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8th International Conference on Informatics and Computing, ICIC 2023

作者： Herlawati, Herlawati Handayanto, Rahmadya Trias Heryadi, Yaya Abdurachman, Edi Soeparno, Haryono Irwansyah, Edy Miranda, Eka Informatics Universitas Bhayangkara Jakarta Raya Jakarta Indonesia Universitas Islam 45 Computer Engineering Bekasi Indonesia BINUS Graduate Program - Doctor of Computer Science Bina Nusantara University Computer Science Department Jakarta11480 Indonesia Trisakti Institute of Transportation and Logistic Jakarta13410 Indonesia Bina Nusantara University School of Computer Science Computer Science Department Jakarta11480 Indonesia Bina Nusantara University School of Information Systems Information Systems Department Jakarta11480 Indonesia

ISBN: (纸本)9798350342604

computer vision has been used in many areas such as medical, transportation, military, geography, etc. The fast development of sensor devices inside camera and satellite provides not only red-greed-blue (RGB) images but also multispectral dataset with some channels including RGB, infrared, short-wave, and thermal wave. Most of the dataset is panchromatic (black and white) and RGB, for example Google Map and other satellite-based map applications. This study examines the effects of multispectral dataset for semantic segmentation of land cover. The comparison between RGB with band 2 to band 7 of Landsat 8 Satellite shows an improvement of accuracy from 90.283 to 94.473 for U-Net and from 91.76 to 95.183 for DeepLabV3+. In addition, this research also compares two well-known semantic segmentation methods, namely U-Net and DeepLabV3+, that shown that DeepLabV3+ outperformed U-Net regarding to speed and accuracy. Testing was conducted in the Karawang Regency area, West Java, Indonesia. © 2023 IEEE.

关键词： Landsat

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Acquiring Automation and Control Data in The Manufacturing Industry: A Systematic Review 8

Acquiring Automation and Control Data in The Manufacturing I...

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8th International Conference on computer science and Computational Intelligence, ICCSCI 2023

作者： Sama, Andi Warnars, Harco Leslie Hendric Spits Prabowo, Harjanto Meyliana Hidayanto, Achmad Nizar Computer Science Department Binus Graduate Program Bina Nusantara University Jakarta11480 Indonesia Management Department BINUS Business School Undergraduate Program Bina Nusantara University Jakarta11480 Indonesia Information System Department School of Information System Bina Nusantara University Jakarta11480 Indonesia Faculty of Computer Science Universitas Indonesia Depok16424 Indonesia

Industry 4.0 has driven the need for Information technology (IT) & Operational technology (OT) convergence to modernize OT by leveraging IT. The challenges for manufacturing operations are utilizing and converting years of scattered data into valuable information integrated into the company's digital transformation strategy. This paper aims to provide a systematic literature review of current evidence in digital transformation for acquiring automation & control technologies data in manufacturing operations, such as programmable Logic Controller (PLC), Supervisory Control and Data Acquisition (SCADA), Distributed Control System (DCS), and Manufacturing Execution System (MES), for analytics purposes and identify the current trends and best practices in this area. The findings cover current information on influential researchers, published journals, research trends, industries, industry types, types of analytics applications, methods, and frameworks for acquiring automation & control technologies data from the legacy OT infrastructure. © 2023 The Authors. Published by Elsevier B.V.

关键词： Data Acquisition Industry 4.0 IT/OT convergence Manufacturing MES Operational technology PLC SCADA

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Hardware-Accelerated Event-Graph Neural Networks for Low-Latency Time-Series Classification on SoC FPGA 21st

Hardware-Accelerated Event-Graph Neural Networks for Low-La...

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21st International Symposium on Applied Reconfigurable Computing, ARC 2025

作者： Nakano, Hiroshi Blachut, Krzysztof Jeziorek, Kamil Wzorek, Piotr Dampfhoffer, Manon Mesquida, Thomas Nishi, Hiroaki Kryjak, Tomasz Dalgaty, Thomas Graduate School of Science and Technology Keio University Tokyo Japan Embedded Vision Systems Group Computer Vision Laboratory AGH University of Krakow Krakow Poland CEA-List Université Grenoble Alpes Grenoble France

ISBN: (纸本)9783031879944

As the quantities of data recorded by embedded edge sensors grow, so too does the need for intelligent local processing. Such data often comes in the form of time-series signals, based on which real-time predictions can be made locally using an AI model. However, a hardware-software approach capable of making low-latency predictions with low power consumption is required. In this paper, we present a hardware implementation of an event-graph neural network for time-series classification. We leverage an artificial cochlea model to convert the input time-series signals into a sparse event-data format that allows the event-graph to drastically reduce the number of calculations relative to other AI methods. We implemented the design on a SoC FPGA and applied it to the real-time processing of the Spiking Heidelberg Digits (SHD) dataset to benchmark our approach against competitive solutions. Our method achieves a floating-point accuracy of 92.7% on the SHD dataset for the base model, which is only 2.4% and 2% less than the state-of-the-art models with over 10× and 67× fewer model parameters, respectively. It also outperforms FPGA-based spiking neural network implementations by 19.3% and 4.5%, achieving 92.3% accuracy for the quantised model while using fewer computational resources and reducing latency. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： event-based audio processing FPGA graph convolutional neural networks dynamic audio sensor artificial cochlea

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Preliminary Evaluation of Kyokko for Inter-FPGA Communication Framework CIRCUS

Preliminary Evaluation of Kyokko for Inter-FPGA Communicatio...

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IEEE International Conference on Cluster Computing Workshops and Posters (CLUSTER WORKSHOPS)

作者： Kaito Kitazume Norihisa Fujita Ryohei Kobayashi Taisuke Boku Master's Program in Computer Science Degree Programs in Systems and Information Engineering Graduate School of Science and Technology University of Tsukuba Center for Computational Sciences University of Tsukuba

In recent years, Field-programmable Gate Arrays (FPGAs) are gaining attention as computational acceleration devices in the field of high-performance computing. By implementing specialized circuits that can be customiz... 详细信息

ISBN: (数字)9798350383454

ISBN: (纸本)9798350383461

关键词： Conferences High performance computing Circuits Cluster computing Low latency communication Field programmable gate arrays

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The Effect of Bitrate Control Methods of MPEG-DASH Streaming on Multi-View Video and Audio QoE

The Effect of Bitrate Control Methods of MPEG-DASH Streaming...

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IEEE International Conference on Consumer Electronics-Taiwan (ICCE-TW)

作者： Toshiro Nunome Yamato Wakayama Department of Engineering Graduate School of Engineering Computer Science Program Nagoya Institute of Technology Nagoya Japan

This paper investigates the effect of bitrate control methods on QoE of multi-view video and audio streaming with MPEG-DASH. We adopt three bitrate control methods for conventional single-view video streaming to the MVV-A system with MPEG-DASH. We conduct a subjective experiment changing available network bandwidth and investigate the effect of the methods on QoE.

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Image Segmentation of Lesions in Wireless Capsule Endoscopy Based on Mask R-CNN

Image Segmentation of Lesions in Wireless Capsule Endoscopy ...

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2021 International Conference on Applied Mathematics, Modeling and computer Simulation, AMMCS 2021

作者： Li, Nianfeng Zhao, Nan Xiao, Zhiguo Lu, Jia College of Computer Science and Technology Changchun University China Graduate School of Changchun University Changchun University China

ISBN: (纸本)9781643682549

The wireless capsule endoscope can comprehensively inspect the digestive tract. It has the advantages of safety, painlessness, and no postoperative reaction, but it has some disadvantages. When the most critical issue is, the entire inspection process is very time-consuming. Using image segmentation technology, the digestive tract lesion tissue and surrounding areas can be locally enhanced, and the Region of Interest (ROI) can be segmented, which is helpful for the doctor to read the image. Based on the Mask R-CNN network, this paper proposes a wireless capsule endoscope lesion image segmentation method. Experimental results show that this method can achieve effective segmentation of the capsule lens lesion image. © 2022 The authors and IOS Press.

关键词： Image segmentation

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Evaluation of REAL-ESRGAN Using Different Types of Image Degradation

Evaluation of REAL-ESRGAN Using Different Types of Image Deg...

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International Conference on ICT For Smart Society (ICISS)

作者： Kus Andriadi Muhammad Zarlis Yaya Heryadi Andry Chowanda Computer Science Department Binus Graduate Program Bina Nusantara University Jakarta Indonesia Information System Management Department BINUS Graduate Program Bina Nusantara University Jakarta Indonesia Computer Science Department School of Computer Science BINUS University Jakarta Indonesia

ISBN: (数字)9798350389654

ISBN: (纸本)9798350389661

This study evaluates the performance of the REAL-ESRGAN [1] model on images with varying levels of degradation using the DIV2K dataset [2], such as the Wild, the Mild, the Difficult, and the x8 subsets. REAL-ESRGAN was created to solve super-resolution problems and aims to produce high-resolution images from low-resolution images. Experiments were conducted at scales of x2 and x4, and performance was measured using Full-Reference metrics (LPIPS, PSNR, SSIM) and No-Reference metrics (NIQE, MANIQA, CLIPIQA, and PI). The Results were good, especially with the x2 scale; it has higher PSNR and SSIM scores, lower LPIPS and NIQE values, and enhanced visual and perceptual quality. The model faced more significant challenges with the wild and the difficult datasets because they have more complex degradations and compression artifacts; it can be seen with unstable results of Full-Reference and No-Reference metrics. On the contrary, the Mild and x8 datasets yielded better results in both metrics; not only that, even the computational cost for Mild and x8 outperforms the rest of the dataset. This study shows the strengths and limitations of REAL-ESRGAN in handling different levels of image degradation. For future research, the model needs enhancement to tackle the degradation format of the wild and the difficult dataset. It would be good if the REAL-ESRGAN improvement could also maintain the computational cost.

关键词： Degradation Measurement Visualization Computational modeling Superresolution Computational efficiency Image reconstruction

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Demonstration of video conferencing tool with overlay network protocol 19

Demonstration of video conferencing tool with overlay networ...

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19th IEEE Annual Consumer Communications and Networking Conference, CCNC 2022

作者： Yoshikawa, Taiki Komura, Hijiri Goto, Ren Matama, Kazushige Nishiwaki, Chihiro Naito, Katsuhiro Aichi Institute of Technology Graduate School of Business Administration and Computer Science Aichi Nagoya Japan Aichi Institute of Technology Faculty of Information Science Aichi Toyota Japan

ISBN: (纸本)9781665431620

Since the current Internet has accessibility issues due to Network Address Port Translation (NAPT) and different IP protocol versions, recent service such as video conferencing also uses a client-server model even if the service model is peer-to-peer. The authors have developed an overlay network protocol to realize peer-to-peer communication because of the lack of the enough implementation for peer-to-peer protocol tackling the accessibility issues. This paper have updated the implementation to support scalability and performance of the proposed protocol. The feature of the proposed protocol provides seamless connectivity over the Internet for any applications. This paper demonstrates the multi-point video conferencing service with the proposed protocol. The service can be available on the Internet even if it only supports local area communication because the proposed protocol virtually connects the conference service. The demonstration also shows the actual signaling process of the proposed protocol to realize the overlay network. Since the proposed system does not relay the communication data at the cloud, the service has high scalability with distributed peer-to-peer communication. © 2022 IEEE.

关键词： Overlay networks

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Text2Avatar: Text to 3d Human Avatar Generation with Codebook-Driven Body Controllable Attribute

Text2Avatar: Text to 3d Human Avatar Generation with Codeboo...

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International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： Chaoqun Gong Yuqin Dai Ronghui Li Achun Bao Jun Li Jian Yang Yachao Zhang Xiu Li Shenzhen International Graduate School Tsinghua University China School of Computer Science and Engineering Nanjing University of Science and Technology China

Generating 3D human models directly from text helps reduce the cost and time of character modeling. However, achieving multi-attribute controllable and realistic 3D human avatar generation is still challenging due to feature coupling and the scarcity of realistic 3D human avatar datasets. To address these issues, we propose Text2Avatar, which can generate realistic-style 3D avatars based on the coupled text prompts. Text2Avatar leverages a discrete codebook as an intermediate feature to establish a connection between text and avatars, enabling the disentanglement of features. Furthermore, to alleviate the scarcity of realistic style 3D human avatar data, we utilize a pre-trained unconditional 3D human avatar generation model to obtain a large amount of 3D avatar pseudo data, which allows Text2Avatar to achieve realistic style generation. Experimental results demonstrate that our method can generate realistic 3D avatars from coupled textual data, which is challenging for other existing methods in this field.

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XLS-R Deep Learning Model for Multilingual ASR on Low- Resource Languages: Indonesian, Javanese, and Sundanese

arXiv

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arXiv 2024年

作者： Arisaputra, Panji Handoyo, Alif Tri Zahra, Amalia Computer Science Department School of Computer Science Bina Nusantara University Jakarta11480 Indonesia Computer Science Department BINUS Graduate Program Bina Nusantara University Jakarta11480 Indonesia

This research paper focuses on the development and evaluation of Automatic Speech Recognition (ASR) technology using the XLS-R 300m model. The study aims to improve ASR performance in converting spoken language into written text, specifically for Indonesian, Javanese, and Sundanese languages. The paper discusses the testing procedures, datasets used, and methodology employed in training and evaluating the ASR systems. The results show that the XLS-R 300m model achieves competitive Word Error Rate (WER) measurements, with a slight compromise in performance for Javanese and Sundanese languages. The integration of a 5-gram KenLM language model significantly reduces WER and enhances ASR accuracy. The research contributes to the advancement of ASR technology by addressing linguistic diversity and improving performance across various languages. The findings provide insights into optimizing ASR accuracy and applicability for diverse linguistic contexts. © 2024, CC BY-SA.

关键词： Linguistics

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