Search Results - (( using optimization based algorithm ) OR ( using deep sensor algorithm ))
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Supervised deep learning algorithms for process fault detection and diagnosis under different temporal subsequence length of process data
Published 2025“…Deep learning algorithms were widely used among all the data-driven algorithms. …”
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Deep learning optimisation algorithms for snatch theft detection / Nurul Farhana Mohamad Zamri ...[et al.]
Published 2022“…Learning algorithms related to deep learning use bells and whistles, called hyperparameters. …”
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An Improved Grasshopper Optimization Algorithm Based Echo State Network for Predicting Faults in Airplane Engines
Published 2020“…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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Class binarization with self-adaptive algorithm to improve human activity recognition
Published 2018“…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
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Wifi-based location-independent human activity recognition and localization using deep learning
Published 2024“…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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Development of a smart edge device for fire detection
Published 2023“…This project proposes a smart edge fire detection system that overcomes the limitations of conventional fire warning systems by utilizing deep learning models and edge computing. The system is based on an object detection model for fire detection using the Improved YOLOv5s algorithm, which integrates BiFPN and an additional prediction layer for detecting small targets of fire. …”
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Final Year Project / Dissertation / Thesis -
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Wearable Sensor Feature Fusion for Human Activity Recognition (HAR) : A Proposed Classification Framework
Published 2022“…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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Proceeding -
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Smart object detection using deep learning algorithm and jetson nano for blind people
Published 2021“…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
Published 2019“…This is further worsen by the use of single sensors modality and machine learning algorithms. …”
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Data fusion and multiple classifier systems for human activity detection and health monitoring: Review and open research directions
Published 2019“…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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Internet of Things (IoT) based activity recognition strategies in smart homes: a review
Published 2022“…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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An intelligent risk management framework for monitoring vehicular engine health
Published 2022“…We used machine learning and deep learning algorithms to assess the effectiveness of the risk management system’s decision model. …”
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Simulated Kalman Filter algorithms for solving optimization problems
Published 2019“…The proposed population-based SKF algorithm and the single solution-based SKF algorithm use the scalar model of discrete Kalman filter algorithm as the search strategy to overcome these flaws. …”
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Localized deep extreme learning machines for efficient RGB-D object recognition
Published 2015“…Existing RGB-D object recognition methods either use channel specific handcrafted features, or learn features with deep networks. …”
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Proceeding Paper
