Search Results - (( leaf classifications using algorithm ) OR ( simulation optimization learning algorithm ))
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Hevea leaf features extraction and recognition algorithm for hevea clones classification using image / Mohamad Faizal Ab Jabal, Suhardi Hamid, Salehuddin Shuib
Published 2013“…Final result produced by the algorithm is 92.312% of average accuracy and the classification for the leaf was based on the leaf-shape information.…”
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Research Reports -
2
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
Leaf lesion classification (LLC) algorithm based on artificial bee colony (ABC)
Published 2015“…Results showed that the Leaf Lesion Classification (LLC) algorithm based on Artificial Bee colony (ABC) produced an average 96.83% of accuracy and average 1.66 milliseconds of processing time, indicating that LLC algorithm is better than algorithm such as Otsu, Canny, Roberts and Sobel. …”
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4
Classification of Citrus (Rutaceae) by Using Image Processing
Published 2019“…The study present how to classify selected Citrus genus species with similar leaf shapes based on leaf images by using digital image vision machine classification. …”
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Undergraduate Final Project Report -
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Plant recognition based on identification of leaf image using image processing / Nor Silawati Sha’ari
Published 2018“…Image processing techniques are used to extract the leaf feature from histogram of the leaf image. …”
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6
Opposition-based learning simulated kalman filter for Numerical optimization problems
Published 2016“…Simulated Kalman Filter (SKF) optimization algorithm is a population-based optimizer operated mainly based on Kalman filtering. …”
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Research Book Profile -
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Performance analysis of machine learning algorithms for classification of infection severity levels on rubber leaves
Published 2023“…The chlorophyll content of each leaf was measured using SPAD meter. Four classification algorithms investigated in this study were artificial neural network (ANN), support vector machine (SVM), knearest neighbour (kNN) and random forest (RF). …”
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8
Automated leaf alignment and partial shape feature extraction for plant leaf classification
Published 2019“…The last few decades have witnessed various approaches to automate the process of plant classification using the characteristics of the leaf. …”
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Investigating the Performance of Deep Reinforcement Learning-Based MPPT Algorithm under Partial Shading Condition
Published 2024“…These DRL-based algorithms optimize the local and global maximum power point (MPP) using deep Q-learning and deep deterministic policy gradient (DDPG). …”
Conference Paper -
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Effects of Different Pre-Trained Deep Learning Algorithms as Feature Extractor in Tomato Plant Health Classification
Published 2023“…This study proposes a system that can classify tomato plant health into five categories of healthy, early blight, late blight, bacterial spot, and yellow leaf curl virus based on their leaves using deep learning algorithms as feature extractors. …”
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A novel framework for potato leaf disease detection using an efficient deep learning model
Published 2022“…Therefore, this article proposes a technique based on an improved deep learning algorithm that uses the potato leaf visual features to classify them into five classes i.e., Potato Late Blight (PLB), Potato Early Blight (PEB), Potato Leaf Roll (PLR), Potato Verticilliumwilt (PVw) and Potato Healthy (PH) class. …”
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A novel framework for potato leaf disease detection using an efficient deep learning model
Published 2022“…Therefore, this article proposes a technique based on an improved deep learning algorithm that uses the potato leaf visual features to classify them into five classes i.e., Potato Late Blight (PLB), Potato Early Blight (PEB), Potato Leaf Roll (PLR), Potato Verticilliumwilt (PVw) and Potato Healthy (PH) class. …”
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13
Application of Fuzzy C-Means with YCbCr and DenseNet-201 for Automated Corn Leaf Disease Detection
Published 2021“…The results show that the proposed method performed better than the previous methods with 96.81% for segmentation as well as 95.11% for classification and it is discovered to be a good fusion of algorithms to detect plant leaf diseases.…”
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Deriving Optimal Operation Rule for Reservoir System Using Enhanced Optimization Algorithms
Published 2025Subjects:Article -
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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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17
A Hybrid of Ant Colony Optimization Algorithm and Simulated Annealing for Classification Rules
Published 2013“…In the first proposed algorithm, SA is used to optimize the rule's discovery activity by an ant. …”
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Development of self-learning algorithm for autonomous system utilizing reinforcement learning and unsupervised weightless neural network / Yusman Yusof
Published 2019“…From the simulation result, by using these sensors information the AUTOWiSARD algorithm can successfully differentiate and classify states without supervision, while the Q-learning algorithm is able to produce and optimized states-actions policy. …”
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Effects of Different Pre-Trained Deep Learning Algorithms as Feature Extractor in Tomato Plant Health Classification
Published 2023“…This study proposes a system that can classify tomato plant health into five categories of healthy, early blight, late blight, bacterial spot, and yellow leaf curl virus based on their leaves using deep learning algorithms as feature extractors. …”
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Effects of Different Pre-Trained Deep Learning Algorithms as Feature Extractor in Tomato Plant Health Classification
Published 2023“…This study proposes a system that can classify tomato plant health into five categories of healthy, early blight, late blight, bacterial spot, and yellow leaf curl virus based on their leaves using deep learning algorithms as feature extractors. …”
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