Recent advancements in deep learning offer an effective approach for the study in machine vision using optical images. In this paper, a convolution neural network is used to deal with the target task of sonar detection, and the performance of each neural network model in the sonar image detection and recognition task of underwater box and tire is compared. The simulation results show that the neural network method proposed in this paper is better than the traditional machine learning methods and SSD network models. The average accuracy of the proposed method for sonar image target recognition is 93%, and the detection time of a single image is only 0.3 seconds
This paper presents an image matching algorithm based on convolutional neural network (CNN) to aid i...
As the in-depth exploration of oceans continues, the accurate and rapid detection of fish, bionics a...
This paper proposes a method that synthesizes realistic sonar images using a Generative Adversarial ...
Underwater target recognition is one core technology of underwater unmanned detection. To improve th...
To solve the problem of sonar image recognition, a sonar image recognition method based on fine-tune...
In underwater environment, sonar sensors have the advantage of being able to shoot images in turbid ...
This paper proposes a method to detect underwater objects using sonar image simulator and convolutio...
This paper proposes a method to detect underwater objects using sonar image simulator and convolutio...
In underwater environment, sonar sensors have the advantage of being able to shoot images in turbid ...
To improve the recognition accuracy of underwater acoustic targets by artificial neural network, thi...
Underwater object detection in sonar images requires a large number of images of target objects. For...
The speckle noise of sonar images affects the human interpretation and automatic recognition of imag...
The Side-scan sonar image automatic recognition is an important part of verification for underwater ...
Research on the automatic analysis of sonar images has focused on classical, i.e. non deep learning ...
Forward Looking Sonars (FLS) are a typical choiceof sonar for autonomous underwater vehicles. They a...
This paper presents an image matching algorithm based on convolutional neural network (CNN) to aid i...
As the in-depth exploration of oceans continues, the accurate and rapid detection of fish, bionics a...
This paper proposes a method that synthesizes realistic sonar images using a Generative Adversarial ...
Underwater target recognition is one core technology of underwater unmanned detection. To improve th...
To solve the problem of sonar image recognition, a sonar image recognition method based on fine-tune...
In underwater environment, sonar sensors have the advantage of being able to shoot images in turbid ...
This paper proposes a method to detect underwater objects using sonar image simulator and convolutio...
This paper proposes a method to detect underwater objects using sonar image simulator and convolutio...
In underwater environment, sonar sensors have the advantage of being able to shoot images in turbid ...
To improve the recognition accuracy of underwater acoustic targets by artificial neural network, thi...
Underwater object detection in sonar images requires a large number of images of target objects. For...
The speckle noise of sonar images affects the human interpretation and automatic recognition of imag...
The Side-scan sonar image automatic recognition is an important part of verification for underwater ...
Research on the automatic analysis of sonar images has focused on classical, i.e. non deep learning ...
Forward Looking Sonars (FLS) are a typical choiceof sonar for autonomous underwater vehicles. They a...
This paper presents an image matching algorithm based on convolutional neural network (CNN) to aid i...
As the in-depth exploration of oceans continues, the accurate and rapid detection of fish, bionics a...
This paper proposes a method that synthesizes realistic sonar images using a Generative Adversarial ...