Search Results - (( intelligence deep learning algorithm ) OR ( intelligence based time algorithm ))

Optimize and deploy machine learning algorithms on embedded devices for manufacturing applications by Teoh, Ming Xue

“…In recent studies, we seen developers and researchers proposing solutions on deep learning algorithms like YOLO, EfficientNet, CNN, MobileNet etc. …”
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. …”
Get full text
Get full text
Get full text

Overhead view based person counting using deep learning by Kaw, Chee Zhao

“…Second, the OpenVINO Inference Engine is utilized to optimize the trained models in order to facilitate real-time implementation. Third, the accurate tracking of each detected person is performed using the deep learning based tracking framework, known as DeepSORT. …”
Get full text
Get full text

Analytical Study Of Machine Learning Models For Stock Trading In Malaysian Market by Hazirah Halul

Subjects:

Supervised deep learning algorithms for process fault detection and diagnosis under different temporal subsequence length of process data by Terence Chia Yi Kai, Agus Saptoro, Zulfan Adi Putra, King Hann Lim, Wan Sieng Yeo, Jaka Sunarso

Get full text
Get full text
Get full text

Realization of a Hybrid Locally Connected Extreme Learning Machine with DeepID for Face Verification by Wong S.Y., Yap K.S., Zhai Q., Li X.

Predicting longitudinal dispersion coefficient using ensemble models and optimized multi-layer perceptron models by Gholami M., Ghanbari-Adivi E., Ehteram M., Singh V.P., Najah Ahmed A., Mosavi A., El-Shafie A.

Subjects:

An empirical study of TensorFlow lite performances in Raspberry Pi / Mohamad Harith Mohd Zahid by Mohd Zahid, Mohamad Harith

“…However, this type of learning is highly time-consuming and costly as very complex algorithms are present. …”
Get full text
Get full text

A hybrid deep CNN model for fast class-incremental food classification / Aymen Taher Ahmed al-Ashwal by Aymen Taher , Ahmed al-Ashwal

“…Recent works used deep learning classifiers for food recognition, which does not have enough intelligence to update the increasing number of food classes. …”
Get full text
Get full text
Get full text

Light weight deep learning algorithm for voice call quality of services (Qos) in cellular communication by Ramalingam, Mritha, Sultanuddin, S. J., Nithya, N., Raj, T. F. Michael, Kumar, T. Rajesh, Prasad, S. J. Suji, Al-Ammar, Essam A., Siddique, M. H., Udayakumar, Sridhar

Get full text
Get full text
Get full text

Deep-learning-based detection of missing road lane markings using YOLOv5 algorithm by Sophian, Ali, Azmi, Nur Hanisah, Bawono, Ali Aryo

“…In this work, preliminary study of the implementation of one of the latest deep learning algorithms, i.e. YOLOv5, has been carried out in the detection and classification of missing road lane markings. …”
Get full text
Get full text
Get full text
Get full text

Comparative performance of machine learning algorithms for cryptocurrency forecasting by Hitam, Nor Azizah, Ismail, Amelia Ritahani

“…Methods has been proposed to construct models including machine learning algorithms such as Neural Networks (NN), Support Vector Machines (SVM) and Deep Learning. …”
Get full text
Get full text
Get full text
Get full text

Wearable Sensor Feature Fusion for Human Activity Recognition (HAR) : A Proposed Classification Framework by Norfadzlan, Yusup, Adnan Shahid, Khan, Izzatul Nabila, Sarbini, Nurul Zawiyah, Mohamad

Get full text
Get full text
Get full text

A Reinforced Active Learning Algorithm for Semantic Segmentation in Complex Imaging by Usmani, U.A., Watada, J., Jaafar, J., Aziz, I.A., Roy, A.

“…We propose a new reinforced active learning strategy based on a deep reinforcement learning algorithm. …”
Get full text
Get full text

Intelligent image noise types recognition and denoising system using deep learning / Khaw Hui Ying by Khaw , Hui Ying

“…An ensemble of these algorithms is an intelligent and adaptive solution, producing a clean output, while preserving significant pixel information. …”
Get full text
Get full text
Get full text

Comparative Analysis of Peak Current Prediction based on Random Forest and MLP Neural Network Algorithms by Bhoyar P., Rahman M.S.A., Irfan S.A., Amirulddin U.A.U.

A Novel Hybrid Deep Learning Model Based on Simulated Annealing and Cuckoo Search Algorithms for Automatic Radiomics-Based COVID-19 Diagnosis by Saleh, Basma Jumaa, Omar, Zaid, As’ari, Muhammad Amir, Bhateja, Vikrant, Izhar, Lila Iznita

“…Applied Computational Intelligence and Soft Computing published by John Wiley & Sons Ltd.…”
Get full text
Get full text

Deep learning-based vehicular engine health monitoring system utilising a hybrid convolutional neural network/bidirectional gated recurrent unit by Rahim, Md. Abdur, Rahman, Md Mustafizur, Islam, Md. Shofiqul, Md. Muzahid, Abu Jafar, Rahman, Md. Arafatur, D., Ramasamy

“…This paper introduces a hybrid deep learning-based vehicular engine health monitoring system (VEHMS) decision model using Deep CNN (convolutional neural network)-BiGRU (bi-directional gated recurrent unit). …”
Get full text
Get full text
Get full text
Get full text

Comparing deep learning CNN method with traditional MRI-based hippocampal segmentation and volumetry for early Alzheimer’s disease diagnosis across diverse populations by Ibrahim, Nur Shahidatul Nabila, Suppiah, Subapriya, Ibrahim, Buhari, Mohad Azmi, Nur Hafizah, Seriramulu, Vengkatha Priya, Mohamad, Mazlyfarina, Hanafi, Marsyita, Mohammad Sallehuddin, Hakimah, Omar Sharif, Nurallysha Najwa, Razali, Rizah Mazzuin, Harrun, Noor Harzana

“…Traditional voxel-based morphometry (VBM) used for measuring hippocampal volume can be time-laborious and sensitive to pre-processing errors, thus CNN-based algorithms can minimize the time and reduce human errors. …”
Get full text
Get full text
Get full text

ICS cyber attack detection with ensemble machine learning and DPI using cyber-Kit datasets by Mubarak, Sinil, Habaebi, Mohamed Hadi, Islam, Md. Rafiqul, Khan, Sheroz

“…The processed metadata is normalized for the easiness of algorithm analysis and modelled with machine learning-based latest deep learning ensemble LSTM algorithms for anomaly detection. …”
Get full text
Get full text
Get full text
Get full text
Get full text