Search Results - (( mobile detection system algorithm ) OR ( image classification based algorithm ))*
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Mobile machine vision for railway surveillance system using deep learning algorithm
Published 2021“…In order to overcome this issue, machine vision embedded with deep learning algorithm can be implemented. Obstacle detection can be achieved through vision-based object detection, where the object classification model computes the images similarity to its respective classes, classifying its potential as an obstacle. …”
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AUTONOMOUS MOBILE ROBOT VISION BASED SYSTEM: HUMAN DETECTION BY COLOR
Published 2013“…There have two part are involve which is mobile robot platform and classification algorithms by color. The core of the classification of color are comprise into two process; offline and online. …”
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Mobile Malware Classification via System Calls and Permission for GPS Exploitation
Published 2024Article -
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A YOLO-based deep learning model for Real-Time face mask detection via drone surveillance in public spaces
Published 2024“…Addressing these challenges entails an efficient and robust object detection and recognition algorithm. This algorithm can deal with a crowd of multiple faces via a mobile camera carried by a mini drone, and performs realtime video processing. …”
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A web-based image recognition system for detecting harumanis mangoes / Mohamad Shahmil Saari, Romiza Md Nor and Huzaifah A Hamid
Published 2020“…A web-based image recognition system for detecting Harumanis mangoes was developed and known as CamPauh to recognize four classes of mango which are Harumanis, apple mango, other types of mangoes and not mango. …”
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Ganoderma boninense disease detection by near-infrared spectroscopy classification: a review
Published 2021“…Remarkably, (i) spectroscopy techniques are more reliable than other detection techniques such as serological, molecular, biomarker-based sensor and imaging techniques in reactions with organic tissues, (ii) the NIR spectrum is more precise and sensitive to particular diseases, including G. boninense, compared to visible light and (iii) hand-held NIRS for in situ measurement is used to explore the efficacy of an early detection system in real time using ML classifier algorithms and a predictive analytics model. …”
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A real time deep learning based driver monitoring system
Published 2021“…Some researchers have focused on developing mobile engines based on machine learning algorithms for detecting driver drowsiness. …”
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A real time deep learning based driver monitoring system
Published 2019“…Some researchers have focused on developing mobile engines based on machine learning algorithms for detecting driver drowsiness. …”
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Ganoderma boninense disease detection by Near-Infrared Spectroscopy Classification: a review
Published 2021“…Remarkably, (i) spectroscopy techniques are more reliable than other detection techniques such as serological, molecular, biomarker-based sensor and imaging techniques in reactions with organic tissues, (ii) the NIR spectrum is more precise and sensitive to particular diseases, including G. boninense, compared to visible light and (iii) hand-held NIRS for in situ measurement is used to explore the efficacy of an early detection system in real time using ML classifier algorithms and a predictive analytics model. …”
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Computer-assisted pterygium screening system: a review
Published 2022“…Hence, it is important to develop an automated pterygium screening system based on simple imaging modalities such as a mobile phone camera so that it can be assessed by many people. …”
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Feature extraction and selection algorithm based on self adaptive ant colony system for sky image classification
Published 2023“…The performance of FESSIC was evaluated against ten benchmark image classification algorithms and six classifiers on four ground-based sky image datasets. …”
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Daisy species classification based on image using Convolutional Neural Network algorithm / Haris Hidayatullah Khaimuza
Published 2024“…Second objective is to develop the prototype of daisy species classification based on image using CNN algorithm. The last objective is to evaluate the accuracy of CNN model in the daisy species classification based on image. …”
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Improving Classification of Remotely Sensed Data Using Best Band Selection Index and Cluster Labelling Algorithms
Published 2005“…In addition, the best band selected for image classification is not necessarily the best for classification.A Best Band Selection Index (BBSI) algorithm was developed which is capable of selecting the best band combination for image visualization and supervised classification. …”
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Mobile banking Trojan detection using Naive Bayes / Anis Athirah Masmuhallim
Published 2024“…The objectives of this project are to study the requirement of the Naive Bayes algorithm in Mobile Banking Trojan detection, to develop a webbased detection system for Mobile Banking Trojan using Naive Bayes, and to evaluate the performance and accuracy of the Naive Bayes algorithm in the Mobile Banking Trojan detection. …”
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Combining object-based classification and data mining algorithm to classify urban surface materials from worldview-2 satellite image
Published 2014“…In this study, Data Mining was performed using C4.5 algorithm to select the appropriate attributes for object-based classification. …”
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Conference or Workshop Item -
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Laser-induced backscattering imaging for classification of seeded and seedless watermelons
Published 2017“…The LDA and kNN-based algorithms also obtained quite high classification accuracies with all the accuracies above 90%. …”
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Automated feature selection using boruta algorithm to detect mobile malware
Published 2020“…The usage of android system is rapidly growing in mobile devices. Android system might also incur severe different malware dangers and security threats such as infections, root exploit, Trojan, and worms. …”
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Home intruder detection system using machine learning and IoT
Published 2022“…HIDES is developed using the System Development Life Cycle (SDLC) approach. HIDES implements an object detection algorithm; Single-Shot Multibox Detection (SSD) in NVIDIA Jetson Nano to detect intruders through a camera connected to the system. …”
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