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The classification of wink-based eeg signals by means of transfer learning models by Jothi Letchumy, Mahendra Kumar

“…It was demonstrated from the simulation investigation that the CWT model could yield a better signal transformation amongst the preprocessing algorithms. In addition, amongst the eighteen TL models evaluated based on the CWT transformation, fourteen was f ound to be able to extract the features reasonable, i.e., VGG16, VGG19, ResNet101, ResNet101 V2, ResNet152, ResNet152 V2, Inception V3, Inception ResNet V2, Xception, MobileNetV2, DenseNet 121, DenseNet 169, NasNetMobile and NasNetLarge. …”
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Joint optimization of resources allocation for quality of service aware next-generation heterogeneous cellular networks / Hayder Faeq Rasool Alhashimi by Hayder Faeq Rasool , Alhashimi

“…Finally, a State-Action-Reward-State-Action (SARSA) algorithm, which is a reinforcement learning approach, is proposed to solve the power allocation optimization problem. …”
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Immune network algorithm in monthly streamflow prediction at Johor river by Mat Ali, Nur Izzah, Abdul Malik, Marlinda, Ismail , Amelia Ritahani

“…AIS has the abilities of self-organizing, memory, recognition, adaptive and ability of learning inspired from the immune system. Immune Network Algorithm is part of the three main algorithm in AIS. …”
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Multi-step time series prediction using recurrent kernel online sequential extreme learning machine / Liu Zongying by Liu , Zongying

“…However, the problems with traditional offline and online learning algorithms in machine learning algorithms are usually faced with parameter dependency, concept drift handling problem, connectionless of neural net and unfixed reservoir. …”
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DC-GAN-based synthetic X-ray images augmentation for increasing the performance of EfficientNet for COVID-19 detection by Pir Masoom Shah, Hamid Ullah, Rahim Ullah, Dilawar Shah, Yulin Wang, Saif ul Islam, Abdullah Gani, Rodrigues, Joel J. P. C.

“…In this paper, we used deep‐convolutional generative adversarial networks algorithm to address this issue, which generates synthetic images for all the classes (Normal, Pneumonia, and COVID‐19). …”
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Static code analysis of permission-based features for android malware classification using apriori algorithm with particle swarm optimization by Adebayo, Olawale Surajudeen, Abdul Aziz, Normaziah

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Hybrid signal processing and machine learning algorithm for adaptive fault classification of wind farm integrated transmision line protection by Olufemi, Osaji Emmanuel, Othman, Mohammad Lutfi, Hizam, Hashim, Othman, Muhammad Murtadha, Ammar, Aker Elhadi Emhemed Alhaaj, Okeke, Chidiebere Akachukwu, Onuabuchi, Nwagbara Samuel

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Immune network algorithm in monthly streamflow prediction at Johor river by Ali N.I.M., Malek M.A., Ismail A.R.

“…AIS has the abilities of self-organizing, memory, recognition, adaptive and ability of learning inspired from the immune system. Immune Network Algorithm is part of the three main algorithm in AIS. …”

Power allocation with non-orthogonal multiple access for 5G heterogeneous network by Johari, Muhammad Amirul Aiman, Anwar Apandi, Nur Ilyana, Muhammad, Nor Aishah

“…An algorithm is constructed based on the deep learning coordinated multi-point to simulate the performance of the downlink 5G. …”
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Modified symbiotic organisms search optimization for automatic construction of convolutional neural network architectures by Jauro, Fatsuma, Abdullahi, Usman Ali, Abdulsalami, Aminu Onimisi, Ibrahim, Adamu Abubakar, Abdullahi, Mohammed, Chiroma, Haruna

“…This research introduces an innovative approach to Convolutional Neural Network (ConvNet) architecture generation through the utilization of the Symbiotic Organism Search ConvNet (SOS_ConvNet) algorithm. …”
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Immune network algorithm in monthly streamflow prediction at Johor river by Mat Ali, Nur Izzah, Abdul Malek, Marlinda, Ismail, Amelia Ritahani

“…AIS has the abilities of self-organizing, memory, recognition, adaptive and ability of learning inspired from the immune system. Immune Network Algorithm is part of the three main algorithm in AIS. …”
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Deep learning segmentation of brain ischemic lesion from magnetic resonance images for three-dimensional modelling by Muhammad Ismaill, Mat Lizah, Nasrul Hadi, Johari, Mohd Jamil, Mohamed Mokhtarudin

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Android Malware classification using static code analysis and Apriori algorithm improved with particle swarm optimization by Adebayo, Olawale Surajudeen, Abdul Aziz, Normaziah

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Deep learning algorithm and IoT based system for Photovoltaic (PV) defect images classification by Mazlan, Nurul Atikah

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Deep learning-based classification of breast tumors in ultrasound images / Ayub Ahmed Omar by Ayub Ahmed, Omar

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Classification Of EEG Imagery Motor Function Using 3D Convolutional Neural Network by Kanesan, Thivagar

“…This EEG output signal will then be classified using deep learning technique known as 3D convolutional neural network to create a classification algorithm. 3D ConvNet is well-suited for spatiotemporal feature learning, where convolution and pooling operations are performed spatio-temporally. …”
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Blood cell classification using deep learning by Liaw, Mun Kin

“…The motivation was gotten from the literature review section where various researchers developed their own methods manually through experimenting such as ensemble methods, learning algorithms, combined methodologies, etc. Therefore, two ResNet models, ResNet-18 and ResNet-50 were built from scratch as the building blocks were studied and coded into the whole architecture which will run through several experiments of different configurations (batch size, learning rate, pooling layer, number of classes and number of dense layers). …”
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Comparative analysis of deepfake image detection method using VGG16, VGG19 and ResNet50 by Ashani, Zahra Nazemi, Che Ilias, Iszuanie Syfidza, Ng, Keng Yap, Kamel Ariffin, Muhammad Rezal, Jarno, Ahmad Dahari, Zamri, Nor Zarina

“…Specifically, we focus on three convolutional neural network (CNN) algorithms—VGG16, VGG19, and ResNet—for this purpose. …”
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A Reinforcement Learning Based Adaptive ROI Generation for Video Object Segmentation by Usmani, U.A., Watada, J., Jaafar, J., Aziz, I.A., Roy, A.

“…Meanwhile, our algorithm improves the accuracy by 8, F1 Measure by 12.25 , and precision by 14 on the CdNet 2014, thus ranking higher than the current state-of-the-art methods. …”
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The implications for ahybrid detection technique against malicious sqlattacks on web applications by Bahjat Arif, Sarajaldeen Akram, Wani, Sharyar

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