Search Results - (( mobile detection system algorithm ) OR ( image classification _ algorithm ))*

Mobile machine vision for railway surveillance system using deep learning algorithm by Kit, Guan Lim, Daniel Siruno, Min, Keng Tan, Chung, Fan Liau, Sha, Huang, Tze, Kenneth Kin Teo

“…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 by Mohd Shah, Hairol Nizam, Ab Rashid, Mohd Zamzuri, Mohd Sobran, Nur Maisarah

“…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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Deep learning detector for pests and plant disease recognition by Ileladewa, Oluwatimilehin Adekunle

“…And developing a quick and accurate model could help in detecting pests and diseases in plants. Meanwhile, evolution in deep convolutional neural networks for image classification has rapidly improved the accuracy of object detection, classification and system recognition. …”
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Mobile Malware Classification via System Calls and Permission for GPS Exploitation by Madihah Mohd Saudi, Husainiamer, MAB

A YOLO-based deep learning model for Real-Time face mask detection via drone surveillance in public spaces by A. Mostafa, Salama, Ravi, Sharran, Zebari, Dilovan Asaad, Zebari, Nechirvan Asaad, Mohammed, Mazin Abed, Nedoma, Jan, Martinek, Radek, Deveci, Muhammet, Ding, Weiping

“…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 by Saari, Mohamad Shahmil, Md Nor, Romiza, Huzaifah, A Hamid

“…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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Cornsense: leaf disease detection application / Iffah Fatinah Mohamad Nasir by Mohamad Nasir, Iffah Fatinah

“…The purpose of this project is to develop a mobile application for corn leaf disease detection leveraging the YOLOv8 (You Only Look Once version 8) object detection algorithm. …”
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Ganoderma boninense disease detection by near-infrared spectroscopy classification: a review by Mas Ira Syafila, Mohd Hilmi Tan, Mohd Faizal, Jamlos, Ahmad Fairuz, Omar, Fatimah, Dzaharudin, Chalermwisutkul, Suramate, Akkaraekthalin, Prayoot

“…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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Automated Vehicle Classification (AVC) using machine learning implementation in Malaysia's toll system by Hassan, Raini, Mohd Ridzal, Aisyah Afiqah, Fadzleey, Nur Zulfah Insyirah

“…Thus, this project aims to develop the best model detector for an automated vehicle classification system using computer vision and machine learning algorithms to enhance toll collection efficiency. …”
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Durian Farm Threats Identification through Convolution Neural Networks and Multimedia Mobile Development by Yusoff, Aiman, Kamarudin, Noraziahtulhidayu, Nabil Ali Al-Emad, Nabil Ali Al-Emad, Sapuan, Khusairi

“…The classification accuracies reached 80% in detecting the animal’s images.…”
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Durian Farm Threats Identification through Convolution Neural Networks and Multimedia Mobile Development by Yusoff, Aiman, Kamarudin, Noraziahtulhidayu, Al-Emad, Nabil Ali, Sapuan, Khusairi

“…The classification accuracies reached 80% in detecting the animal’s images.…”
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Durian Farm Threats Identification through Convolution Neural Networks and Multimedia Mobile Development by Yusof, Aiman, Kamarudin, Noraziahtulhidayu, Al-Emad, Nabil Ali, Sapuan, Khusairi

“…The classification accuracies reached 80% in detecting the animal’s images.…”
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Durian Farm Threats Identification through Convolution Neural Networks and Multimedia Mobile Development by Yusof, Aiman, Kamarudin, Noraziahtulhidayu, Al-Emad, Nabil Ali, Sapuan, Khusairi

“…The classification accuracies reached 80% in detecting the animal’s images.…”
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Durian Farm Threats Identification through Convolution Neural Networks and Multimedia Mobile Development by Yusoff, Aiman, Kamarudin, Noraziahtulhidayu, Al-Emad, Nabil Ali, Sapuan, Khusairi

“…The classification accuracies reached 80% in detecting the animal’s images.…”
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Durian Farm Threats Identification through Convolution Neural Networks and Multimedia Mobile Development by Aiman Yusof, Aiman Yusof, Kamarudin, Noraziahtulhidayu, Nabil Ali Al-Emad, Nabil Ali Al-Emad, Khusairi Sapuan, Khusairi Sapuan

“…The classification accuracies reached 80% in detecting the animal’s images.…”
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Durian Farm Threats Identification through Convolution Neural Networks and Multimedia Mobile Development by Aiman Yusoff, Aiman Yusoff, Noraziahtulhidayu Kamarudin, Noraziahtulhidayu Kamarudin, Nabil Ali Al-Emad, Nabil Ali Al-Emad, Khusairi Sapuan, Khusairi Sapuan

“…The classification accuracies reached 80% in detecting the animal’s images.…”
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Durian Farm Threats Identification through Convolution Neural Networks and Multimedia Mobile Development by Aiman Yusoff, Aiman Yusoff, Noraziahtulhidayu Kamarudin, Noraziahtulhidayu Kamarudin, Nabil Ali Al-Emad, Nabil Ali Al-Emad, Khusairi Sapuan, Khusairi Sapuan

“…The classification accuracies reached 80% in detecting the animal’s images.…”
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Ganoderma boninense disease detection by Near-Infrared Spectroscopy Classification: a review by Mohd Hilmi Tan, Mas Ira Syafila, Jamlos, Mohd Faizal, Omar, Ahmad Fairuz, Dzaharudin, Fatimah, Chalermwisutkul, Suramate, Akkaraekthalin, Prayoot

“…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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Durian Farm Threats Identification through Convolution Neural Networks and Multimedia Mobile Development by Aiman Yusoff, Aiman Yusoff, Noraziahtulhidayu Kamarudin, Noraziahtulhidayu Kamarudin, Nabil Ali Al-Emad, Nabil Ali Al-Emad, Khusairi Sapuan, Khusairi Sapuan

“…The classification accuracies reached 80% in detecting the animal’s images.…”
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A real time deep learning based driver monitoring system by Mohd Hanafi, Mohamad Faris Fitri, Md. Nasir, Mohammad Sukri Faiz, Wani, Sharyar, Abdulghafor, Rawad Abdulkhaleq Abdulmolla, Gulzar, Yonis, Hamid, Yasir

“…Some researchers have focused on developing mobile engines based on machine learning algorithms for detecting driver drowsiness. …”
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