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6 articles for “facial landmark detection”
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Driver’s Safety Technology Using Machine Learning
Abstract: Nowadays, machine learning is mostly used in personalized recommendation systems. The use of machine learning to model the complex user-item interaction function is a trend in the current recommendation domain. This study outlines research carried out in the realm of computer science and engineering to develop a system for detecting driver drowsiness. The main aim is to prevent majority of traffic accidents caused by driver fatigue and drowsiness, fire and …
Published in Journal of Communication Engineering & Systems · Vol. 13, Issue 3, 2023 · pp. 30–37 Read article
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Virtuality Keyboard by AI
Abstract: As everyone knows, computer vision is used to process images in machine learning. Today, for this wonderful task, we are using OpenCV and the cv-zone library in Python. Everyone is familiar with OpenCV, and the cv-zone is essentially a library for hand detection, pose detection, face detection, and other related tasks. By this, we created a keyboard named as “Virtuality Keyboard”. It is just another example of today's computer trend …
Published in Journal of Computer Technology & Applications · Vol. 13, Issue 1, 2022 · pp. 24–36 Read article
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An Experimental Analysis on Enhancement of Electric Vehicle Safety using ADAS Technology and Forward Collision Avoidance with an Automatic Braking System
Abstract: The rapid expansion of the automobile sector in developing nations has intensified road safety concerns, particularly in congested urban environments where human error accounts for approximately 90% of all accidents. This paper presents and experimentally validates an integrated Advanced Driver Assistance System (ADAS) for electric vehicles comprising three complementary safety modules: a Forward Collision Avoidance System (FCAS) employing an HC-SR04 ultrasonic sensor interfaced with an Arduino Uno R3 to detect …
Published in Journal of Automobile Engineering and Applications · Vol. 13, Issue 2, 2026 · pp. 20–30 Read article
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DRIVE-DEFENDER: A Driver Safety-oriented Alcohol and Drowsiness Detection System
Abstract: DRIVE-DEFENDER presents a pioneering approach in driver safety through the development of a real-time machine learning system for alcohol detection. The detrimental impact of alcohol-impaired driving on road safety necessitates efficient detection mechanisms. Current methodologies are often hindered by their cost, invasiveness, and reliance on specialized sensors. DRIVE-DEFENDER utilizes a camera for recording the face of the driver in real time, employing image processing techniques to identify facial landmarks. These …
Published in Journal of Open Source Developments · Vol. 11, Issue 1, 2024 · pp. 15–26 Read article
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Live Integrated Facial Observation (L.I.F.O.)
Abstract: A human face is the most influential part of humans that can uniquely identify a person. Using all the facial characteristics as biometric, the LIFO system can be applicable in many different ways. Like in everyday life, the most mandatory task in any organization is attendance marking. Earlier, people used to mark their presence using paperwork but now along with the advancement of technology, this system has also changed and …
Published in Journal of Advancements in Robotics Read article
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Driver Drowsiness Detection System
Abstract: One of the main causes of road accidents worldwide in recent years is driver fatigue. Assessing a driver's mood, or how sleepy they are, is a clear approach to gauge their level of exhaustion. Therefore, detecting driver fatigue is very important to save lives and property. The creation of a prototype drowsiness detection system is the aim of this research. The system operates in real time, continuously capturing images and …
Published in International Journal of Optical Innovations & Research · Vol. 3, Issue 2, 2025 · pp. 16–21 Read article