Search Results - (( modal machine learning algorithm ) OR ( java implication based algorithm ))

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

Get full text
Get full text
Get full text
Get full text

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. …”
Get full text
Get full text
Get full text

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

“…Thus, this study will be using the FRF data as the ANN input to identify damage on a running machine. Multilayer Perceptron (MLP) with backpropagation learning algorithm ANN is used in this study. …”
Get full text
Get full text

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

“…In the modeling phase, amongst all DM algorithms, the applicability of machine learning, artificial intelligence and statistical data mining techniques were examined using Support Vector Machine (SVM), Artificial Neural Network (ANN) and Classification and Regression Tree (CART) to detect the hidden patterns in vibration data. …”
Get full text
Get full text
Get full text

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

Get full text
Get full text
Get full text
Get full text

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. …”
Get full text
Get full text

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. …”
Get full text
Get full text

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. …”
Get full text
Get full text

Improving the diagnostic accuracy for major depressive disorder using machine learning algorithms integrating clinical and near-infrared spectroscopy data by Ho, C.S., Chan, Y.L., Tan, T.W., Tay, G.W., Tang, T.B.

Get full text
Get full text

Machine learning or morphometric scaling? a systematic review of methodological confounds and the generalizability of sex classification in neuroimaging by Sapuan, Abdul HaliM, Jamaludin, Iqbal, Abdul Majid, Zafri Azran, Mohd Tamrin, Mohd Izzuddin, Che Azemin, Mohd Zulfaezal, Turaev, Sherzod

“…We examine how imaging modalities, algorithms, and population strata influence both classification outcomes and biological interpretability. …”
Get full text
Get full text
Get full text

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. …”
Get full text
Get full text

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

“…These sensors are pre-processed and different feature sets such as time domain, frequency domain, wavelet transform are extracted and transform using machine learning algorithm for human activity classification and monitoring. …”
Get full text
Get full text

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. …”
Get full text
Get full text
Get full text

Partitional clustering algorithms for highly similar and sparseness Y-Short Tandem Repeat Data / Ali Seman by Seman, Ali

Get full text
Get full text

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. …”
Get full text
Get full text

A neural network modal decomposition mechanism in predicting network traffic by Shi Jinmei

Get full text
Get full text
Get full text

Machine Learning in Ambient Assisted Living for Enhanced Elderly Healthcare: A Systematic Literature Review by Mir, Aabid A., Khalid, Ahmad S., Musa, Shahrulniza, Fauzi, Mohammad Faizal Ahmad, Razak, Normy N., Tang, Tong Boon

“…Such systems integrate advanced technologies such as machine learning (ML), internet of things (IoT), and sensors to enhance safety and healthcare delivery. …”
Get full text
Get full text

Algorithms for moderating effect of emotional value from a cross-media data fusion perspective: a case study of Chinese dating reality shows by Zhang, Shasha, Dong, Qiming, Yasin, Megat Al Imran, Fang, Ng Chwee

“…During the feature extraction part, different machine-learning models are applied: Bidirectional Encoder Representations from Transformers (BERT) or Enhanced Representation through Knowledge Integration (ERNIE) for text; Convolutional Recurrent Neural Network (CRNN), and Bidirectional Long Short-Term Memory (Bi-LSTM) for audio; and Residual Neural Network (ResNet50) and Inflated 3D Convolutional Network (I3D) for video. …”
Get full text
Get full text

A decomposed streamflow non-gradientbased artificial intelligence forecasting algorithm with factoring in aleatoric and epistemic variables / Wei Yaxing by Wei , Yaxing

“…The dissertation aims to develop an effectively decomposed time-series nongradient- based artificial intelligence model for forecasting a time-series regression machine learning task. Real-world optimizations, such as forecasting streamflow, are a complicated process that is highly non-linear and multi-modal, demanding the use of a suitable modeling tool, with an emphasis on artificial intelligence algorithms, to get befitting forecast results. …”
Get full text
Get full text
Get full text

The implications for ahybrid detection technique against malicious sqlattacks on web applications by Bahjat Arif, Sarajaldeen Akram, Wani, Sharyar

Get full text
Get full text
Get full text