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From points to rooms: enhancing large language model comprehension through concrete representations 3

From points to rooms: enhancing large language model compreh...

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3rd international conference on Electronics technology and Artificial intelligence, ETAI 2024

作者： Chen, Siyi Zhang, Yanping School of Information Science and Technology North China University of Technology Beijing100144 China

ISBN: (纸本)9781510683143

Nowadays, large language models (LLM) have made significant progress in understanding and generating natural language and have become an important focus of research in the field of artificial intelligence. The capabilities of these models have been validated in a variety of applications, including machine translation, question-answer systems, and text generation. However, there are still challenges in understanding and processing spatial data, e.g., perception of abstract graph data. This study proposes a method to convert abstract graph representations into concrete object representations to enhance the impact of LLM comprehension. In the study, correspondences between abstract graph elements and concrete objects were first identified, such as mapping nodes in the graph to concrete objects and transforming the properties of edges into distances or connectivity between these spaces. Then, the graph data are transformed into easy-to-understand textual descriptions by constructing concrete scene descriptions. The experimental results show that, compared with the direct input of abstract graph, the concrete object representation can significantly improve the understanding and information processing ability of the model. This suggests that by converting abstract data into concretized descriptions, the language comprehension capability of LLM can be utilized more effectively, thus improving its performance in processing complex data. This study not only provides new perspectives for understanding the behavior of LLM when dealing with different types of data, but also provides practical strategies for improving model performance. © 2024 SPIE.

关键词： Graph neural networks

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Research on the application of artificial intelligence in network literature communication 3

Research on the application of artificial intelligence in ne...

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2022 3rd international conference on Computer Information and Big Data applications, CIBDA 2022

作者： Huang, Nini Faculty of Literature and Law Wuhan DongHu University Hubei Wuhan China

ISBN: (纸本)9783800758760

After more than 20 years of development, network literature has opened up a large market and formed a coexistence situation with traditional literature. Under the influence of the continuous progress of computer technology and modern scientific system, modern science and technology such as artificial intelligence have gradually realized the integration with many traditional technical fields, and a large number of literary works have been emerging and updated with the help of the new technology of artificial intelligence. This paper analyzes the application of artificial intelligence in network literature communication from two aspects of intelligent recommendation technology and computer-aided translation technology. Artificial intelligence makes a qualitative leap in the efficiency and scope of network literature communication, and audiences at home and abroad can appreciate excellent network literature works. © VDE VERLAG GMBH - Berlin - Offenbach.

关键词： Artificial intelligence

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Humanoid robot control system based on human pose detection 3

Humanoid Robot control system based on human pose detection

引用

3rd international conference on Control and Intelligent robotics, ICCIR 2023

作者： Wen, Jinghao Feng, Xuran Zhang, Qirui Yuan, Hongye Peng, Xi School of Computer Central China Normal University Hubei Wuhan430000 China Hubei Provincial Key Laboratory of Artificial Intelligence and Smart Learning China Higher Education Institutions of Hubei Province Experimental Teaching Model Center of Basic Computer Science China

ISBN: (纸本)9781510671867

With the rapid progress of science and technology, an increasing number of robots are used in society. Compared with multi-legged crawling robots, humanoid robots have gained more flexibility and reliability with a structure similar to the human body, and have been widely used. Therefore, the proper pose control of the humanoid robot is particularly critical. This paper proposes and designs a humanoid robot control system based on human pose detection. The system detects the posture image of the human body by using the OpenPose method, and then uses the space vector method to calculate the rotation angle information of the human body joints. After being processed, the information is sent to the steering gear controller by the Raspberry Pi. After the controller solves and processes the signal, the pose of the robot is controlled by driving the steering gear. © 2023 SPIE.

关键词： Human computer interaction

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Study on HGR by Using Machine Learning 3

Study on HGR by Using Machine Learning

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3rd international conference on Advance Computing and Innovative Technologies in Engineering, ICACITE 2023

作者： Sharma, Anand Kumar Suresh Kumar, A. Nagpal, Amandeep Singh, Rajesh Reddy, Dasari Veera Chadha, Anupama Vallurupalli Nageswara Rao Vignana Jyothi Institute of Engineering & Technology Department of Information Technology Hyderabad India Graphic Era Deemed to Be University Department of CSE India Lovely Professional University Phagwara India Uttaranchal University Uttaranchal Institute of Technology India SR University School of Computer Science and Artificial Intelligence Warangal Telangana India Manav Rachna International Institute of Research and Studies Department of Computer Applications Haryana Faridabad India

ISBN: (纸本)9798350399264

The medical field and other research areas fields heavily rely on artificial intelligence (AI) and machine learning (ML). Hand gesture recognition (HGR), which is a straightforward approach for interacting with machines, has drawn the attention of numerous researchers in the context of AI. Utilizing ML technique, HGR is carried out. Both the image technique and the design approach are parts of it. In the image technique, the hand picture is rebuilt utilizing the attributes of the images. However, when using the model-based approach, the image is recreated using many models, including volumetric, geometric, and others. The key difficulty in gesture control continues to be the ML individual's complexity and preparation time. Its accuracy is used to assess the HGR accuracy. Its precision is used to assess the HGR overall system performance. The many techniques and algorithms utilized in gesture control are covered in detail inside this work. © 2023 IEEE.

关键词： Machine learning

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Real-time Multiple Analog Gauges Reader for an Autonomous robot Application 17

Real-time Multiple Analog Gauges Reader for an Autonomous Ro...

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17th international Joint Symposium on Artificial intelligence and Natural Language Processing (iSAI-NLP) / 3rd international conference on Artificial intelligence and Internet of Things (AIoT)

作者： Trairattanapa, Visarut Phimsiri, Sasin Utintu, Chaitat Cherdchusakulcha, Riu Tosawadi, Teepakorn Thamwiwatthana, Ek Tungjitnob, Suchat Tangamonsiri, Peemapol Takutruea, Aphisit Keomeesuan, Apirat Jitnaknan, Tanapoom Suttichaya, Vasin Al & Robot Ventures Co Ltd Bangkok Thailand

ISBN: (数字)9781665457279

ISBN: (纸本)9781665457279

With the development of robotic technology, autonomous robots have been extended to production industries to substitute manual tasks like routine operations. In the general manufacturer, analog gauges are the most commonly utilized and required operators for manual reading. Accordingly, an analog gauge reading can be considered a fundamental feature for the operator robots to be fully automated for inspection purposes. This paper presents the methods for reading multiple analog gauges automatically using a camera. The processing pipeline consists of two main stages: 1) gauge detector for extracting individual gauges and 2) gauge reader for estimating gauge values. For gauge detectors, we propose three different YOLOv5 architecture sizes. The gauge readers are mainly categorized into computer-vision approach (CV), and deep learning regression approaches. The deep learning approaches consist of two CNN-based backbones, ResNet50 and EfficientNetV2B0, and one transformer-based SwinTransformer. Finally, we introduce the feasibility of the combination of each gauge detector and reader. As a result, the YOLOv5m detector with EfficientNetV2B0 CNN backbone reader theoretically achieves the best performance but is not practical for industrial applications. In contrast, we introduce the YOLOv5m detector with the CV method as the most robust multiple gauge reader. As a result, it reaches the comparative performances to the EfficientNetV2B0 backbone and is more compatible with robotic applications.

关键词： Analog Gauge Reader Computer Vision Image Processing Object Detection Image Regression

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Analysis of Machine Learning for Recognizing Hand Gestures 3

Analysis of Machine Learning for Recognizing Hand Gestures

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3rd international conference on Advance Computing and Innovative Technologies in Engineering, ICACITE 2023

作者： Kumar Sharma, Anand Kumar, A Suresh Nagpal, Amandeep Singh, Rajesh Reddy, DasariVeera Chadha, Anupama Vallurupalli Nageswara Rao Vignana Jyothi Institute of Engineering & Technology Department of Information Technology Hyderabad India Graphic Era Deemed to Be University Department of Cse India Lovely Professional University Phagwara India Uttaranchal University Uttaranchal Institute of Technology India Sr University School of Computer Science and Artificial Intelligence Telangana Warangal India ManavRachna International Institute of Research and Studies Department of Computer Applications Haryana Faridabad India

ISBN: (纸本)9798350399264

关键词： Machine learning

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Deciphering the Catalysts Influencing the Willingness to Embrace Digital Learning applications: A Comprehensive Exploration 3rd

Deciphering the Catalysts Influencing the Willingness to Emb...

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3rd international Semantic intelligence conference, ISIC 2023

作者： Srivastava, Ankita Nautiyal, Navtika Singh National Forensic Sciences University Gujarat India

ISBN: (纸本)9789819773558

The rapid advancement of technology has revolutionized the education sector, ushering in a new era of digital learning applications. In recent years, the adoption of these applications has witnessed significant growth due to their potential to enhance learning experiences, promote accessibility, and adapt to individual needs. The research methodology employed a mixed-methods approach, combining quantitative surveys and qualitative interviews. The study sample consisted of a diverse group of students and educators from various educational institutions, representing different age groups, backgrounds, and fields of study. Furthermore, the study found that the attitudes and perceptions of peers and instructors also exerted a considerable influence on the intention to adopt digital learning applications. Positive endorsements and recommendations from influential peers and respected educators positively impacted participants’ attitudes toward adoption. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Contrastive Learning

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Three-dimensional profilometry for tool wear area using modulation-based structured illumination microscopy 3

Three-dimensional profilometry for tool wear area using modu...

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2023 3rd international conference on Detection technology and intelligence System, DTIS 2023

作者： Hu, Chang'An Wang, Xi Xie, Zhongye Lv, Fei National Institute of Measurement and Testing Technology Sichuan Chengdu610021 China School of School of Excellence in Engineering Dongguan University of Technology Guangdong Dongguan523808 China School of Computer Science Chengdu Normal University Chengdu611130 China

A new approach named modulation-based structured-illumination microscopy (MSIM) is presented in this paper to reconstruct the three-dimensional (3D) topography of the tooltip, which can be used to evaluate the degree of wear. In MSIM, the modulation estimation of the reflected patterns characterizes the surface profile. This technique can reconstruct the 3D profile precisely and something that conventional computer vision and imaging analysis cannot achieve. Importantly, an ordinary objective lens is used in the measurement system to take the image of the sample. So, the measurement system is simple and cheap. The theoretical analysis and experiments conducted on the tooltip are presented. The measurement repeatability can reach 500 nm. This method holds promise for applications in tool wear monitoring, wear mechanism analysis, and micromachining. © Published under licence by IOP Publishing Ltd.

关键词： Wear of materials

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A High Quality Secure Medical Image Steganography Method 3

A High Quality Secure Medical Image Steganography Method

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3rd international conference on Computing and Information technology, ICCIT 2023

作者： Hameed, Mohamed Abdel Hassaballah, M. Bekhet, Saddam Narmatha, C. Kenk, Mourad A. Luxor University Faculty of Computers and Information Department of Computer Science Luxor Egypt Prince Sattam Bin Abdulaziz University College of Computer Engineering and Sciences Department of Computer Science AlKharj Saudi Arabia South Valley University Faculty of Commerce Qena Egypt University of Tabuk Faculty of Computers and Information Technology Tabuk City Saudi Arabia South Valley University Faculty of Computers and Artificial Intelligence Department of Computer Science Hurghada Egypt

ISBN: (纸本)9798350321487

The exchange of medical images over the Internet has prompted substantial claims on the last years due to the presentation of cloud-based medical data systems according to various web services in the area of telemedicine applications. The preservation of confidential information has ever been a key indicator of the effectiveness of these systems. In this paper, an efficient data hiding technique is proposed for Digital Imaging and Communications in Medicine (DICOM) images hence security can be specified for the highly invaluable and private sensitive data of the patient. The proposed method is developed for DICOM images to embed Patient Record Information (PRI) for maintaining the fidelity of both the critical components of the image and private patient data. The proposed method is very effective in telemedicine applications as it can increase the security of the PRI during its transmission over the Internet from different remote places. © 2023 IEEE.

关键词： Steganography

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A Reliable Approach for Automatic Grading of Diabetic Retinopathy from Fundus Images using Feature Extraction and Fusion 3

A Reliable Approach for Automatic Grading of Diabetic Retino...

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3rd international conference on Electrical, Electronics, Information and Communication Technologies, ICEEICT 2024

作者： Jasmine, R.Anita Ramla, M. Ramesh, M. Srm Institute of Science and Technology Department of Data Science and Business Systems Chennai Kattankulathur India Srm Institute of Science and Technology Department of Computer Applications Chennai Kattankulathur India Srm Institute of Science and Technology Department of Computer Science Chennai Kattankulathur India

ISBN: (纸本)9798350369083

Diabetic Retinopathy (DR) is widely recognized as the primary cause of visual impairment worldwide. Early intervention is crucial in preventing irreversible vision loss. Ophthalmologists conventionally utilize fundus cameras to capture retinal images and detect indications of diabetic retinopathy, thereby facilitating prompt diagnosis. The progress made in computational intelligence has significantly enhanced our ability to identify, predict, and categorize DR. The focus of this research is to present a proficient framework for the DR grading. The framework proposed employs Laplacian filters to reduce undesirable image distortions and enhance the overall quality of the images. The methodology involves the utilization of transfer learning through the pre-existing VGG19 Convolutional Neural Network architecture to pull out features from diverse pooling layers. The amalgamation of extracted features from multiple layers results in the formation of feature vectors. These vectors are utilized as inputs for training various machine learning algorithms, with the objective of identifying the most effective model for evaluating the severity of DR. Significantly, the research provides a rationale for its forecasts, guaranteeing the transparency of the algorithm and comprehensibility of the model, thereby validating its reliability. The model's exceptional precision renders it a promising candidate for broad implementation in clinical identification and prediction of DR, potentially augmenting global patient outcomes. © 2024 IEEE.

关键词： Convolutional neural networks

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