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Learning a deeply supervised multi-modal RGB-D embedding for semantic scene and object category recognition by Mohd Zaki, Hasan Firdaus, Shafait, Faisal, Mian, Ajmal

“…This technique motivates bilateral transfer learning between the modalities by taking the outer product of each feature extractor output. …”
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Operational structural damage identification using de-noised modal feature in machine learning / Chen Shilei by Chen , Shilei

“…By integrating ISMA, both supervised and unsupervised machine learning algorithms were investigated to develop real-time damage identification schemes. …”
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Effect of different modalities of facial images for diagnosis of ASD by deep neural network by Rashid, Muhammad Mahbubur, Alam, Mohammad Shafiul, Haque, M A, Ali, Mohammad Yeakub, Yvette, Susiapan

“…This research aims to explore the potential of various facial image types in diagnosing Autism Spectrum Disorder (ASD) through the application of deep learning neural networks. It delves into how deep learning algorithms perform with different facial image modalities, especially 2D and 3D, while addressing specific challenges associated with each. …”
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Real time electrocardiogram identification with multi-modal machine learning algorithms by Waili, Tuerxun, Mohd Nor, Rizal, Sidek, Khairul Azami, Abdul Rahman, Abdul Wahab, Guven, Ghokan

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Adaptive Neuro Fuzzy Inference System (ANFIS) and Artificial Neural Networks (ANNs) for structural damage identification by Hakim, S.J.S., Abdul Razak, H.

“…However the proposed ANFIS architecture using hybrid learning algorithm was found to perform better than the multilayer feedforward ANN which learns using the backpropagation algorithm. …”
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Multi-modal association learning using spike-timing dependent plasticity (STDP) by Ibrahim, Mohammed Fadhil

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Recent Automatic Segmentation Algorithms of MRI Prostate Regions: A Review by Khan, Z., Yahya, N., Alsaih, K., Al-Hiyali, M.I., Meriaudeau, F.

“…This survey reviewed 22 machine learning and 88 deep learning-based segmentation of prostate MRI papers, including all MRI modalities. …”
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Recent Automatic Segmentation Algorithms of MRI Prostate Regions: A Review by Khan, Z., Yahya, N., Alsaih, K., Al-Hiyali, M.I., Meriaudeau, F.

“…This survey reviewed 22 machine learning and 88 deep learning-based segmentation of prostate MRI papers, including all MRI modalities. …”
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Personalized Clothing Prediction Algorithm Based on Multi-modal Feature Fusion by Rong, Liu, Annie, Joseph, MiaoMiao, Xin, Hongyan, Zang, Wanzhen, Wang, Shengqun, Zhang

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Data mining for structural damage identification using hybrid artificial neural network based algorithm for beam and slab girder / Meisam Gordan by Meisam , Gordan

“…To this end, experimental modal analysis of aforesaid structures was carried out by introducing different damage scenarios to generate the modal parameter database. …”
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Development of damage identification scheme using de-noised modal frequency response function data with artificial neural network / Mohamad Izzudin Hussein Shah by Mohamad Izzudin , Hussein Shah

“…Multilayer Perceptron (MLP) with backpropagation learning algorithm ANN is used in this study. Moreover, this study needs to minimize the number of samples used by reducing number of sensors and frequency range used without affecting the performance accuracy. …”
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Data fusion and multiple classifier systems for human activity detection and health monitoring: Review and open research directions by Nweke, Henry Friday, Teh, Ying Wah, Mujtaba, Ghulam, Al-Garadi, Mohammed Ali

“…Recently, deep learning algorithms for automatic feature representation have also been proposed to lessen the burden of reliance on handcrafted features and to increase performance accuracy. …”
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Revolutionizing video analytics: a review of action recognition using 3D by Jeddah, Yunusa Mohammed, Hassan Abdalla Hashim, Aisha, Khalifa, Othman Omran, Ibrahim, Adamu Abubakar

“…This paper provides an overview of recent research in 3D video action recognition, concentrating on different deep learning architectures, self-supervised learning, graph-based methods, fewshot and zero-shot learning, cross-modal action understanding, and model interpretability. …”
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Cardiotocogram Data Classification using Random Forest based Machine Learning Algorithm by Molla, M. M. Imran, Jui, Julakha Jahan, Bari, Bifta Sama, Rashid, Mamunur, Hasan, Md Jahid

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Damage identification using experimental modal analysis and adaptive neuro-fuzzy interface system (ANFIS) by Hakim, S.J.S., Razak, H.A.

“…The adaptive neuro-fuzzy inference system (ANFIS) is a process for mapping from a given input to a single output using the fuzzy logic and neuro-adaptive learning algorithms. Using a given input-output data set, ANFIS constructs a Fuzzy Inference System (FIS) whose fuzzy membership function parameters are adjusted using combination of back propagation algorithm with a least square type of method. …”
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Multi-sensor fusion and deep learning framework for automatic human activity detection and health monitoring using motion sensor data / Henry Friday Nweke by Henry Friday , Nweke

“…This is further worsen by the use of single sensors modality and machine learning algorithms. Furthermore, developing robust and efficient methods are required to handle issues such as orientation and position displacement, sensor fusion and feature incompatibility, automatic feature representation, and how to minimize intra-class similarity and inter-class variability. …”
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Human hearing disorder recognition model using eeg-aep based signal by Md Nahidul, Islam

“…This study investigated two conventional machine learning algorithms: support vector machine (SVM) and k-nearest neighbors (KNN), and two deep learning techniques: convolutional neural network (CNN) and improved-VGG16 model. …”
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A cognitive mapping approach in real-time haptic rendering interaction for improved spatial learning ability among autistic people / Kesavan Krishnan by Kesavan , Krishnan

“…Meanwhile, in the past decade, the use of haptic technology in autism has increased in terms of various disciplines that can assist in improving their learning skills. Nevertheless, the use of haptic technology in terms of spatial learning is still not fully utilized, and this weakens autistic people in the process of learning about their surroundings. …”
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Partitional clustering algorithms for highly similar and sparseness y-short tandem repeat data / Ali Seman by Seman, Ali

“…The idea was incorporated into a new algorithm called, k-Approximate Modal Haplotypes (&-AMH) algorithm. …”
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Computer-assisted pterygium screening system: a review by Abdani, Siti Raihanah, Zulkifley, Mohd Asyraf, Shahrimin, Mohamad Ibrani, Zulkifley, Nuraisyah Hani

“…During the early stage of automated pterygium screening system development, conventional machine learning techniques such as support vector machines and artificial neural networks are the de facto algorithms to detect the presence of pterygium tissues. …”
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