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Image classification of Aedes mosquitoes using transfer learning / Zetty Ilham Abdullah by Abdullah, Zetty Ilham

“…The advancement and rapid growth of machine learning field should not overlook this issue. Transfer learning concept in machine learning has been shown to improve learning of the targeted task by extending the original algorithm with knowledge gathered from the initial training to improve the performance of new model. …”
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A hybrid deep CNN model for fast class-incremental food classification / Aymen Taher Ahmed al-Ashwal by Aymen Taher , Ahmed al-Ashwal

“…Lastly, the incremental learning algorithm ABACOC is used to classify each feature of food classes. …”
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A new classifier based on combination of genetic programming and support vector machine in solving imbalanced classification problem by Mohd Pozi, Muhammad Syafiq

“…In addition, the classifier is also optimized such that it has a good generalization property. The main keys of the new classifier are based on the new kernel method, new learning metric and a new optimization algorithm in order to optimize the SVM decision function. …”
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An ensemble learning method for spam email detection system based on metaheuristic algorithms by Behjat, Amir Rajabi

“…Recently, various techniques based on different algorithms have been developed. However, the classification accuracy and computational cost are not satisfied. …”
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A new hybrid deep neural networks (DNN) algorithm for Lorenz chaotic system parameter estimation in image encryption by Nurnajmin Qasrina Ann, Ayop Azmi

“…The first research objective is to develop a new deep learning algorithm by a hybrid of DNN and K-Means Clustering algorithms for estimating the Lorenz chaotic system. …”
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The classification of wink-based eeg signals by means of transfer learning models by Jothi Letchumy, Mahendra Kumar

“…A new form of input which consists of scalogram and spectrogram images that represents both time and frequency domains , are then introduced in the classification of wink-based EEG signals. …”
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Neural network paradigm for classification of defects on PCB by Heriansyah, Rudi, Syed Al-Attas, Syed Abdul Rahman, Zabidi, Muhammad Mun'im Ahmad

“…The algorithms to segment the image into basic primitive patterns, enclosing the primitive patterns, patterns assignment, patterns normalization, and classification have been developed based on binary morphological image processing and Learning Vector Quantization (LVQ) neural network. …”
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Deep learning-based item classification for retail automation by Ling, Ji Xiang

“…This project focuses on developing a deep learning-based system for retail item classification. …”
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Automated plant classification system using a hybrid of shape and color features of the leaf by Hamid, Laith Emad

“…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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Reassembly and clustering bifragmented intertwined jpeg images using genetic algorithm and extreme learning machine by Raad Ali, Rabei

“…The RX_myKarve is an extended framework from X_myKarve, which consists of the following key components: (i) an Extreme Learning Machine (ELM) neural network for clusters classification using three existing content-based features extraction (Entropy, Byte Frequency Distribution (BFD) and Rate of Change (RoC)) to improve the identification of JPEG images content and support the reassembling process; (ii) a genetic algorithm with Coherence Euclidean Distance (CED) matric and cost function to reconstruct a JPEG image from a set of deformed and fragmented clusters in the scan area. …”
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Phylogenetic tree classification system using machine learning algorithm by Tan, Jia Kae

“…A study is conducted to develop an automated phylogenetic tree image classification system by using machine learning algorithm. …”
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A Comparative Analysis of Machine Learning and Deep Learning Algorithms for Image Classification by Madanan M., Gunasekaran S.S., Mahmoud M.A.

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Evaluation of the Transfer Learning Models in Wafer Defects Classification by Jessnor Arif, Mat Jizat, Anwar, P. P. Abdul Majeed, Ahmad Fakhri, Ab. Nasir, Zahari, Taha, Yuen, Edmund, Lim, Shi Xuen

“…The key metrics for the evaluation are classification accuracy, classification precision and classification recall. 855 images were used to train and test the algorithms. …”
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The use of SOM for fingerprint classification by Turky A.M., Ahmad M.S.

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Detection of sweetness level for fruits (watermelon) with machine learning by Wan Nazulan, Wan Nurul Suraya, Asnawi, Ani Liza, Mohd Ramli, Huda Adibah, Jusoh, Ahmad Zamani, Ibrahim, Siti Noorjannah, Mohamed Azmin, Nor Fadhillah

“…The objective of this work is to investigate the sweetness parameter for the fruit’s detection and classification algorithm in machine learnings. This study applies image processing techniques to detect the color and shape of watermelon’s skin for grading based on the sweetness level using K-means clustering method via the Python platform. 13 samples of watermelon images are used to test the functionality of the proposed detection system in this study. …”
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Classification of brain tumors: using deep transfer learning by Husin, Nor Azura, Husam, Mohamed, Hussin, Masnida

“…Experimenters employed data augmentation and learning algorithms.…”
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Classification of diabetic retinopathy clinical features using image enhancement technique and convolutional neural network / Abdul Hafiz Abu Samah by Abu Samah, Abdul Hafiz

“…In general, this thesis introduces an automated machine learning algorithm for detecting diabetic retinopathy (DR) in fundus images. …”
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Transfer Learning for Lung Nodules Classification with CNN and Random Forest by Abdulrazak, Saleh, Chee, Ka Chin, Ros Ameera, Rosdi

“…This research demonstrates the potential of using machine learning algorithms in the healthcare industry, especially in disease detection and classification.…”
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Classification of Planetary Nebulae through Deep Transfer Learning by Dayang N.F., Awang Iskandar, Zijlstra, Albert A., McDonald, Iain, Rosni, Abdullah, Fuller, Gary A., Ahmad H., Fauzi, Johari, Abdullah

“…It focusses on distinguishing PNe from other types of objects, as well as their morphological classification. We adopted the deep transfer learning approach using three ImageNet pre-trained algorithms. …”
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Gender classification based on asian faces using deep learning by Janahiraman T.V., Subramaniam P.

“…Face recognition; Human computer interaction; Image classification; Learning algorithms; Natural language processing systems; Neural networks; Speech recognition; Systems engineering; Convolutional neural network; Gender classification; Learning architectures; Learning frameworks; NAtural language processing; Recognition accuracy; Recognition process; TensorFlow; Deep learning…”