Search Results - (( image classification method algorithm ) OR ( changes optimization method algorithm ))
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A new classifier based on combination of genetic programming and support vector machine in solving imbalanced classification problem
Published 2016“…Algorithmic level based methods however are based on introducing new optimization task to improve the minority class classification rate, without changing the data characteristics. …”
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An ensemble learning method for spam email detection system based on metaheuristic algorithms
Published 2015“…In order to address the challenges that mentioned above in this study, in the first phase, a novel architecture based on ensemble feature selection techniques include Modified Binary Bat Algorithm (NBBA), Binary Quantum Particle Swarm Optimization (QBPSO) Algorithm and Binary Quantum Gravita tional Search Algorithm (QBGSA) is hybridized with the Multi-layer Perceptron (MLP) classifier in order to select relevant feature subsets and improve classification accuracy. …”
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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“…The combination of gist, MTH and SIFT features increased the performance of image identification and showed 49% accuracy. 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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Analysis Of Personal Protective Equipment Classification Method Using Deep Learning
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Face emotion recognition using artificial intelligence techniques
Published 2008“…FER is achieved in two parts, they are image processing part and classification part. The first part investigates a set of image processing methods suitable for recognizing the face emotion. …”
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Iban Plaited Mat Motif Classification using Adaptive Smoothing
Published 2024“…To address this issue, an improved classification method with adaptive smoothing is proposed. …”
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Durian (Durio zibethinus) ripeness detection using thermal imaging with multivariate analysis
Published 2021“…Linear discriminant analysis (LDA), k-nearest neighbour (kNN), and support vector machine (SVM) were applied for the establishment of the optimal classification modelling algorithms. The SVM classifier gave the overall best performance for the discrimination of durian ripeness with a classification accuracy of 97 %. …”
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Task-state EEG signal classification for spatial cognitive evaluation based on multiscale high-density convolutional neural network
Published 2022“…In this study, a multi-scale high-density convolutional neural network (MHCNN) classification method for spatial cognitive ability assessment was proposed, aiming at achieving the binary classification of task-state EEG signals before and after spatial cognitive training. …”
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Deep plant: A deep learning approach for plant classification / Lee Sue Han
Published 2018“…Besides using solely a single leaf organ to recognize plant species, numerous studies have employed DL methods to solve multi-organ plant classification problem. …”
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Using genetic algorithms to optimise land use suitability
Published 2012“…Second task is to determine the fitness function for the genetic algorithms. The third objective is to optimize the land use map using economic benefits. …”
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Improving Classification of Remotely Sensed Data Using Best Band Selection Index and Cluster Labelling Algorithms
Published 2005“…In addition, the best band selected for image classification is not necessarily the best for classification.A Best Band Selection Index (BBSI) algorithm was developed which is capable of selecting the best band combination for image visualization and supervised classification. …”
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Daisy species classification based on image using Convolutional Neural Network algorithm / Haris Hidayatullah Khaimuza
Published 2024“…Second objective is to develop the prototype of daisy species classification based on image using CNN algorithm. The last objective is to evaluate the accuracy of CNN model in the daisy species classification based on image. …”
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Evaluation and Comparative Analysis of Feature Extraction Methods on Image Data to increase the Accuracy of Classification Algorithms
Published 2024“…This research compares three different methods for extracting features from fruit images to determine which method yields the highest accuracy for fruit classification. …”
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Feature extraction and selection algorithm based on self adaptive ant colony system for sky image classification
Published 2023“…Therefore, an improved feature extraction and selection for sky image classification (FESSIC) algorithm is proposed. …”
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Real-time oil palm fruit bunch ripeness grading system using image processing techniques
Published 2013“…In this research, a real time oil palm grading system was built and an image processing techniques algorithm was developed based on the external features of oil palm fresh fruit bunches (FFB) such as colour, texture, and thorns. …”
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Sauvola Segmentation and Support Vector Machine-Salp Swarm Algorithm Approach for Identifying Nutrient Deficiencies in Citrus Reticulata Leaves
Published 2024“…The proposed method integrates colour and texture feature-based image analysis with machine learning algorithms for classification. …”
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Image Classification with Higher-Dimension Watershed Classifier: A Test to Malaysian National Land Use Classification Scheme
Published 1996“…Recent image classification based on watershed algorithm (Watson et. al.,1992) has reported as a potential method for producing accurate method of classifying satellite images. …”
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Aerial imagery paddy seedlings inspection using deep learning
Published 2022“…The emergence of artificial intelligence due to the capability of recent advances in computing architectures could become a new alternative to existing solutions. Deep learning algorithms in computer vision for image classification and object detection can facilitate the agriculture industry, especially in paddy cultivation, to alleviate human efforts in laborious, burdensome, and repetitive tasks. …”
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