scholarly journals Sea–Sky Line and its Nearby Ships Detection Based on the Motion Attitude of Visible Light Sensors

Sensors ◽  
2019 ◽  
Vol 19 (18) ◽  
pp. 4004 ◽  
Author(s):  
Shan ◽  
Zhao ◽  
Pan ◽  
Wang ◽  
Zhao
Keyword(s):  
Visible Light ◽  
Target Detection ◽  
Degrees Of Freedom ◽  
Saliency Detection ◽  
Detection Algorithm ◽  
Visual Development ◽  
Sensor Data ◽  
Camera Motion ◽  
Six Degrees Of Freedom ◽  
Ship Detection

In the maritime scene, visible light sensors installed on ships have difficulty accurately detecting the sea–sky line (SSL) and its nearby ships due to complex environments and six-degrees-of-freedom movement. Aimed at this problem, this paper combines the camera and inertial sensor data, and proposes a novel maritime target detection algorithm based on camera motion attitude. The algorithm mainly includes three steps, namely, SSL estimation, SSL detection, and target saliency detection. Firstly, we constructed the camera motion attitude model by analyzing the camera's six-degrees-of-freedom motion at sea, estimated the candidate region (CR) of the SSL, then applied the improved edge detection algorithm and the straight-line fitting algorithm to extract the optimal SSL in the CR. Finally, in the region of ship detection (ROSD), an improved visual saliency detection algorithm was applied to extract the target ships. In the experiment, we constructed SSL and its nearby ship detection dataset that matches the camera’s motion attitude data by real ship shooting, and verified the effectiveness of each model in the algorithm through comparative experiments. Experimental results show that compared with the other maritime target detection algorithm, the proposed algorithm achieves a higher detection accuracy in the detection of the SSL and its nearby ships, and provides reliable technical support for the visual development of unmanned ships.

scholarly journals А Nоvel Data-Driven Орtimаl Methоdоlоgy fоr Deteсting Shiр from Sаr Images Bаsed on Аrtifiсiаl Intelligenсe

2021 ◽  
Vol 1 (3) ◽  
pp. 17-22
Author(s):  
M.S.Antony Vigil ◽  
Rishabh Jain ◽  
Tanmay Agarwal ◽  
Abhinav Chandra
Keyword(s):  
Target Detection ◽  
Detection Rate ◽  
Target Identification ◽  
Detection Algorithm ◽  
High Accuracy ◽  
Data Driven ◽  
Identification Rate ◽  
Ship Detection ◽  
Hyper Spectral ◽  
Multiple Issues

There are a variety of deep learning algorithms available in the supervision of ships, but they are dealing with multiple issues of inaccurate identification rate and inadequate target detection speed. At this stage, an algorithm is given оn Соnvоlutiоnаl Neural Network for target identification and detection using the ship image. The study involves the investigation of the reactions of hyper spectral atmospheric rectification on the accurate and precise results of ship detection. The ship features which were detected from two atmospheric rectified algorithms on airborne hyper spectral data were corrected by the application of these algorithms with the help of an unsupervised target detection procedure. High accuracy and fast ship identification was a result of this algorithm and using unique modules, improving the loss function and enlargement of data for the smaller targets. The results of the experiments show that our algorithm has given much better detection rate as compared to target detection algorithm using traditional machine learning.

Hardware Design for State Vector Identification of a Small Helicopter Model

2013 ◽  
Vol 282 ◽  
pp. 107-115 ◽  
Author(s):  
Viliam Fedák ◽  
Ján Bačík
Keyword(s):  
Degrees Of Freedom ◽  
Sensory System ◽  
Hardware Design ◽  
Sensor Data ◽  
State Variables ◽  
Six Degrees Of Freedom ◽  
Long Term Stability ◽  
Helicopter Flight ◽  
Embedded Computer

The paper deals with hardware design for sensory system of a small helicopter model that is characterized by a long-term stability and in real time generates data about helicopter state variables during helicopter flight. The sensor system is based on powerful 32-bit processors with the cores ARM7 and Cortex-M3. The main unit for data processing presents an embedded computer built on a mini-ITX motherboard with processor Intel i3. As the helicopter presents a system with six degrees of freedom and in the fact, during the flight, there is not any fixed point that would enable to caliber the sensors placed on the helicopter board, for processing of sensor data complex stochastic calculations are necessary. They are based on the discrete Kalman filter that present a main computing tool of the control system.

Control of processing at multi-tool two-support setup

2020 ◽  
pp. 67-73
Author(s):  
N.D. YUsubov ◽  
G.M. Abbasova
Keyword(s):  
Degrees Of Freedom ◽  
Factor Model ◽  
Angular Displacement ◽  
Factor Models ◽  
Technological System ◽  
Displacement Control ◽  
Model Accuracy ◽  
Six Degrees Of Freedom ◽  
Angular Displacements ◽  
And Control

The accuracy of two-tool machining on automatic lathes is analyzed. Full-factor models of distortions and scattering fields of the performed dimensions, taking into account the flexibility of the technological system on six degrees of freedom, i. e. angular displacements in the technological system, were used in the research. Possibilities of design and control of two-tool adjustment are considered. Keywords turning processing, cutting mode, two-tool setup, full-factor model, accuracy, angular displacement, control, calculation [email protected]

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