Search Results - (( code classification using algorithm ) OR ( image classification modeling algorithm ))
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Scene classification for aerial images based on CNN using sparse coding technique
Published 2017“…Aerial scene classification purposes to automatically label aerial images with specific semantic categories. …”
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Scene classification for aerial images based on CNN using sparse coding technique
Published 2023Article -
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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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An improved plant identification system by Fuzzy c-means bag of visual words model and sparse coding
Published 2020“…Bag of visual words (BoVW) model and its variants are used effectively for the retrieval of images by many researchers. …”
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Phishing image spam classification research trends: Survey and open issues
Published 2020“…At present, the email is submerged with spam content, both in text-based form or undesired text planted inside the images. This study reviews articles on phishing image spam classification published from 2006 to 2020 based on spam classification application domains, datasets, features sets, spam classification methods, and the measurement metrics adopted in the existing studies. …”
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Automatic multilevel medical image annotation and retrieval
Published 2008“…Image annotation performance largely depends on three issues: (1) automatic image feature extraction; (2) a semantic image concept modeling; (3) algorithm for semantic image annotation. …”
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Deep learning based emotion recognition for image and video signals: matlab implementation
Published 2021“…This book is carried out to develop an image and video-based emotion recognition model using CNN for automatic feature extraction and classification with Matlab sample codes. …”
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Dual-tone multifrequency signal detection using support vector machines
Published 2023Conference paper -
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A multilayered convolutional sparse coding framework for modeling of pooling operation of convolution neural networks
Published 2019“…The multilayered version of CSC(ML-CSC) is shown to be connected to forward pass of CNNs and dictionary learning and sparse coding algorithms of this model are analyzed for solving classification and inverse problems in image processing. …”
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Proceeding Paper -
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Pemetaan Pm10 Dan Aot Menggunakan Teknik Penderiaan Jauh Di Semenanjung Malaysia
Published 2006“…The proposed algorithms were used to generate PM10 and AOT maps for the study areas. …”
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Using genetic algorithms to optimise land use suitability
Published 2012“…In this study, under environmentfriendliness objective, based on multi-agent genetic algorithms, was developed a geospatial model for the land use allocation. …”
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Android Malware classification using static code analysis and Apriori algorithm improved with particle swarm optimization
Published 2014“…In this method, features were extracted from Android applications byte-code through static code analysis, selected and were used to train supervised classifiers. …”
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Proceeding Paper -
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Static code analysis of permission-based features for android malware classification using apriori algorithm with particle swarm optimization
Published 2015“…However, supervised learning technique has limitations for malware classification task. This paper presents a classification approach on android malware using candidate detectors generated from an unsupervised association rule of Apriori Algorithm. …”
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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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An improved pixel-based and region-based approach for urban growth classification algorithms / Nur Laila Ab Ghani
Published 2015“…The urban growth images obtained are analysed to improve existing classification algorithms. …”
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Evaluation of the Transfer Learning Models in Wafer Defects Classification
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Classification of Citrus (Rutaceae) by Using Image Processing
Published 2019“…This research will be conducted by using digital image processing approach based on the morphological features of leaf with the combination of gray level co-occurrence matrix (GLCM), Prewitt and Canny algorithm and training classification models by using support vector machine (SVM). …”
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Undergraduate Final Project Report -
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A Comparative Analysis of Machine Learning and Deep Learning Algorithms for Image Classification
Published 2024Subjects:Conference Paper
