Search Results - (( using deep sensor algorithm ) OR ( using optimization method algorithm ))

An Improved Grasshopper Optimization Algorithm Based Echo State Network for Predicting Faults in Airplane Engines by Bala, A., Ismail, I., Ibrahim, R., Sait, S.M., Oliva, D.

“…Hence, in this work, we design an improved Grasshopper Optimization Algorithm (GOA) based ESN. The proposed technique uses a new solution representation with a simplified attraction and repulsion mechanisms to enhance performance. …”
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Wearables-assisted smart health monitoring for sleep quality prediction using optimal deep learning by Hamza, Manar Ahmed, Hassan Abdalla Hashim, Aisha, Alsolai, Hadeel, Gaddah, Abdulbaset, Othman, Mahmoud, Yaseen, Ishfaq, Rizwanullah, Mohammed, Zamani, Abu Sarwar

“…For sleep quality prediction, the WSHMSQP-ODL model uses the deep belief network (DBN) model. To enhance the sleep quality prediction performance of the DBN model, the enhanced seagull optimization (ESGO) algorithm is used for hyperparameter tuning. …”
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Class binarization with self-adaptive algorithm to improve human activity recognition by Zainudin, Muhammad Noorazlan Shah

“…Therefore, feature selection using Relief-f with self-adaptive Differential Evolution (rsaDE) algorithm is proposed to select the most significant features. …”
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3D LiDAR Vehicle Perception and Classification Using 3D Machine Learning Algorithm by Yong, Ericsson, Muhammad Aizzat, Zakaria, Mohamad Heerwan, Peeie, M. Izhar, Ishak

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Wifi-based location-independent human activity recognition and localization using deep learning by Abuhoureyah, Fahd Saad Amed

“…Third, recognizing the capability of location independence, we propose a novel locationindependent HAR using a self-learning CSI-based technique for wireless sensor networks. …”
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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

“…The deep learning model Long-Short Term Memory based Deep Recurrent Neural Network (LSTM-DRNN) will be used to extract deep features. …”
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Smart object detection using deep learning algorithm and jetson nano for blind people by Tan, Mei Yan, Anis Farihan, Mat Raffei, Mohd Arfian, Ismail

“…Therefore, this project develops a smart object detection using deep learning algorithm and jetson nano to improve object detection for blind people. …”
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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. …”
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Deep learning in face recognition for attendance system: an exploratory study / Mochamad Azkal Azkiya Aziz, Shahrinaz Ismail and Noormadinah Allias by Aziz, Mochamad Azkal Azkiya, Ismail, Shahrinaz, Allias, Noormadinah

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Deep learning optimisation algorithms for snatch theft detection / Nurul Farhana Mohamad Zamri ...[et al.] by Mohamad Zamri, Nurul Farhana, Md Tahir, Nooritawati, Megat Ali, Megat Syahirul Amin, Khirul Ashar, Nur Dalila

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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

“…Deep learning algorithms were widely used among all the data-driven algorithms. …”
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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

“…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. …”
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Student attendance system using facial recognition based on deep learning / Syahila Aina Haris and Zulfikri Paidi by Haris, Syahila Aina, Paidi, Zulfikri

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Internet of Things (IoT) based activity recognition strategies in smart homes: a review by Babangida, Lawal, Perumal, Thinagaran, Mustapha, Norwati, Yaakob, Razali

“…Human activity recognition is one of the services provided by this IoT method of data collection from the sensor network when activated by residents. The obtained data can be subjected to extensive preprocessing and feature extraction tasks before being learned using appropriate machine learning or deep learning algorithms to generate a model capable of managing human activities more effectively. …”
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Application of genetic algorithm methods to optimize flowshop sequencing problem by Mohd Fadil, Md Sairi

“…Genetic algorithm method was one of the methods that were widely used in solving optimization problem. …”
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Development of spike train algorithms for physiotherapy assessment using deep learning approaches by Nor Rashid, Fadilla' Atyka

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Sizing optimization of large-scale grid connected photovoltaic system using dolphin echolocation algorithm / Muhammad Zakyizzuddin Rosselan by Rosselan, Muhammad Zakyizzuddin

“…Later, an Iterative-based Sizing Algorithm (ISA) was developed to determine the optimal sizing solution which was later used as benchmark for sizing algorithms using optimization methods. …”
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An improved method using fuzzy system based on hybrid boahs for phishing attack detection by Noor Syahirah, Nordin

“…Moreover, Butterfly Optimization Algorithm and Harmony Search Algorithm were combined as optimization method led to a new method named BOAHS. …”
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An intelligent risk management framework for monitoring vehicular engine health by Rahim, Md. Abdur, Rahman, Md. Arafatur, Rahman, Md. Mustafizur, Zaman, Nafees, Moustafa, Nour, Razzak, Imran

“…We used machine learning and deep learning algorithms to assess the effectiveness of the risk management system’s decision model. …”
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Localized deep extreme learning machines for efficient RGB-D object recognition by Mohd Zaki, Hasan Firdaus, Shafait, Faisal, Mian, Ajmal S.

“…Existing RGB-D object recognition methods either use channel specific handcrafted features, or learn features with deep networks. …”
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