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Research on the Path of Artificial intelligence technology to Improve Students' Learning Effect 3

Research on the Path of Artificial Intelligence Technology t...

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3rd international conference on Education, Knowledge and Information Management, ICEKIM 2022

作者： Wang, Yaorong Tianjin University School of Education Tianjin China

ISBN: (纸本)9781665416665

With the continuous development of big data and artificial intelligence, big data and intelligence in the traditional field will be inevitable. At present, the combination of artificial intelligence and the education industry is becoming a hot spot in artificial intelligence applications. This research explores the research hotspots of artificial intelligence in education, using Bloom's educational goal classification method to divide learning effects into cognitive learning effects, emotional learning effects, and skill-behavior learning effects, and analyze the effects of artificial intelligence on student learning. Through the in-depth integration of artificial intelligence and education, cultivate students' human-computer collaboration ability, promote education reform, strengthen the research of artificial intelligence education learning content, and strengthen artificial intelligence theoretical innovation and practical innovation to enhance the learning effect. © 2022 IEEE.

关键词： Big data

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Explainable Encoder-Decoder Crack Segmentation: Convolutional Network Vs. Transformer 3

Explainable Encoder-Decoder Crack Segmentation: Convolutiona...

引用

3rd international conference on Emerging Smart Technologies and applications, eSmarTA 2023

作者： Al-Huda, Zaid Al-Antari, Mugahed A. Peng, Bo Saleh, Radhwan A.A. School of Computing and Artificial Intelligence Southwest Jiaotong University Sichuan China Sejong University Department of Artificial Intelligence Seoul05006 Korea Republic of Kocaeli University Department of Mechatronics Engineering Kocaeli41001 Turkey

ISBN: (纸本)9798350305333

Crack segmentation is a crucial task in various domains, particularly in infrastructure inspection, civil engineering, and road maintenance. To accurately detect various cracks from the input RGB images, two artificial intelligence (AI) approaches have been presented for segmentation purpose: Convolutional Neural Network (CNN) and transformer-based techniques (ViT). In this study, we present a comparative analysis to evaluate the robustness of convolutional networks against ViT. CNNs are built upon a series of convolutional and pooling layers, designed to capture local patterns and features in an image. On the other hand, ViTs utilize self-attention mechanisms to capture global relationships within a sequence of input patches from the image. In addition to quantitative evaluation comparison, qualitative visual explainable heat saliency maps are derived. We use two crack datasets for comparison evaluation purposes: Crack500 and DeepCrack. We compare the evaluation results among six XAI models (three models for each;CNN and ViT). The segmentation results show the commutative measurements among the CNN and ViT models. Such a comprehensive comparison study could be helpful to assist the researchers in the domain for the best model selection. © 2023 IEEE.

关键词： Convolution

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Patrolling robot with Facial Detection 1

引用

3rd international conference on Innovations in Computational intelligence and Computer Vision, ICICV 2022

作者： Golsangi, Mitrajeet Ghuge, Vivek Godse, Divija Harne, Pravin Thopate, Kaushalya Department of Computer Science Vishwakarma Institute of Technology Pune India

ISBN: (数字)9789819926022

ISBN: (纸本)9789819926015

Security of any facility and the people inside it is a huge responsibility of the management of that facility. This, even though it can be achieved using humans, it leaves them at risk and introduces a factor of human error. Thus, the proposed system aims to improve the surveillance and security of a compound, without putting any human lives at risk and naturally removing the human error factor from the process. The paper discusses the implementation of such a system and all the work related to it. The proposed system is a fully functional robot which can follow the direction of a sound. It also has an on board camera which sends live footage of everything to a server. This feed is then processed for detection of a face and it is displayed to the user. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023.

关键词： Face recognition

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Fingerprint Identification using Ridge Lines 3

Fingerprint Identification using Ridge Lines

引用

3rd international conference on Computer Vision, Image and Deep Learning and international conference on Computer Engineering and applications, CVIDL and ICCEA 2022

作者： Liu, Ziqi Niu, Yucheng Qu, Qianhou University of Sheffield Department of Information Management Sheffield United Kingdom University of Delaware Department of Engineering NewarkDE19711 United States Hebei University of Technology Department of Artificial Intelligence and Data Science Tianjin300000 China

ISBN: (纸本)9781665459112

This design is based on MATLAB fingerprint identification system. This designed system mainly carries of three consisting of fingerprint image processing, image preprocessing, feature extraction, and feature matching. Image preprocessing includes four steps: image graying, filtering enhancement, binarization, and refinement. After the fingerprint image is preprocessed, the redundant part of the original image is removed, which is convenient for subsequent recognition processing. Feature extraction is mainly to extract the endpoints and bifurcation points of the fingerprint image after refinement. Feature matching is to compare the feature points of two fingerprint images to determine whether the two images are from the same finger. Experiments on real datasets validate the effectiveness of our method. © 2022 IEEE.

关键词： Feature extraction

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Development of a low-cost active 3D triangulation laser scanner of intelligent mobile robot for transferring button weight

Development of a low-cost active 3D triangulation laser scan...

引用

2024 conference on Spectral technology and applications, CSTA 2024

作者： Wu, Weixin Yuan, Jing Yu, Qinghua Yu, Yanxi Dong, Guangxian Chongqing Academy of Metrology and Quality Inspection Chongqing401121 China China Satellite Maritime Tracking and Control Department Jiangyin214431 China

ISBN: (纸本)9781510683082

In modern intelligent living, the weight and shape size of a button weight are ones of the crucial fundamental quantities to ensure their conformity to design specifications serving a range of monitoring and management, from flight-weight, expressway inspection, and market transaction to house applications. In this paper, an intelligent mobile robot for transferring button weight was developed based on a low-cost active 3D triangulation laser scanner. An automatic scanning path planning algorithm of 3D profile contour of button weight was proposed. 3D geometric dimensions of button body was also described by identifying the marking graphics. Finally, a series of experiments of several typical button weights have been performed to demonstrate this automated path planning technique and the final intelligence level. Moreover, an commercial 3D intelligent mobile robot was also introduced, which has two degrees of laser scanner and robotic arm. Those scanning paths generation have been proven to be amenable for practical purposes through many tests so that it might be applicable to achieve transferring button weight in a practical working environment. © 2024 SPIE.

关键词： Triangulation

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Research on Digitization of Cultural Relics Based on Nondestructive Testing and Quantum Computer 3

Research on Digitization of Cultural Relics Based on Nondest...

引用

3rd international conference on Artificial intelligence, Big Data and Algorithms, CAIBDA 2023

作者： Yu, Lu Wang, Hanxi Wuhan University of Technology Wuhan China

ISBN: (纸本)9781643684444

With the rapid iteration of technology and the deepening of the digitization process of human society, some cultural relics can already be restored and electronically archived through 3D modeling, but the simple 3D modeling only repairs and records the cultural relics on a macroscopic level through the computer, and the information on the cultural relics obtained is very limited. This paper provides a quantum computer simulation method based on non-destructive testing. By detecting the material composition inside the cultural relic, the valence state of ions, the arrangement law of the lattice and other data, the quantum computer is used for simulation and construction, and the complete information of the cultural relic can be obtained to the greatest extent. And digitally enter it to provide a driving force for the inheritance and protection of material cultural heritage. © 2023 The Authors.

关键词： Nondestructive examination

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Challenges and Opportunities Applying Laser Beam Scanning Displays Based on Biaxial Resonantly Operated MEMS Scanners 3

Challenges and Opportunities Applying Laser Beam Scanning Di...

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3rd IEEE international conference on Metrology for eXtended Reality, Artificial intelligence and Neural Engineering, MetroXRAINE 2024

作者： Pohl, Leon Petrak, Oleg Berlinski, Jan Metschulat, Marcel Boie, Lars Schmoll, Robert Studer, Jakob Galjan, Wjatscheslaw Bahr, Andreas OQmented GmbH R&d Kiel Germany Hamburg University of Technology Hamburg Germany Jade University of Applied Sciences Wilhelmshaven Germany

ISBN: (纸本)9798350378009

Laser Beam Scanning (LBS) light engines based on two-dimensional (biaxial) resonantly operated and vacuum packaged MEMS scanners, show several advantages over traditional display technologies. Their easy scalability in terms of brightness, resolution, field of view and frame rate makes them well suitable for a wide range of applications including automotive Head-Up Displays (HUD), outdoor displays, 3D sensing and especially compact and fashionable all-day wearable Augmented Reality (AR) glasses. In order that LBS light engines can exploit their unique advantages important challenges must be overcome first. The aim of this paper is to explain the function principle of MEMS based Lissajous laser beam scanning as well as the importance of control loops and optimization mechanisms. Additionally, the resulting opportunities for LBS light engines are highlighted which allows the projector to scale towards the desired resolution, frame rate, field of view or brightness. The achieved projections demonstrating different use cases are visualized by real photographs. © 2024 IEEE.

关键词： Head-up displays

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Multiple Viewing Angle robot with Remote access 3

Multiple Viewing Angle Robot with Remote access

引用

3rd international conference on Intelligent robotics, Mechatronics and Automation Systems, IRMAS 2023

作者： Chougule, S. Mhaswade, Y. Mitra, A. Mogali, C. Molwane, A. Gunjal, M. Department of Mechanical Engineering Vishwakarma Institute of Technology Pune-37 India

robots have existed for a long time with their primary purpose to make the daily lives of humans easier. Today there are a variety of robots available each for a different purpose;some are used in the industry whereas some are used for home applications. Lately the trend of surveillance-based robots is going on, the best example of this is a drone. Drones have a camera attached to them and the operator is given the controls to guide the drone and get the appropriate footage. The main disadvantage of a drone is its stability and that it needs ample space to travel. These drawbacks are eliminated by a camera-mounted robot on a set of three wheels. These robots can be guided from the narrowest of the passage and stability is something the operator need not worry about. © Published under licence by IOP Publishing Ltd.

关键词： robots

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Deep Learning Techniques in Mobile Edge Computing for Internet of Medical Things 3

Deep Learning Techniques in Mobile Edge Computing for Intern...

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3rd international conference on Emerging Smart Technologies and applications, eSmarTA 2023

作者： Alawadhi, Abdulwadood Ahmad, R. Badlishah Almogahed, Abdullah Abrar, Ahmad Department of Computers and Information Technology Yemen Universiti Malaysia Perlis Faculty of Electronic Engineering and Technology Perlis Malaysia Universiti Tun Hussein Onn Malaysia Faculty of Computer Science and Information Technology Johor Parit Raja Malaysia School of Computing Universiti Utara Malaysia InterNetWorks Research Laboratory Sintok-Kedah Malaysia

ISBN: (纸本)9798350305333

The fast expansion of the Internet of Medical Things (IoMT) has resulted in a ubiquitous home health diagnostic network. High patient demand results in high costs, short latency, and communication overload. As a result, 6G is the next generation of IoT, IoMT, and cellular networks, intending to considerably improve the quality of smart healthcare services through high throughput and decreased latency. So far, adopting cloud computing for time-critical applications and decreasing access delays to resources is difficult. Deep learning has been extensively employed to extract characteristics from complicated networks as artificial intelligence technology has advanced. On the other hand, deep learning models are often run in cloud computing data centres with tremendous processing resources. Conventional cloud computing systems primarily rely on the network, which has significant latency and security and privacy issues. One of the successful solutions is the Mobile Edge Computing (MEC) paradigm, which brings cloud computing services closer to the edge network and uses available resources. Mobile edge computing places computer and storage nodes near mobile devices at the Internet's edge, leading to considerable savings in system operating time, memory cost, and power usage. Deep learning is used in mobile edge computing to forecast changes in demand based on daily patient behaviours. It also prepares the network by scaling up network resources as required. This study aims to discuss IoMT and identfy the problems in deep learning for mobile edge computing technology and its applications. © 2023 IEEE.

关键词： Deep learning

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Enhancing Collaborative robots Performance Through Bat Algorithm Based Multi-Objective Optimization 3

Enhancing Collaborative Robots Performance Through Bat Algor...

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3rd international conference on Mechatronics and Automation technology, ICMAT 2024

作者： Sivakumar, R. John Alexis, S. Manickavasagam, A. Rajagopal, Sivakumar Department of Artificial Intelligence and Machine Learning Ahalia School of Engineering and Technology India Department of Mechanical Engineering Ahalia School of Engineering and Technology India Department of Electrical and Electronics Engineering Ahalia School of Engineering and Technology India School of Electronics Engineering Vellore Institute of Technology Vellore India

ISBN: (纸本)9781643685649

Collaborative robots (cobots) are progressively becoming essential in industrial settings, where they operate in conjunction with human workers to execute intricate tasks. Optimising the operational efficiency of cobots entails various obstacles stemming from conflicting aims, including the minimisation of task completion time, reduction of energy consumption, and assurance of safety. This work presents a hybrid optimisation method that integrates the advantages of the Tabu Search algorithm and the Bat Algorithm to tackle these multi-objective difficulties. The Tabu Search is proficient in local search optimisation but frequently becomes ensnared in local optima, whereas the Bat Algorithm, derived from bat echolocation, excels in global search yet may exhibit deficiencies in precision during fine-tuning. The suggested algorithm improves global exploration and local exploitation by hybridising these two strategies, hence ensuring effective job allocation, trajectory planning, and resource management in dynamic collaborative robot environments. The hybrid algorithm is utilised to optimise various objectives inside a simulated collaborative robot environment. Experimental findings indicate substantial enhancements in cobot performance, especially for the equilibrium of work efficiency, safety, and energy consumption, relative to conventional optimisation techniques. This research emphasises the efficacy of integrating bio-inspired algorithms with traditional optimisation methods to address intricate multi-objective challenges in industrial contexts. © 2024 The Authors.

关键词： Collaborative robots

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