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FLoW-Vision: Object Recognition and Pose Estimation System based on Three-Dimensional (3D) computer Vision 23

FLoW-Vision: Object Recognition and Pose Estimation System b...

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23rd International Electronics Symposium, IES 2021

作者： Putra, Vardyansyah Cahya Pratama Harsetya Apriandy, Kevin Ilham Pramadihanto, Dadet Barakbah, Ali Ridho Dept. of Informatics and Computer Engineering Electronic Engineering Indonesia

ISBN: (纸本)9781665443463

This paper presents a three-dimensional computer vision-based object recognition on FLoW-Vision in RoISC (formerly ER2C) has entered its second phase. Previously, the robot had a basic vision that was used to replicate 'human-like' visual skills using 2D computer vision. As a result of the above discussion, we proposed the design and implementation of an object recognition and pose estimation system based on three-dimensional computer vision to handle object recognition and pose estimation tasks in real-world environments simultaneously. In the object recognition process, a point-cloud segmentation method is used to obtain possible object clusters before starting the calculation of feature description. Then, a keypoints-based two-stage matching process is performed to speed up the computation of finding correspondences between the object clusters of the current scene and a colored point cloud model of an object. Next, a Hough voting algorithm is employed to filter out matching errors in the correspondence set and estimate the initial 3D pose of the object. Last process process the pose estimation from clustered object using RANSAC to search the largest surface as Z surface. Experimental validate the object recognition can work correctly with percentage 100% and pose estimation accuracy of the proposed system can work correctly with percentage 60% in a complex real-world scene. © 2021 IEEE.

关键词： Object detection

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Flood Evacuation Route Recommendation Using Particle Swarm Optimization Algorithm

Flood Evacuation Route Recommendation Using Particle Swarm O...

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2023 International Conference on Information Technology and Computing, ICITCOM 2023

作者： Mahendra, Ricky Haedir, Teuku Muh. Nur, M. Adnan Nur, Nur Khaerat Hazriani Handayani University of Makassar Dept. of Informatics Makassar Indonesia Fajar University Dept. of Civil Engineering Makassar Indonesia Handayani University of Makassar Dept. of Computer System Makassar Indonesia

ISBN: (纸本)9798350359633

Equipping the society with an evacuation route assistant is important as a preventive action in order to minimize anxiety as well as number of victims when disaster strike. Therefore, research on best route determination to the shelter is a noble task. Evacuation routes mean routes to pass in order to reach the gathering point or shelter safely. This study aims to implement the particle swarm optimization (PSO) algorithm in finding the optimal path to the designated shelter. PSO is a metaheuristic algorithm inspired by the behaviour of flocks of birds or fish to optimize the search for the best route. Taking into account the details of the PSO implementation, including initialization of the random particle position and velocity, selection of the best particle (Pbest) and Global Best (Gbest), and updating the speed and position of the particle using the specified formula. The objective function is recalculated based on the total distance of the particle route as well as the condition weight of the affected areas. The results showed that out of ten experiments with 100 iterations, six valid routes were found with the highest fitness value of 1,935, which indicates that PSO can provide optimal solutions in the context of finding flood evacuation routes. © 2023 IEEE.

关键词： Floods

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A Procedure for Optimization of Placement Products in Large Industrial Areas of a Greek Soft Drinks Company

A Procedure for Optimization of Placement Products in Large ...

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International Conference on Applied Mathematics & computer Science (ICAMCS)

作者： Sotirios Tsakiridis Alkiviadis Tsimpiris Athanasios Angeioplastis Nikolaos Papaioannou Paris Mastorocostas Apostolos Papakonstantinou Angeliki Kamilali Dimitrios Varsamis Dept. Computer Informatics and Telecommunications Engineering International Hellenic University Serres Greece Dept. Informatics and Computer Engineering University of West Attica Egaleo Greece Dept Civil Engineering and Geomatics Cyprus University of Technology Lemesos Cyprus

ISBN: (数字)9798350363807

ISBN: (纸本)9798350363814

In this paper we present the process of optimal placement of industrial products (pallets) in mapped ware-houses and specifically in a soft drink company in Greece. The optimization criterion is to minimize the cost of moving the lifting machine that places the products in specific positions. The computational method of optimal placement of industrial products receives data from the automatic product count of the mapped warehouse and from the sales predictive model. Therefore, the computational method, having knowledge of the location and number of products in the warehouse and the prediction of sales for each product, places the products produced in an optimal way. Automatic product counting is carried out using an unmanned aerial vehicle (UAV) which developed and applied in soft drink company in Greece. The sales prediction is carried out through a prediction model which developed in a soft drink company in Greece.

关键词： computer science Costs Computational modeling Area measurement Companies Predictive models Autonomous aerial vehicles Optimization Pallets

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Topic Modeling Using Latent Dirichlet Allocation Method Based On Child Anecdotal Record Data

Topic Modeling Using Latent Dirichlet Allocation Method Base...

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Science and Information Technology in Smart Administration (ICSINTESA), International Conference of

作者： Rasio Fernandis Daniel Swanjaya Risky Aswi Ramadhani Patmi Kasih Julian Sahertian Dept. Informatics Engineering Faculty of Engineering and Computer Science Universitas Nusantara PGRI Kediri Kediri

ISBN: (数字)9798350376111

ISBN: (纸本)9798350376128

Kindergarten education has a very important role in shaping the foundation of child development. For parents, see reports on the achievement of children’s development at school through the results of each semester’s assessment. The process of preparing teacher assessments uses 4 types of assessments, one of which is anecdotal record assessment. However, teachers experience problems in analyzing the topics in children’s anecdotal notes so that the results become less clear. In addition, it is still done manually so it takes a long time to analyze. Assessment of children’s anecdotal notes is an assessment in the form of a record of events that occur to children while at school. Anecdotal notes are in the form of text data, therefore this research aims to find out the topics in children’s anecdotal notes data by utilizing topic modeling using the Latent Dirichlet Allocation (LDA) method. The children’s anecdotal notes data is used as one dataset with a total of 276 collected directly from YBPK Sidorejo Kindergarten, after which data preprocessing is carried out in the form of case folding, remove punctuation, tokenizing, stopwords, and stemming. In the LDA topic modeling research using the Gensim library, 5 experiments were carried out by determining the number of different iterations, and displaying a range of 2-10 topics for each experiment. Analysis and evaluation using coherence score to determine the optimal number of topics by looking at the highest coherence score value in the experiment conducted. The analysis results in 3 topics with a coherence score of 0.4704 and 40 iterations or passes.

关键词： Analytical models Data preprocessing Education Coherence Libraries Data models Resource management Information technology

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Modeling a balanced commute educational timetabling problem in the context of teaching Integer Programming 7

Modeling a balanced commute educational timetabling problem ...

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7th South-East Europe Design Automation, computer engineering, computer Networks and Social Media Conference, SEEDA-CECNSM 2022

作者： Gogos, Christos Dimitsas, Angelos Valouxis, Christos Alefragis, Panayiotis University of Ioannina Dept. of Informatics and Telecommunications Arta Greece University of Patras Dept. of Electrical and Computer Engineering Rio Greece University of Peloponesse Dept. of Electrical and Computer Engineering Patras Greece

ISBN: (数字)9798350398588

ISBN: (纸本)9798350398588

In this work we present modeling and optimally solving a timetabling problem that was given as a compulsory assignment to students attending an Operations Research course. The project aimed at introducing Integer Programming in a problem that used enrollments of the students themselves to individual courses and aimed at minimizing, in a balanced manner, commute time needed for attending lessons. Students were given a problem that was familiar to them and nontrivial to be solved optimally. In the process, modern commercial and open source Integer Programming solvers were used. More importantly, modeling skills were acquired and the benefits of approaching hard problems using solvers employing exact algorithms was demonstrated. © 2022 IEEE.

关键词： Integer programming

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Leveraging the Pre-Trained Whisper Model and Levenshtein Distance for Audio Buginesse Transcription

Leveraging the Pre-Trained Whisper Model and Levenshtein Dis...

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2024 Beyond Technology Summit on informatics International Conference, BTS-I2C 2024

作者： Mukmin, Amirul Adnan Jalil, Abdul Pallawabonang, Mahabintang Prakasa, Esa Yuyun Handayani University of Makassar Dept. of informatics engineering Makassar Indonesia Handayani University of Makassar Dept. of computer system Makassar Indonesia Research center for data and information science National Research and Innovation Agency Bandung Indonesia

ISBN: (纸本)9798331508579

This research aims to transcribe audio into text using the pre-trained Whisper model, focusing on Bugis, a low-resource language. A key challenge in transcribing local languages like Bugis is the limited availability of language model. To address this, we implemented an algorithmic correction approach that does not require extensive datasets or computationally demanding customizations. The Whisper model provides an initial transcription, serving as a foundation;however, the output often lacks accuracy due to the absence of specific adjustments for Bugis. To enhance accuracy, we applied the Levenshtein distance algorithm to correct word errors by comparing transcription results with entries in a Bugis language dataset based on similarity. Although this method is not fully precise and depends on the completeness of the reference dataset, evaluation results indicate that it effectively lowers the word error rate (WER) and improves transcription accuracy. This research produces SRT files containing transcripts that have been corrected using the Levenhstein distance algorithm, which not only improves accessibility but also contributes to the preservation of Bugis language through digital media. This approach is expected to provide a practical solution to improve transcription accuracy and support more accurate documentation in Bugis language preservation efforts. © 2024 IEEE.

关键词： Speech recognition

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An Intelligent Controller for Demand-Side Management in Residential Electrical Networks

An Intelligent Controller for Demand-Side Management in Resi...

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Panhellenic Conference on Electronics and Telecommunications (PACET)

作者： Gregory Zigirkas John Kalomiros Dept. of Computer Informatics and Telecommunications Engineering International Hellenic University Serres Greece

A novel embedded controller is proposed for the management of electrical consumption in residential installations. The proposed system is designed to implement well-established DSM techniques. It can be placed directly into the electrical board of a residential circuit and can be connected to the smart grid. The controller is based on a PIC microcontroller and incorporates a series of perceptrons which adjust the duty cycle of PWM modules according to user defined preferences. The system is tested in laboratory conditions and is proved to be able to adjust the total current to a predefined threshold, without violating user comfort and priorities. The proposed embedded controller is a flexible solution in the form of a final product, ready for the smart grid and able to support microgrids.

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Cutlery Detection System With Camera and Yolov5

Cutlery Detection System With Camera and Yolov5

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International Electronics Symposium (IES)

作者： Gita Agraini Manullang Setiawardhana Bima Sena Bayu Dewantara Dept. of Informatics and Computer Engineering Politeknik Elektronika Negeri Surabaya Surabaya Indonesia

ISBN: (数字)9798350391992

ISBN: (纸本)9798350392005

The culinary business industry, such as restaurants, heavily relies on consumer experience. One aspect that can affect consumer experience is the service provided by the restaurant in supplying complete dining equipment. Misunderstandings may occur due to the lack of complete dining and drinking utensils in restaurants, leading to complaints from customers or guests. However, manually checking the completeness of dining equipment can be time-consuming and can easily lead to human error. Therefore, it is necessary to develop a system that capable to detect the completeness of dining equipment on restaurant tables. To address this, this research uses cameras and machine learning to build a system that can automatically recognize dining equipment on the dining table. The machine learning model used in this research is YOLOv5. In YOLOv5, two processes occur such as training and testing. The training process is carried out on an annotated dataset to produce a trained model. Then this model is tested in the testing process to evaluate its performance using a separate dataset different from the training dataset. The model run on Google Colab showed an accuracy rate of 90% during training and 93.75% during testing.

关键词： Training YOLO Industries Accuracy Machine learning Cameras Internet

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Evaluation of Pseudorandom Pixel Placement in Enhancing Face Recognition using VGG-Face 5

Evaluation of Pseudorandom Pixel Placement in Enhancing Face...

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5th International Conference on Image, Video Processing, and Artificial Intelligence, IVPAI 2023

作者： Hadis, Muhammad Sabirin Akita, Junichi Toda, Masashi Dept. of Electrical Engineering and Computer Science Kanazawa University Kakuma-machi Ishikawa Kanazawa920-1192 Japan Research and Education Institute for Semiconductors and Informatics Kumamoto University Kumamoto860-8555 Japan

ISBN: (纸本)9781510674660

In efforts to enhance face recognition performance, techniques ranging from super-resolution methods to the use of Local Binary Pattern (LBP) and deep learning have been explored. Among these, the pseudorandom pixel placement (PSE) technique has demonstrated potential in face recognition. Nevertheless, its testing was previously limited to just 8 subjects. This study undertakes a comprehensive evaluation of the PSE technique with a larger sample, utilizing 2000 subjects from the DigiFACE1M dataset and leveraging the state-of-the-art VGG-Face deep learning model. Through experiments involving 10 different PSE patterns on 144.000 face images, our findings indicate that, compared to Regular Pixel Placement (REG), PSE achieved an improvement in average accuracy by 1.05%, reduced the standard deviation by 1.47%, and resulted in 31 additional subjects achieving 100% accuracy. We conclude that PSE consistently outperforms REG in face recognition tasks using the VGG-Face model across the majority of tested scenarios. © 2024 SPIE. All rights reserved.

关键词： Pixels

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Sentiment Analysis of Thesis Policy by Instagram Users Using Logistic Regression

Sentiment Analysis of Thesis Policy by Instagram Users Using...

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International Conference on Electrical engineering, computer Science and informatics (EECSI)

作者： Fathia Dwi Astuti Widodo Bambang Prasetya Adhi Dept. of Informatics and Computer Engineering Education Universitas Negeri Jakarta Jakarta Indonesia

ISBN: (数字)9798350355314

ISBN: (纸本)9798350355321

The requirements for university graduation were changed by the Minister of Education, Culture, Research and Technology in August 2023, where a thesis is no longer required and can be replaced with another form. The existence of this regulation has caused discussion in the community with various responses visible through social media Instagram. Instagram has become a forum for sharing the latest topics for the public, causing the emergence of online media accounts such as Folkative. This research aims to analyze sentiment regarding the policy of eliminating thesis obligations at universities through data collected from comments on Folkative's Instagram account posts. Sentiment analysis was carried out using Logistic Regression for classification, K-Fold Cross Validation for data validation, Confusion Matrix for evaluation, and ADASYN to resolve data imbalances. The data collected from the scraping process was 4,172 comments. After carrying out the classification and performance evaluation process, the best method produced was a combination of Logistic Regression and ADASYN achieving results of 89.6% accuracy, 91.5% precision, 87.7% recall, and f-1 score 89.5%. This shows that the performance of the Logistic Regression method is good and suitable for use as a classification model in this research.

关键词： Support vector machines Performance evaluation Logistic regression Sentiment analysis Accuracy Social networking (online) Media Regulation Web sites Multimedia communication

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