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Studying fish recognition has important realistic and theoretical significance to aquaculture and marine biology. Fish recognition is challenging problem because of distortion, overlap and occlusion of digital images. Previous researchers have done a lot of work on fish recognition, but the classification accuracy may be not high enough. Classification and recognition methods based on convolutional...
Side scan sonar (SSS) is a vital sensor for autonomous underwater vehicles (AUVs) to do ocean survey. Many methods have been proposed to carry out SSS image segmentation, among which machine learning algorithms provide outstanding performance. Machine learning algorithms like support vector machine (SVM) and convolutional neural networks (CNN) are the most used. When SVM is used to do pixel-level...
Nowadays, ocean observatory networks, which gather and provide multidisciplinary, long-term, 3D continuous marine observations at multiple temporal spatial scales, play a more and more important role in ocean investigations. In this paper, we try to develop a portable smart device with online fish detection and tracking strategies by ARM7 microprocessor for ocean observatory networks, combining the...
Autonomous underwater vehicles (AUVs) are becoming increasingly popular for ocean exploration, military and industrial applications. Motion control of AUV is the key to completing these missions. The classical linear Proportional Integral Derivative (PID) controllers are widely used due to its reliability and simplicity. However, it is difficult to tune the parameters in the classical PID controllers...
Underwater obstacle detection is essential for safe deployment of autonomous underwater vehicles (AUVs). In this paper, we make an attempt to explore one kind of underwater obstacle detection strategy with the help of the Relative Total Variation(RTV) and Joint Guided Filtering(JGF). We first introduce one kind of virtual retinex model. Then we utilize the Relative Total Variation to extract the essential...
Traditional mining algorithms did not suit mining of global maximal frequent itemsets. Therefore, a new mining algorithm of global maximal frequent itemsets for health big data, namely, NMAGMFI algorithm was proposed. Firstly, the global frequent items were mined. Secondly, local FP-tree was reconstructed by each node. Thirdly, the mining results were combined by the center node. Finally, the global...
The date mining based on big data was a very important field. In order to improve the mining efficiency, the mining algorithm of frequent itemsets based on mapreduce and FP-tree was proposed, namely, MAFIM algorithm. Firstly, the data were distributed by mapreduce. Secondly, local frequent itemsets were computed by FP-tree. Thirdly, the mining results were combined by the center node. Finally, global...
Ultrafast fiber lasers have been recognized as the efficient ultrashort pulse sources, which can be applied to various practical fields, such as material processing, fiber sensing, optical communication and medicine. To generate ultrashort pulse, the most efficient approach is the use of passive mode-locking techniques. So far, the passively mode-locked pulse duration ranging from femtosecond to picosecond...
As an underwater detection sensor, side-scan sonar plays an important role in marine survey, mineral exploration, underwater archaeology and so on. During the use of side-scan sonar, classifiication and mosaicking of collected images is essential in most cases. There are two main contributions in our work. On the one hand, we propose a supervised learning method based on kernel-based extreme learning...
Underwater object tracking is one of the most essential and fundamental tasks in ocean investigations recent years. In this paper, we try to capture multi-scale retinex (MSR) model as well as the partial least square (PLS) analysis for underwater object tracking. We first make use of multi-scale retinex model to evolve and enhance the partial color constancy from the underwater video sequences, which...
Underwater target detecting is an important technique for the development of the ocean engineering and exploration also a significant task of the ocean detecting. It plays a substantial role not only for the civil economy but also for the national security. The formation of the super-resolution underwater image is significant topic in ocean detecting field. In order to enhance the visual quality of...
Image segmentation of underwater environment with inhomogeneous intensity turns out to be one of the most challenging topics these years. In this paper, we try to combine co-saliency detection with local statistical active contour model together for underwater image segmentation. The cluster-based algorithm is first taken for co-saliency detection, which makes salient region in the underwater images...
The challenge in the Autonomous Underwater Vehicle (AUV) navigation technology is how to ensure precise localization accurately. Extended Kalman filter (EKF) is the most widely used navigation method. Despite its long successful application, EKF has a number of problems in application, for instance, the system motion model usually not appropriate to be described as a linear system. This paper proposed...
Underwater visual understanding tends to be one of the most important challenges in ocean investigations recent years. In this paper, we make an attempt to develop a depth estimation approach from one single underwater image with non-uniform illumination correction. First, we try to remove the relatively strong reflection layer from the scene layer in those underwater images with non-uniform illumination...
Side-scan sonar image segmentation is an important part in marine surveys, especially when we need to get the topographic features of the seabed. Actually, due to the complexity of the geomorphological characteristics in the seabed, we can't obtain any prior knowledge. Therefore we need an unsupervised system to segment side-scan sonar images automatically. In this paper, a novel segmentation system...
A new HPC technology was developed in terms of the domain decomposition along time-axis, namely time decomposition method (TDM), to solve all time steps (or a subdivision of all time steps) simultaneously to achieve better scalability, instead of solving a transient problem sequentially one time-step by one time-step. For practical applications, we further introduced two TDM models: one is the Periodic...
The high performance AC servo system is required to achieve fast response without overshoot. The traditional proportional-integral(PI) controller which utilizes fixed parameters, however, cannot well guarantee the requirement for both response and overshoot at the same time. Thus a variable structure PI(VSPI) controller is proposed in this paper, and the stability conditions of the closed-loop system...
This paper puts forwards a series of indexes to represent utilization rate and risk level of power system as well as to discuss their interrelationship. In particular, probabilistic risk assessment method is adopted in this paper to calculate security coefficient of over-limit voltage. Data envelopment analysis (DEA) is used innovatively to probe into the best balance point of system. By respectively...
With the expansion of electric vehicles, the planning problems of charging facilities is becoming more and more critical. An efficient density and distribution planning program of charging facilities can promote the promotion of electric vehicles. In this paper, we build the Estimating the Balance Density of Electric Vehicles Charging Points (EBQEC) model, which can be applied to estimate the reasonable...
Heading control is an important part of Autonomous Underwater Vehicle (AUV) control. But it's control performance is restricted to the uncertainty environments, and lack of understanding of dynamic characteristics of AUV. As a model-free method, the Q-learning achieves its control motivation by interacting with the environment and maximizing a reward, so suits the complicated applications in heading...
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