An Intelligent Approach to Positive Target Identification

Singh, Ram-Nandan P.

doi:10.1016/b978-012646490-0/50025-1

Cited by 2 publications

(4 citation statements)

References 10 publications

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“…Pyramids are multi-scale signal representation where a signal is subject to repeated smoothing and subsampling. Two types of pyramids exist that is Gaussian and Laplacian pyramid, also known as lowpass and bandpass pyramid respectively (Singh, Sinha, & Gupta, 2000). However, this study places more emphasis on the Laplacian pyramid.…”

Section: The Gaussian and Laplacian Pyramidmentioning

confidence: 92%

“…The Laplacian pyramid, as applied to a digital image, is constructed by taking the difference between adjacent layers in the Gaussian pyramid. In practice, these layers are of varying size, and the smaller sized layers are expanded using interpolating techniques (Singh, Sinha, & Gupta, 2000). Mathematically, this concept is set up as follows.…”

Section: The Gaussian and Laplacian Pyramidmentioning

confidence: 99%

“…Given a 2D image, let u(x, y, t) represent a Gaussian pyramid then the difference of levels can be stated as u(x, y, t 2 ) -u(x, y, t 1 ). With the assumption that Gaussian pyramid function is a solution to the heat diffusion equation (Singh, Sinha, & Gupta, 2000), the Laplacian pyramid function V(x, y, t) is formed with the relation in Eqn. 1:…”

Section: The Gaussian and Laplacian Pyramidmentioning

confidence: 99%

See 2 more Smart Citations

Primary Mobile Image Analysis of Human Intestinal Worm Detection

Appati

Yaokumah

Owusu

et al. 2022

International Journal of System Dynamics Applications

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One among a lot of public health concerns in rural and tropical areas is the human intestinal parasite. Traditionally, diagnosis of these parasites is by visual analysis of stool specimens, which is usually tedious and time-consuming. In this study, the authors combine techniques in the Laplacian pyramid, Gabor filter, and wavelet to build a feature vector for the discrimination of intestinal worm in a low-resolution image captured with mobile devices. The dimension of the feature vector is reduced using principal component analysis, and the resultant vector is considered as input to the SVM classifier. The proposed framework was applied to the Makerere intestinal dataset. At its preliminary stage, the results demonstrate satisfactory classification with an accuracy rate of 65.22% with possible extension in future work.

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Section: The Gaussian and Laplacian Pyramidmentioning

confidence: 92%

Section: The Gaussian and Laplacian Pyramidmentioning

confidence: 99%

Section: The Gaussian and Laplacian Pyramidmentioning

confidence: 99%

See 1 more Smart Citation

Primary Mobile Image Analysis of Human Intestinal Worm Detection

Appati

Yaokumah

Owusu

et al. 2022

International Journal of System Dynamics Applications

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“…An FLC will be designed to guide the DDWMR from the current robot's position Q(xQ, yQ) to the waypoint W(xW, yW). The general structure of a fuzzy logic controller is shown in Figure 5 [30][31][32]. The block diagram of the FLC used for the DDWMR is shown in Figure 6.…”

Section: Design Of the Initail Fuzzy Logic Controllermentioning

confidence: 99%

Optimization of Fuzzy Logic Controller Used for a Differential Drive Wheeled Mobile Robot

et al. 2021

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The energy-efficient motion control of a mobile robot fueled by batteries is an especially important and difficult problem, which needs to be continually addressed in order to prolong the robot’s independent operation time. Thus, in this article, a full optimization process for a fuzzy logic controller (FLC) is proposed. The optimization process employs a genetic algorithm (GA) to minimize the energy consumption of a differential drive wheeled mobile robot (DDWMR) and still ensure its other performances of the motion control. The earlier approaches mainly focused on energy reduction by planning the shortest path whereas this approach aims to optimize the controller for minimizing acceleration of the robot during point-to-point movement and thus minimize the energy consumption. The proposed optimized controller is based on fuzzy logic systems. At first, an FLC has been designed based on the experiment and as well as an experience to navigate the DDWMR to a known destination by following the given path. Next, a full optimization process by using the GA is operated to automatically generate the best parameters of all membership functions for the FLC. To evaluate its effectiveness, a set of other well-known controllers have been implemented in Google Colab® and Jupyter platforms in Python language to compare them with each other. The simulation results have shown that about 110% reduction of the energy consumption was achieved using the proposed method compared to the best of six alternative controllers. Also, this simulation program has been published as an open-source code for all readers who want to continue in the research.

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An Intelligent Approach to Positive Target Identification

Cited by 2 publications

References 10 publications

Primary Mobile Image Analysis of Human Intestinal Worm Detection

Primary Mobile Image Analysis of Human Intestinal Worm Detection

Optimization of Fuzzy Logic Controller Used for a Differential Drive Wheeled Mobile Robot

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