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检索条件"机构=Department of Robotics Program"

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Automation Lamp Healing Application based on Face Expression Identification System using Convolution Neural Network (CNN)

Automation Lamp Healing Application based on Face Expression...

引用

2023 International Conference on Electrical Engineering and Informatics, ICEEI 2023

作者： Saduki Simangunsong, Devin Onil Mahesh Puji, Muhammad Nurul Astuti, Winda Binus Aso School of Engineering Bina Nusantara University Automotive and Robotics Program Computer Engineering Department Jakarta11480 Indonesia

ISBN: (纸本)9798350381290

The disruption of routines, education, recreation, as well as concerns about family income and health, has left many young people feeling fearful, angry, and worried about their future. In this system, a smart system will be developed that can capture, process, and interpret facial expressions so that a person's emotions can be easily and accurately identified, which is one of the best solutions. The system will use artificial intelligence that has been trained beforehand using suitable datasets. In the processed of developing the system, Face image with the size of 48 x 48 x 1 became the input of the system, processes by Convolution layer using Relu activation function. The activation function used in the output layer is softmax because it is suitable for more than 2 classifications. by applying CNN based on Adam optimization which have result on 98.96% and 70%, for training and testing accuracy, respectively. Furthermore, the system accurately turn-on the healing lamp based on the emotion identified. © 2023 IEEE.

关键词： Face recognition

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Traffic Signs Detection System Using YOLO (You Only Look Once) That Provides Notification 1

Traffic Signs Detection System Using YOLO (You Only Look Onc...

引用

1st International Conference on Smart Mechatronics, ICSMech 2024

作者： Setiawan, Yosua Puji, Muhammad Nurul Astuti, Winda Binus Aso School of Engineering Bina Nusantara University Automotive & Robotics Program Computer Engineering Department Jakarta11480 Indonesia

ISBN: (纸本)9798350368918

Road accidents have become a problem for many road users in many countries. It may affect human daily activity and tasks, potentially influencing productivity and safety. Therefore, reducing road accidents as swiftly and effectively as possible is critical. For this reason, a Traffic signs detection system has been developed in this work to improve road safety. The detection system can detect traffic signs on the road such as traffic lights, speed limits, and no U-turn signs, and then it will provide users with the corresponding text on an LCD and vibration feedback using a motor. Throughout this work, the You Only Look Once (YOLO) algorithm is proposed for detecting traffic signs on the road. Moreover, a camera is used to extract live videos which serve as an input for the Raspberry Pi 4 model B containing custom YOLOv5 and YOLOv8 models. The system then sends the output to an LCD, a vibration motor, and a radio frequency (RF) module as notifications for users. In the end, the performance of the proposed method has been collected and it is found to produce good accuracy within an inconsiderable amount of 1.677 images and 2.263 annotations. Therefore, the accuracy of 0.69 for YOLOv5 and 0.7 for YOLOv8 were obtained from the training and validation process. Furthermore, the system accurately detects the traffic signs on the road. © 2024 IEEE.

关键词： Traffic signs

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Computer Vision-Based Hydroponic Lettuce Contour and Area Recognition System

Computer Vision-Based Hydroponic Lettuce Contour and Area Re...

引用

2023 International Conference on Electrical Engineering and Informatics, ICEEI 2023

作者： Pranowo, Samuel Raymond Sukra, Zener Lie Asy'ari, Muhammad Zacky Paryasto, Marisa Binus Aso School of Engineering Bina Nusantara University Automotive and Robotics Program Computer Engineering Department Jakarta Indonesia Telkom University Computer Engineering Program Electrical Engineering Department Bandung Indonesia

ISBN: (纸本)9798350381290

Agriculture is a vital industry for the people of Indonesia, but there are several obstacles, including limited space in urban areas and inefficient conventional sorting and harvesting methods. Using computer vision to choose hydroponic lettuce that is ready to be harvested and a robotic arm to bring the selected lettuce yields, the produced system aims to solve this problem. The system's computer vision algorithms include color space conversion, intensity transformation, and an algorithm for following borders. This project's research methodology combines a quantitative approach with an experimental approach, which consists of conducting several trials on the built system. Several trials demonstrated that the computer vision software was able to accomplish the specified objectives. The average success rate of the developed computer vision system is 93%, while the average success rate of the robot arm is 85%. © 2023 IEEE.

关键词： Lettuce

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Emotion Recognition Based on Voice Using Combination of Long Short Term Memory (LSTM) and Recurrent Neural Network (RNN) for Automation Music Healing Application 1

引用

International Conference on Innovative Technologies in Intelligent Systems and Industrial Applications, CITISIA 2022

作者： Trisyanto, Daryl Elangi Reynard, Michael Oey, Endra Astuti, Winda Automotive and Robotics Program Computer Engineering Department BINUS ASO School of Engineering Bina Nusantara University Jakarta11480 Indonesia

ISBN: (数字)9783031290787

ISBN: (纸本)9783031290770

Stress has become a problem for many people experience in the world. It can affect in decrease in activity and productivity in daily life. Therefore, it is important to reduce or even heal this stress. One way to do that is by listening to appropriate music. Emotion recognition based on voice intonation has been developed in this work. The system has the ability to recognize the emotion of the speaker then automatically play the appropriate music based on emotion of the speaker. In this work, the combination of Long Short Term Memory (LSTM) and Recurrent Neural Network (RNN) approach for identifying emotion based on voice intonation of the speaker is proposed. The Mel Frequency Cepstral Coefficient (MFCC) is adopted as a feature extraction of the voice, which will used as input to the combination of Long Short Term Memory (LSTM) and Recurrent Neural Network (RNN)-based identifier. The performance of the proposed technique has been investigated, especially for multiclass classification and it is found to produce good accuracy within short duration training time. The accuracy of 99.8% and 62.5%, for training and testing accuracy respectively. Furthermore, the system accurately plays the music based on the emotion identified. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023.

关键词： Long short-term memory

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Vision based people tracking using stereo camera and camshift

Vision based people tracking using stereo camera and camshif...

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6th International Conference on Intelligent robotics and Applications, ICIRA 2013

作者： Park, Kang-Il Park, Chan-Ik Lee, Jangmyung Interdisciplinary Program in Robotics Pusan National University Korea Republic of Department of Electrical Engineering Pusan National University Korea Republic of

ISBN: (纸本)9783642408519

In this paper proposes a visual manipulation method that incorporates computation of 3D object position from characteristic disparity of stereo image. First, we proceed to an image revision work using the calibration. To obtain the characteristic disparity, a set of characteristic points, essential to obtain characteristics like center points or corner points are determined from the CAMShift center of left and right images. By iterative computation and tracking in real time, the algorithm is able to robustly provide accurate 3D position of target objects. © 2013 Springer-Verlag Berlin Heidelberg.

关键词： Calibration

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A robotics engineering M.S. degree

A robotics engineering M.S. degree

引用

2010 ASEE Annual Conference and Exposition

作者： Gennert, Michael Michalson, William Demetriou, Michael Computer Science Department Robotics Engineering Program Worcester Polytechnic Institute United States Worcester Polytechnic Institute United States

There is an increasing demand for creative scientific, engineering, and management talent to meet national needs. We believe that the best way to educate professionals for leadership roles is in a unified multi-disciplinary curriculum. This paper describes one such program, a Master of Science degree in robotics Engineering at Worcester Polytechnic Institute, whose goal is to prepare men and women for technical leadership in the robotics industry and research in robotics. The program, launched in fall 2009, develops competence in electro-mechanical-computational systems and an awareness of management systems. It constitutes a multi-disciplinary effort by faculty in Arts & Sciences (Mathematics and Computer Science), Engineering (Electrical & Computer Engineering and Mechanical Engineering), and Management. The program is organized around a technical coursework core with select science and engineering electives. Technical strength is supplemented by organizational and management principles embodied in context courses in Systems Engineering and Management. The program culminates in individual capstone projects that take the form of a thesis, directed research, or practicum with written report. In all cases, a public oral presentation is required. A B.S./M.S. option allows the program to be completed in a single additional year of work past the Bachelor's degree. By using existing courses where appropriate, we were able to start the program by developing only two new courses, Foundations of robotics and Robot Dynamics, supplemented by special topics, independent study, and other project work. We anticipate adding new courses as the program grows, additional faculty join the program, and as we introduce a Ph.D. in robotics Engineering. Initial response to the program by students and industry has been very positive, and the program shows great promise to contribute significantly to meeting future engineering workforce needs. © American Society for Engineering Education,

关键词： Curricula

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Analysis of Knocking Potential Based on Vibration on a Gasoline Engine for Pertalite and Pertamax Turbo Using Signal Processing Methods 1

引用

International Conference on Innovative Technologies in Intelligent Systems and Industrial Applications, CITISIA 2022

作者： Qadri, Munzir Astuti, Winda Automotive and Robotics Program Computer Engineering Department BINUS ASO School of Engineering Bina Nusantara University Jakarta11480 Indonesia

ISBN: (数字)9783031290787

ISBN: (纸本)9783031290770

Knocking is one of the problems in internal combustion engines with many influencing factors, one of which is the use of fuel octane values that are not in accordance with the recommended use or engine specifications. Knocking can lead to poor performance of an engine and shorten its lifetime. To prevent this from happening, a study was conducted on how the octane rating can affect the knocking of an engine by comparing two types of fuel that have different octane rating levels. The most appropriate signal processing method was also determined to carry out this research. The engine speed was predetermined in each experiment. The achieved results prove that the engine has the potential of knocking to occur when using Pertalite-type fuel, caused by misfires. Signal processing is carried out using the Fast Fourier Transform (FFT) and Low Pass Filter (LPF) methods to obtain clear data. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023.

关键词： Gasoline

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License plate recognition system based on principal component analysis and one-against-one multi-class support vector machine 3

License plate recognition system based on principal componen...

引用

3rd International Conference on Eco Engineering Development, ICEED 2019

作者： Kosasih, Kevin Kristofer Astuti, Winda Oey, Endra Automotive and Robotics Program Computer Engineering Department BINUS ASO School of Engineering Bina Nusantara University Jakarta11480 Indonesia

The license plate number which identifies the original registered place of the vehicle, as well as the usage of each vehicle which belongs to a private entity, a government vehicle, and a commercial vehicle, is identified in this work. Vehicle plate detection by a camera that mounted on parking gate. Detection process starts with collecting data using the camera. This work consists two important parts, namely image processing and classification system, respectively. In the image processing, the plate image capture by the camera is extracted to the feature space which will use as the input to the classification system. The classification system is then will identify the extracted input to the plat recognition identification. The Fast Fourier Transform (FFT) and Support Vector Machine (SVM) are applied as feature extraction technique and classification methods, respectively. The results of the training and testing phase are 80% and 66%, respectively. © 2020 Published under licence by IOP Publishing Ltd.

关键词： Fast Fourier transforms

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A portable workcell design for robotics industry

A portable workcell design for robotics industry

引用

2009 ASEE Annual Conference and Exposition

作者： Padir, Taskin Department of Robotics Engineering Program Worcester Polytechnic Institute United States Department of Electrical and Computer Engineering Lake Superior State University United States

This paper presents how a senior capstone project can be utilized to build partnerships between the academia and several companies representing key industries in modern robotics technology. The project can be described as designing a portable robotic workcell for industry to showcase state-of-the-art equipment and technologies in robotics. The industrial sponsor for this project is Applied Manufacturing Technologies (AMT) located in Orion, Michigan. AMT plans to use the workcell for demonstrating current robotics technology in tradeshows, industrial open houses and/or robotics conferences. In addition, the workcell is to be used as a platform to provide training to engineers working in robotics industry on robot programming, machine vision and systems integration. The small size, flexible design and durability make the workcell appealing to many other applications in robotics engineering. An engineering senior project design team composed of one computer engineer, two electrical engineers and two manufacturing engineering technologists at Lake Superior State University has worked on this project as their capstone design requirement through the 2007-2008 academic year. Lake Superior State University offers ABET accredited programs in computer, electrical and mechanical engineering as well as in manufacturing engineering technology. robotics and automation is a degree option in all majors. The capstone senior design project is an integral part of all the degree programs and provides a real-life experience for the engineering senior students. The two-semester course has been an important tool to introduce students to soft skills such as project management, communications, engineering economics, and engineering ethics. The paper illustrates how a capstone design project can be used to build partnerships in robotics technology. An educational partnership between Lake Superior State University and Applied Manufacturing Technologies has quickly expanded to include many oth

关键词： Engineering education

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Development of Detection Lung Disease Stand Alone System Based on Convolutional Neural Network (CNN) 7

Development of Detection Lung Disease Stand Alone System Bas...

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7th International Conference of Computer and Informatics Engineering, IC2IE 2024

作者： Liewarnata, Edgar Caesar Mariana, Yosica Tan, Sofyan Liawatimena, Suryadiputra Astuti, Winda Bina Nusantara University Binus Aso School of Engineering Automotive and Robotics Program Computer Engineering Department Jakarta11480 Indonesia Bina Nusantara University Binus Aso School of Engineering Product Design Program Industrial Engineering Department Jakarta11480 Indonesia Bina Nusantara University Binus Graduate Program - Master of Computer Science Automotive and Robotics Program Computer Engineering Department Binus Aso School of Engineering Computer Science Department Jakarta11480 Indonesia

ISBN: (纸本)9798331505530

Lung disease, especially Tuberculosis (TBC), placed the highest death rate in Indonesia. Tuberculosis (TB) in Indonesia is ranked second after India. Therefore, it is important to reduce or early detection of the lung disease, to prevent this disease and speed up handling. The system can recognize the disease lung identification, and the system applied as standalone system. In this work, the Convolutional Neural Network (CNN) approach for identifying diseases lung identification is proposed. The Mel Frequency Cepstral Coefficient (MFCC) applied to process the stethoscope sounds which will used as input to the CNN. The performance of the proposed system has been investigated and resulted. The accuracy of 99% and 98%, for training and testing accuracy respectively. Furthermore, the system accurately detects lung diseases identification. © 2024 IEEE.

关键词： Lung cancer

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