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2022 IEEE International Conference on Multimedia and Expo, ICME 2022

作者： Wang, Yixuan Li, Jianing Zhu, Lin Xiang, Xijie Huang, Tiejun Tian, Yonghong School of Electronic and Computer Engineering Peking University China School of Computer Science Peking University China Department of Electrical and Computer Engineering Shanghai Jiao Tong University China Peng Cheng National Laboratory China

ISBN: (数字)9781665485630

ISBN: (纸本)9781665485630

Bio-inspired spike cameras, offering high temporal resolution spike streams, have brought a new perspective to address common challenges (e.g.,high-speed motion blur) in depth estimation tasks. In this paper, we propose a novel problem setting, spike-based stereo depth estimation, which is the first trail that explores an end-to-end network to learn stereo depth estimation with transformers for spike cameras, named Spike-based Stereo Depth Estimation Transformer (SSDEFormer). We first build a hybrid camera platform and provide a new stereo depth estimation dataset (i.e.,PKU-Spike-Stereo) with spatiotemporal synchronized labels. Then, we propose a novel spike representation to effectively exploit spatiotemporal information from spike streams. Finally, a transformer-based network is designed to generate dense depth maps without a fixed-disparity cost volume. Empirically, it shows that our approach is extremely effective on both synthetic and real-world datasets. The results verify that spike cameras can perform robust depth estimation even in cases where conventional cameras and event cameras fail in fast motion scenarios. © 2022 IEEE.

关键词： Cameras

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Enhancing the effectiveness of intelligent tutoring systems using adaptation and cognitive diagnosis modeling 1

Enhancing the effectiveness of intelligent tutoring systems ...

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1st International Conference on Novelties in Intelligent Digital Systems, NIDS 2021

作者： Krouska, Akrivi Troussas, Christos Giannakas, Filippos Sgouropoulou, Cleo Voyiatzis, Ioannis Department of Informatics and Computer Engineering University of West Attica Greece

ISBN: (纸本)9781643682044

This paper presents a novel framework for developing educational hypermedia systems incorporating adaptation techniques and tailored feedback. In particular, the adaptation techniques refers to the content presentation;where the system hides/displays information according to students' knowledge level and learning goals, and to the navigation design;where the system proposes the learning path that is better to be followed based on their profile. Finally, the framework embodies a diagnostic model that analyzes the students' misconceptions and provides tailored feedback and advices on bridging students' knowledge gap. This framework aims to enhance the effectiveness of learning process, increasing student engagement through the adaptive content and navigation and improving student performance through the tailored feedback. © 2021 The authors and IOS Press.

关键词： Students

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The method of dynamic routing in Self-healing Networks 5

The method of dynamic routing in Self-healing Networks

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5th IEEE KhPI Week on Advanced Technology, KhPIWeek 2024

作者： Anna, Shyman Kuchuk, Nina Kovalenko, Andriy Kashkevich, Svitlana Partyka, Stanislav Yankovskyi, Oleksandr Department of Computer Engineering and Programming National Technical University Kharkiv Polytechnic Institute" Kharkiv Ukraine Department of Electronic Computers Kharkiv National University of Radio Electronics Kharkiv Ukraine Department of Computerized Management Systems National Aviation University Kyiv Ukraine

ISBN: (纸本)9798350384499

The report proposes a dynamic routing method for Self-healing Networks (ShN). The method takes into account the specific features of ShN. During routing, the flow of service information is reduced. The search for the optimal route is carried out using a convolutional neural network. The method significantly outperforms existing methods when some network nodes fail. ©2024 IEEE.

关键词： Dynamic routing algorithms

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Cost-Effective HWIL testing methodology for SALS guided missiles

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Materials Today: Proceedings 2022年 62卷 2509-2515页

作者： Todi, Ivana Kuzmanovi, Vladimir University of Belgrade Faculty of Mechanical Engineering Weapon Systems Department Kraljice Marije 16 Belgrade 11120 Serbia University of Belgrade Faculty of Mathematics Department for Computer Science and Informatics Studentski Trg 16 Belgrade 11000 Serbia

Verifying a new missile design requires a series of successful real-life tests on a firing range in various scenarios. Such an approach is extremely expensive and requires complex infrastructure and logistics. The costs of developing a new missile design can be significantly reduced by applying extensive and well thought out laboratory testing prior to any real-life test. Laboratory tests such as Hardware-In-The-Loop (HWIL) simulation enable the missile to be tested in a controlled environment inside a laboratory. HWIL testing methodology enables engineers to test the missile or its components in various simulated scenarios that correspond to real-life flights. Usually, a five-axis motion platform is used to perform HWIL simulation of terminal guidance. Three inner axes of the five-axis motion platform are used for simulation of the missiles body angles, while the two outer axes are used for simulation of the target movement relative to the missile. Such an approach requires spacious laboratories and expensive equipment. In this paper, we present a cost-effective HWIL testing methodology for Semi-Active-Laser-Seeker (SALS) guided missiles. The presented methodology requires only a three-axis motion platform and a fixed laser source. In the paper, we propose a two-stage HWIL testing procedure. In the first stage, the INS algorithm, guidance algorithm and autopilot algorithms are verified. In the second stage of the proposed HWIL testing methodology, the terminal guidance algorithm based on SALS angles is verified. Besides the HWIL testing methodology, we present the guidance law used in the testing procedure as well as the design of intercommunication between all the devices required to perform the tests. Next, the obtained results after each stage of the proposed HWIL testing methodology are presented and analyzed. Finally, a conclusion is drawn and limitations of the proposed testing methodology are explained. © 2020

关键词： Embedded systems

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Facial Expression Recognition with Manifold Learning and Graph Convolutional Network 1

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2nd International Conference on Pan-African Intelligence and Smart Systems, PAAISS 2022

作者： Ekundayo, Olufisayo Viriri, Serestina Heymann, Reolyn School of Mathematics Statistics and Computer Science University of KwaZulu-Natal Durban South Africa Department of Electrical and Electronic Engineering Science University of Johannesburg Johannesburg South Africa

ISBN: (数字)9783031252716

ISBN: (纸本)9783031252709

Facial Expression Recognition (FER) has the ability to detect human affect state. Most of the methods employed for FER task do not really consider the correlation among FER data labels to resolve data annotation and ambiguity problems. Label Distribution Learning (LDL) application to FER considerably address this, but only in the presence of data with distribution labels. Therefore, methods that would recover label distribution from logical labels are required. This work is presenting a graph-based label enhancement approach with manifold learning and Graph Convolutional Network (GCN) for facial expression recognition. The manifold learning approach transforms FER data as a graphical problem, where the data points are considered as nearest neighbours represent graph nodes, with the motive of representing the distances along the edges of the neighbouring graph with the approximate distances along the manifold. This process uses the nearest neighbour graph to learn the geometric structure in FER data, which also learn the possible correlation among the data labels. The graphical convolutional network is employed to incorporate the information provided in the manifold learning and the logical description of the data to classify the nodes of the graph using the information of the nearest neighbours. The experiment conducted on the Binghampton University-3D Facial Expression (BU-3DFE) and the Cohn Kanade extension (CK+) data shows that the model gives promising results. © 2023, ICST Institute for computer Sciences, Social informatics and Telecommunications engineering.

关键词： Convolution

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Image Acquisition and Deep Convolutional Neural Network Incorporated Cost-Effective Automated Nursery Disease Detection Method for the Tea Industry 10

Image Acquisition and Deep Convolutional Neural Network Inco...

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10th International Multidisciplinary engineering Research Conference on Moratuwa engineering Research, MERCon 2024

作者： Weerasekara, Dinithi Bhagya Kahatapitiya, Nipun Shantha Sanjeewa, Nuwan Wathudura, Vimukthi Madushan Prasanna, Nuwan Kalupahana, Deshan Wijenayake, Udaya Silva, Bhagya Nathali Wijethunge, Akila Wijesinghe, Ruchire Eranga University of Sri Jayewardenepura Faculty of Technology Department of Materials and Mechanical Technology Pitipana Sri Lanka University of Sri Jayewardenepura Faculty of Engineering Department of Computer Engineering Nugegoda Sri Lanka IOT Solutions Pvt Ltd Homagama Sri Lanka Sri Lanka Institute of Information Technology Faculty of Computing Department of Information Technology Malabe Sri Lanka Malabe Sri Lanka Sri Lanka Institute of Information Technology Faculty of Engineering Department of Electrical and Electronic Engineering Malabe Sri Lanka

ISBN: (纸本)9798331529048

Tea cultivation, a globally significant industry across over 60 countries, requires effective management of tea nurseries for robust plant growth and disease control. Implementing automated disease detection in tea nurseries using advanced technologies enhances efficiency, precision, and sustainability compared to manual inspection methods. An image acquisition system incorporating a Deep Convolutional Neural Network (DCNN) was developed as a cost-effective automated solution for nursery disease detection. First, images of Blister Blight (BB) disease in tea plants were collected primarily from various estates. These images were then preprocessed, labeled, and augmented to create a robust dataset. Two models based on the YOLOv5 architecture were trained, with the second model benefiting from dataset augmentation and enhanced labeling. The Improved Model achieved a mean Average Precision (mAP) of 80.6% at a 0.5 threshold, demonstrating its high accuracy in BB detection in tea nurseries. It was integrated with the image acquisition system to enable continuous monitoring of tea leaves in nursery plantations and facilitate the immediate detection of BB diseases. This system holds significant potential for further enhancement in disease management across the tea industry, promoting healthier crops, reducing costs, and minimizing environmental impact. © 2024 IEEE.

关键词： Convolutional neural networks

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Two-step registration of rigid and non-rigid MR-iUS for brain shift compensation using transfer learning

Two-step registration of rigid and non-rigid MR-iUS for brai...

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International Symposium on Artificial Intelligence and Signal Processing (AISP)

作者： Amir Hossein Jalalzadeh Seyed Saeid Talebi Mehrdad Hashemi Kamangar Department of Biomedical Engineering Engineering faculty Shahed University Tehran Iran Department of Electrical and Computer Engineering Noshirvani University Babol Iran Department of Electrical and Electronic Engineering Engineering Faculty Shomal University Amol Iran

Accurate removal of brain tumors is always one of the most important challenges for surgeons, as the continuous change of the brain state after opening the skull and releasing the resulting pressure causes the tumor state to change. By registration of preoperative MR images on intraoperative ultrasound images, the extent of this change is estimated and a new image of the brain is created. The result shows the changes and shifts in the brain, and the surgeon removes the tumor based on this image. Image registration using new deep learning methods has attracted the attention of many researchers due to its high efficiency and accuracy. In this paper, the images of 22 male and female patients with grade 2 glioma tumors were used to evaluate the proposed method. MR images of the patients were taken before surgery, while ultrasound images were taken during surgery and after cranial incision. The deep network used in this paper to compensate for non-rigid changes is voxel morph. All images were fed to the pre-trained network in pairs, and the results are reported for each individual. The average error of all images for the proposed method is 3.56 ± 1.72. This shows the improvement in performance compared to the previous methods since in this work the landmarks were not used in training phase.

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Sentiment Analysis of Chinese Online Course Reviews by Combining Prompt Learning and Contrastive Learning 4

Sentiment Analysis of Chinese Online Course Reviews by Combi...

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4th International Conference on Information Science and Education, ICISE-IE 2023

作者： Xu, Kai He, Junfei School of Computer Engineering Guilin University of Electronic Technology Beihai China Chengdu Cloud Power Technology Co. Ltd Department Research and Development Chengdu China

ISBN: (纸本)9798350394610

The study of sentiment analysis of Chinese online course reviews can provide an in-depth understanding of students' learning attitudes and needs, optimize the teaching mode, and thereby improve the quality of teaching. To this end, this research proposes a sentiment analysis method for Chinese online course reviews, which combines prompt learning and contrast learning. First, a question and answer prompt template for the large-scale language model ELECTRA is constructed to guide ELECTRA to learn the semantic information contained in the Chinese online course review text. Then, contrastive learning is used to further enhance the data samples and learn feature representations. Finally, the feature representation trained by contrastive learning is input into the sparse Softmax function to perform sentiment polarity classification of Chinese online course reviews. The experimental results on real Chinese online course data sets show that the macro F1 value of the proposed model reaches more than 85% on the three data sets. © 2023 IEEE.

关键词： Sentiment analysis

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A CPW-Fed Printed Ultra Wideband Antenna 12

A CPW-Fed Printed Ultra Wideband Antenna

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12th IEEE-APS Topical Conference on Antennas and Propagation in Wireless Communications, APWC 2023

作者： Li, Kexin Ortiz-Fuentes, Jesus- Antonio Kelly, James Segovia-Vargas, Daniel School of Electronic Engineering and Computer Science Queen Mary University of London London United Kingdom Carlos Iii University of Madrid Signal Theroy Department Madrid Spain

ISBN: (纸本)9798350320602

An ultra-wideband (UWB) antenna is presented in this paper. The UWB antenna consists of a rectangular monopole with a convex arc-shaped edge and a coplanar waveguide (CPW) feed line. This antenna can provide a relatively broad 10 dB return loss bandwidth of 9.8 GHz, from 2.2 GHz to 12 GHz. This band covers the requirements of the Federal Communication Commission (FCC) UWB band. © 2023 IEEE.

关键词： Microstrip antennas

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SparkReact: A Novel and User-friendly Graphical Interface for the Apache Spark MLlib Library 26

SparkReact: A Novel and User-friendly Graphical Interface fo...

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26th Pan-Hellenic Conference on informatics, PCI 2022

作者： Karras, Aristeidis Karras, Christos Bompotas, Agorakis Bouras, Panagiotis Theodorakopoulos, Leonidas Sioutas, Spyros Department of Computer Engineering and Informatics University of Patras Rion Patras Greece Department of Management Science and Technology University of Patras Koukouli Patras Greece

ISBN: (纸本)9781450398541

Visualization is a critical component across every software as it enables users to familiarize themselves with the environment and perform certain tasks with ease. Therefore, straightforward yet interactive and easy-to-understand tools let users' complex demands be satisfied within minutes. The objective of this work is to give an optimized graphical user interface for the Apache Spark MLlib library to apply machine learning algorithms quickly, conveniently, and effectively. We introduce SparkReact, a responsive graphical user interface that allows users to apply clustering, classification, and regression techniques within just a few mouse clicks by implementing and evaluating a certain algorithm and pre-building the code ready for import to Spark. To evaluate the usefulness of our tool we performed crowdsourcing to two categories, computer experts and ordinary users. The results indicate that both populations were satisfied with the tool at a surprising 98 percent. As per the time required to construct and evaluate a machine learning model, it took approximately 4 minutes using SparkReact while with ordinary methods it took almost 4 times longer. Ultimately, future extensions will seek to provide more algorithmic choices. © 2022 ACM.

关键词： Graphical user interfaces

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