Iwin Thanakumar Joseph S., Sasikala J. and Sujitha Juliet D.
The purpose of this paper is to study various ship detection methodologies. The accuracy of ship detection using satellite images still suffers from disturbances due to cluttered…
Abstract
Purpose
The purpose of this paper is to study various ship detection methodologies. The accuracy of ship detection using satellite images still suffers from disturbances due to cluttered scenes and varying ship sizes. The suitability of the techniques for various applications is explained in this survey.
Design/methodology/approach
A list of data on the subject was gathered and processed into tables. The test outcomes were then discussed to determine the most effective ship detection technique under various complex environments.
Findings
In this work, the advantages and disadvantages of different classification techniques of ship detection are highlighted. The suitability of the techniques for various applications is also explained in this survey. Several hybrid approaches can be developed in order to increase the accuracy of ship detection system. This survey also aids in highlighting the significant contributions of satellite images to effective ship detection system.
Originality/value
In this paper, studying various ship detection methodologies is given specific attention. A survey on ship detection and recognition is clarified with the detailed comparative analysis of various classifier techniques.
Details
Keywords
Iwin Thanakumar Joseph Swamidason, Sravanthy Tatiparthi, Karunakaran Velswamy and S. Velliangiri
An intelligent personal assistant for personal computers (PCs) is a vital application for the current generation. The current computer personal assistant services checking…
Abstract
Purpose
An intelligent personal assistant for personal computers (PCs) is a vital application for the current generation. The current computer personal assistant services checking frameworks are not proficient at removing significant data from PCs and long-range informal communication information.
Design/methodology/approach
The proposed verbalizers use long short-term memory to classify the user task and give proper guidelines to the users. The outcomes show that the proposed method determinedly handles heterogeneous information and improves precision. The main advantage of long short-term memory is that handle the long-term dependencies in the input data.
Findings
The proposed model gives the 22% mean absolute error. The proposed method reduces mean square error than support vector machine (SVM), convolutional neural network (CNN), multilayer perceptron (MLP) and K-nearest neighbors (KNN).
Originality/value
This paper fulfills the necessity of intelligent personal assistant for PCs using verbalizer.