Search Results - (( leaf optimization methods algorithm ) OR ( parameter evaluation a algorithm ))
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1
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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2
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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3
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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4
Evaluation of multiple In Situ and remote sensing system for early detection of Ganoderma boninense infected oil palm
Published 2018“…In conclusion, for early detection of Ganoderma, better accuracies were derived from the spectroradiometer which is a destructive and ground based method and still requires individual leaf sampling. …”
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5
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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6
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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7
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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An alternative approach to normal parameter reduction algorithms for decision making using a soft set theory / Sani Danjuma
Published 2017“…Many normal parameter reduction algorithms exist to handle parameter reduction and maintain consistency of decision choices. …”
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9
Evaluating power efficient algorithms for efficiency and carbon emissions in cloud data centers: a review
Published 2015“…The three algorithms are evaluated for performance using three parameters; power efficiency, cost effectiveness, and amount of CO2 emissions. …”
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Evaluation of lightning current parameters using measured lightning induced voltage on distribution power lines
Published 2023Conference Paper -
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Modeling time series data using Genetic Algorithm based on Backpropagation Neural network
Published 2018“…Finally, a GA based BPNN called (GA-BPNN) is designed and evaluated. …”
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12
Hyperdize Jaya Algorithm for Harmony Search Algorithm's Parameters Selection
Published 2016“…This paper present a successful method to tune the parameters of the harmony search algorithm, which is a well-known meta-heuristic algorithm. …”
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Performance Evaluation of Maximum Power Point Tracking Approaches and Photovoltaic Systems
Published 2018“…In the last phase, a comparative table presents performance-evaluating parameters of MPPT design criterion. …”
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14
A study on the parameter selection of bat algorithm in in optimizing parameters in camera auto calibration problem
Published 2022“…Each bat in the Bat Algorithm represents a potential solution to the issue, and each dimension in the Bat Algorithm's search space represents one of the basic parameters: skew, focal length, and magnification factor. …”
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15
A Hybrid Least Squares Support Vector Machine with Bat and Cuckoo Search Algorithms for Time Series Forecasting
Published 2020“…Evaluation was performed separately to further analyze the strength of Bat and Cuckoo Search to optimize LSSVM parameters. …”
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16
Inversed Control Parameter in Whale Optimization Algorithm and Grey Wolf Optimizer for Wrapper-Based Feature Selection: A Comparative Study
Published 2023“…The proposed mWOA and mGWO were given a new inversed control parameter expected to enable more search areas for the search agents in the early phase of the algorithms, resulting in a faster convergence speed. …”
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Inversed Control Parameter in Whale Optimization Algorithm and Grey Wolf Optimizer for Wrapper-Based Feature Selection: A Comparative Study
Published 2023“…The proposed mWOA and mGWO were given a new inversed control parameter expected to enable more search areas for the search agents in the early phase of the algorithms, resulting in a faster convergence speed. …”
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Two level Differential Evolution algorithms for ARMA parameters estimatio
Published 2013“…The results of both examples show the effectiveness of the proposed algorithm over a well known conventional technique.…”
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A Preliminary Study on Camera Auto Calibration Problem Using Bat Algorithm
Published 2013“…Each bat in Bat Algorithm represents a candidate solution for the problem and each dimension in the search space of the Bat Algorithm represents a parameter of intrinsic parameters: skew, focal length, and magnification factor. …”
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Adaptive differential evolution algorithm with fitness based selection of parameters and mutation strategies / Rawaa Dawoud Hassan Al-Dabbagh
Published 2015“…The second taxonomy is a new taxonomy proposed to classify the adaptive DE algorithms in particular into two categories (DE with adaptive parameters and DE with adaptive parameters and strategies) considering the adaptive components used in this algorithm. …”
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