Search Results - (( parametric classification using algorithm ) OR ( leaf optimization method algorithm ))
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Improvement of land cover mapping using Sentinel 2 and Landsat 8 imageries via non-parametric classification
Published 2020“…Nevertheless, AC is not required for LCM if the original multi-spectral image is used. The last phase involves developing a new fusion algorithm using SVM and Fuzzy K-Means Clustering (FKM) algorithms for Sentinel 2 data to enhance LCM accuracy. …”
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Automated plant classification system using a hybrid of shape and color features of the leaf
Published 2016“…Automated plant leaf classification is a computerized approach that employs computer vision and machine learning algorithms to identify a plant based on the features of its leaf. …”
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3
Validation on an enhanced dendrite cell algorithm using statistical analysis
Published 2017“…In this study, we evaluated the performance of the enhanced algorithm called dendrite cell algorithm using sensitivity, specificity, false positive rate, and accuracy and validated the result using parametric and non parametric statistical significant tests. …”
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Leaf condition analysis using convolutional neural network and vision transformer
Published 2024“…Besides, existing leaf disease detection programs do not provide an optimized user’s experience. …”
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Plant leaf recognition algorithm using ant colony-based feature extraction technique
Published 2013“…Then, based on the characteristics of each species, decision making is done by means of ant colony optimisation as a search algorithm to return the optimal subset of features regarding the related species. …”
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Plant identification using combination of fuzzy c-means spatial pyramid matching, gist, multi-texton histogram and multiview dictionary learning
Published 2016“…Moreover, instead of concatenating feature vectors together and send to classifier, sparse coding and dictionary learning methods are used and instead of considering all features as one view (visual feature), K-SVD algorithm that is one of the famous algorithms for sparse representation is optimized and developed to multi-view model.The experimental results prove that the proposed methods has improved accuracy by 53.77% compared to concatenating features and classic K-SVD dictionary learning model as well.…”
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8
Data Analysis and Rating Prediction on Google Play Store Using Data-Mining Techniques
Published 2022“…This study aims to predict the ratings of Google Play Store apps using decision trees for classification in machine learning algorithms. …”
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Generalized derivations and automorphisms of some classes of algebras
Published 2019“…In the Leibniz algebra case, we had eight subspaces too, with different structures, it includes two one-parametric sets as well. Furthermore, by using the two one-parametric sets, two invariant functions are de- fined. …”
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10
Application of Decision Trees in Athlete Selection: A Cart Algorithm Approach
Published 2023“…The focus of this study is on the use of DTs, employing the Classification and Regression Trees (CART) algorithm, in the initial screening of athletes. …”
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Balancing Exploitation And Exploration Search Behavior On Nature-Inspired Clustering Algorithms
Published 2018“…The experimental results are also thoroughly evaluated and verified via non-parametric statistical analysis. Based on the obtained experimental results, the OGC, DPSO, and VDEO frameworks achieved an average enhancement up to 24.36%, 9.38%, and 11.98% of classification accuracy, respectively. …”
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Deep plant: A deep learning approach for plant classification / Lee Sue Han
Published 2018“…They look for the procedures or algorithms that maximize the use of leaf databases for plant predictive modelling, but this results in leaf features which are liable to change with different leaf data and feature extraction techniques. …”
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13
Enhancing battery state of charge estimation through hybrid integration of barnacles mating optimizer with deep learning
“…In response to the growing importance of SoC estimation, this study introduces a hybrid approach called the Barnacles Mating Optimizer with Deep Learning (BMO-DL) for SoC of Nissan Leaf batteries. …”
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Novel voice activity detection based on cepstrum moments
Published 2010“…In this paper we propose a novel statistical VAD algorithm using Cepstrum coefficients and their moments as features for classification. …”
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An optimized variant of machine learning algorithm for datadriven electrical energy efficiency management (D2EEM)
Published 2024“…It is a well-established fact that machine learning is outperforming in terms of prediction and classification. Therefore, in this study a new optimized variant of machine learning algorithms is presented. …”
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Image Splicing Detection With Constrained Convolutional Neural Network
Published 2019“…It is shown that CNN with constrained convolution algorithm can be used as a general image splicing detection task.…”
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Oil palm mapping over Peninsular Malaysia using Google Earth Engine and machine learning algorithms
Published 2020“…In this study, 30 m Landsat 8 data were processed using a cloud computing platform of Google Earth Engine (GEE) in order to classify oil palm land cover using non-parametric machine learning algorithms such as Support Vector Machine (SVM), Classification and Regression Tree (CART) and Random Forest (RF) for the first time over Peninsular Malaysia. …”
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Development of compound clustering techniques using hybrid soft-computing algorithms
Published 2006“…The neural network methods use a number of heuristics to find appropriate parametric values. …”
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Hybrid conjugate gradient using exact line search in photovoltaic system / Muhammad Ariiq Iqbaal Azizul Firdaus
Published 2025“…Various studies have been undertaken by implementing the CG method in image restoration, optimal rocket landing guidance and motion control field. There are a few classifications of CG method such as classical, hybrid, three-term and parametric CG methods. …”
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Introducing new statistical shape based and texture feature extraction methods in the plant species recognition system
Published 2013“…The results show the outperformance of the two proposed methods for image processing and optimized classifier for classification part. …”
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