 citation statement)

References 4 publications

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“…i: Transfer function of amplifier Hopfield chose the function s to be a sigmoidal function. A simplified form of the transfer function shown inFigure 4.7 was suggested[30] as follows:…”

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confidence: 99%

Neural network approach for solving inverse problems

Elshafiey

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“…i: Transfer function of amplifier Hopfield chose the function s to be a sigmoidal function. A simplified form of the transfer function shown inFigure 4.7 was suggested[30] as follows:…”

mentioning

confidence: 99%

Neural network approach for solving inverse problems

Elshafiey

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Position and posture measurements and shape recognition of columnar objects using an ultrasonic sensor array and neural networks

Ohtani

Baba

Konishi

2002

Systems & Computers in Japan

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SUMMARYA new method for measuring the position and posture (pose) and recognizing the shape using ultrasonic wave sound pressure signals and neural networks is proposed. In most of the past methods of this kind, the characteristic quantities have been based on either time of flight methods or acoustic holographic methods. In these methods, measuring and recognizing the width and depth directions simultaneously with a high resolution has been difficult in principle. In this paper, the problems of the past methods are resolved by changing the viewpoints by using criteria such as the peak values of the penetrating and reflecting waveforms, their positions, their deflection points, and their intervals when ultrasonic waves are directed onto a measured object, as characteristic quantities given to neural networks. In addition, a prototype measuring and recognizing system implementing the proposed scheme is constructed by introducing a circuit for detecting the peak positions of the sound pressure signal distribution waveforms with high resolution. The experimental results are satisfactory in position measurements and shape recognition, and confirm that the method is applicable to rectangular prisms and the like. It is shown that the position and pose measurements and shape recognition can be realized with high resolution in both the width and depth directions by this scheme, and that the proposed method is very effective when applied to position and pose measurements and shape recognition and the like ultrasonically.

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Ultrasonic robot eyes using neural networks

Watanabe

Yoneyama

1990

IEEE Trans. Ultrason., Ferroelect., Freq. Contr.

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In order to construct a robot eye using ultrasonic waves in air, a system that combines existing acoustical holography with neural networks is devised. In this system, neural networks are used to reduce the vagueness of reconstruction from the acoustical holography. The system is able to identify objects and to reconstruct the acoustical images of objects using an array of only a small number of receivers. Some experimental results on identification and reconstruction using several kinds of metal plate objects are reported.

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Superresolution for ultrasonic imaging in air using neural networks

Cited by 8 publications

References 4 publications

Neural network approach for solving inverse problems

Neural network approach for solving inverse problems

Position and posture measurements and shape recognition of columnar objects using an ultrasonic sensor array and neural networks

Ultrasonic robot eyes using neural networks

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