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A dwell point detection algorithm for smart pen 2

A dwell point detection algorithm for smart pen

引用

2nd International Conference on Computer Graphics, Image and Virtualization, ICCGIV 2022

作者： Kong, DeHui University of Jinan School of Information Science and Engineering Jinan250022 China Shandong Provincial Key Laboratory of Network Based Intelligent Computing Jinan250022 China

ISBN: (纸本)9781665492508

This paper presents a dwell point detection algorithm for smart pen. The main innovations of the method are: (a) The tracking of a smart pen is achieved by a common monocular camera. (b) A method of vertex adsorption is proposed. (c) The definition of a dwell point is introduced, and the auxiliary line intent is calculated by detecting the dwell point. Compared to the collision body detection method in Unity3D, the method in this paper improves the accuracy of doing auxiliary line intent and the smoothness of user operation. The effectiveness of the method is demonstrated by the use of the method in a smart pen interacting with a Unity3D-based three-dimensional geometry teaching system. © 2022 IEEE.

关键词： Virtual reality

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A Survey of FPGA-Based Deep Learning Acceleration Research

A Survey of FPGA-Based Deep Learning Acceleration Research

引用

International Conference on Image, Vision and intelligent Systems, ICIVIS 2021

作者： Lv, Ziyi Zhang, Jing School of Information Science and Engineering University of Jinan Jinan250022 China Shandong Provincial Key Laboratory of Network-Based Intelligent Computing Jinan250022 China

ISBN: (纸本)9789811669620

In a range of fields such as emotion detection, medical image processing and speech recognition, deep learning has recently achieved good results. With the pursuit of more precise results, many scholars try to add more new type network layers to increase the size of the neural network. However, this will lead to deeper and more intricate network models, and training and evaluating models requires intensive CPU calculations and tremendous computing resources which cannot be achieved by general purpose processors. Nowadays, some hardware accelerators such as Field Programmable Gate Array (FPGA) have been employed to accelerate the neural network, and FPGA with reconfigurability and low power consumption are currently applied to improve throughput of deep learning networks at a reasonable price. In this paper, the typical technologies and methods of accelerating deep learning network on FPGA in recent years are reviewed and analyzed with their advantages and disadvantages, and feasible research suggestions for the next research direction are given. It is expected that it will have a certain reference value for researchers in the field of deep learning acceleration and hardware optimization. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Deep learning

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Attention-Aware U-Net network for Segmentation of Retinopathy Region

Attention-Aware U-Net Network for Segmentation of Retinopath...

引用

International Conference on Image, Vision and intelligent Systems, ICIVIS 2021

作者： Kong, Wenyang Li, Fan Xing, Ruiwen Gao, Xizhan Zhao, Hui Su, Jie Niu, Sijie School of Information Science and Engineering University of Jinan Jinan250022 China Shandong Provincial Key Laboratory of Network-Based Intelligent Computing Jinan250022 China

ISBN: (纸本)9789811669620

The important function of the computer-aided analysis platform for OCT (Optical Coherence Tomography) retinal images is image segmentation and the accuracy of the segmentation results affects the diagnosis of the disease area. In this paper, we improve the U-Net network by introducing attention mechanism and residual learning for segmenting retinal image lesions. Based on the original U-Net architecture, we embed the Squeeze-and-excitation module into the residual learning branch of the residual structure to replace the backbone network of U-Net. As a result, our improved method not only retains the advantages of fast convergence of network and Solve the problem of the weakening of the neural network's ability to extract features in the deep level, but also considers the correlation between attention learning channels, enhances useful features, and suppresses noise features. The data set used for training and testing of the method in this paper contains 2944 images from 23 patients diagnosed with ocular CSC (Central Serous Chorioretinopathy). We performed 4 sets of cross-validation on this dataset. According to experimental data, the method proposed in this paper can get better segmentation results. Compared with seven methods, our improved method can achieve competitive segmentation results, which is helpful for clinical disease diagnosis. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Optical tomography

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Multimodal intention understanding method based on NHMM 2

Multimodal intention understanding method based on NHMM

引用

2nd International Conference on Computer Graphics, Image and Virtualization, ICCGIV 2022

作者： Liu, Hao University of Jinan School of Information Science and Engineering Jinan250022 China Shandong Provincial Key Laboratory of Network Based Intelligent Computing Jinan250022 China

ISBN: (纸本)9781665492508

This paper proposes a multimodal intention understanding method based on NHMM. Due to the declining expression ability of the elderly, single-mode input during human-computer interaction may reduce the accuracy of robot intention understanding and cannot meet the requirements of helping the elderly. Therefore, in the aspect of intention understanding, this paper uses multi-modal input of voice, gesture and posture to obtain the user's multi-dimensional information as much as possible. Each modal information is processed to obtain three intention sets, and then fused to obtain the fused intention set, By combining the improvement of the core formula of hidden Markov model (HMM) with Bayes, the intention with the highest probability in the fusion intention set is calculated as the result of intention understanding. The results show that the accuracy of this method is 97.7% in the state of user natural interaction, and compared with the other four intention understanding methods, this method is more effective for intention extraction under fuzzy input. © 2022 IEEE.

关键词： Human computer interaction

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Multiple Random Feature Superpixel-Based Fuzzy Clustering for Image Segmentation 9

Multiple Random Feature Superpixel-Based Fuzzy Clustering fo...

引用

9th International Conference on information, Cybernetics, and Computational Social Systems, ICCSS 2023

作者： Zhang, Chuanbin Chen, Long Tian, Yifei Shi, Zhaoyin Wang, Yingxu University of Macau Department of Computer and Information Science China School of Computer Science Nanjing University of Posts and Telecommunications Nanjing China Shandong Provincial Key Laboratory of Network-Based Intelligent Computing University of Jinan Jinan China

ISBN: (纸本)9798350342239

Random feature maps attempt to approximate the kernel method with low computational complexity, and they are efficient and effective algorithms for dealing with the non-linear structure of data. Nevertheless, the existing random feature-based methods are sensitive to hyper-parameters, and their performances are affected by the randomness in feature maps. To improve the robustness of random feature maps and further speed up kernel-based image segmentation algorithms, a multiple random feature superpixel-based fuzzy clustering is proposed in this paper. First, we generate a group of random features from the original image via a novel multiple random feature scheme. Then, we use the superpixel segmentation to reduce the scale of multiple random features. The final segmentation results are obtained by performing the multi-view fuzzy clustering on the multiple random feature superpixels. Experiments on two shared benchmark data sets verify the superiority of our approach. © 2023 IEEE.

关键词： Image segmentation

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Non-Destructive Judgment of Watermelon Ripeness Based on Multi-Feature Fusion of Image

Non-Destructive Judgment of Watermelon Ripeness Based on Mul...

引用

International Conference on Fuzzy Systems and Knowledge Discovery (FSKD)

作者： Hongbao Shi Jun Liu Yimei Huang Jinping Li Shandong Provincial Key Laboratory of Network Based Intelligent Computing School of Information Science and Engineering University of Jinan Jinan China

ISBN: (数字)9798350356328

ISBN: (纸本)9798350356335

The nondestructive judgment of watermelon ripeness is a key issue in everyday life. Whether watermelons are ripe or not affects the interests of watermelon farmers and consumers. So far, acoustic, electrical, machine vision and other methods have been applied to the nondestructive judgment of agricultural product ripeness, but the equipment used in the lab, such as spectrometers and laser Doppler vibrometers, is expensive, difficult to carry, and has limited practical value in daily life. Based on practical experience, the ripeness of watermelons can be judged by observing specific physical characteristics, such as the rind's glossiness, texture, fuzz on the fruit stalk and navel. In this study, images of the watermelon's texture, fuzz and navel were captured using a smartphone. We utilized ResN et with an embedded Coordinate Attention mechanism and Swin-Transformer networks to independently analyze the ripeness of each feature. Then we combined the output prediction scores using post-fusion technology, with the highest weighted prediction score judging the final ripeness assessment. Our method achieved a 90.2% accuracy rate on the test set. The experiments demonstrate that a deep learning model utilizing multi-feature fusion of image data can reliably and accurately identify watermelon ripeness, even under varying image conditions.

关键词： Deep learning Laser theory Accuracy Vibrometers Machine vision Morphology Knowledge discovery Mobile handsets Reliability Guidelines

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The Problems and Analysis of Artificial Intelligence Specialty Construction in Universities Under the Present Situation of Artificial Intelligence Development 8th

The Problems and Analysis of Artificial Intelligence Special...

引用

8th EAI International Conference on e-Learning, e-Education, and Online Training, eLEOT 2022

作者： Fu, Weina Liu, Shuai Institute of Information Science and Engineering Hunan Normal University Hunan Changsha410081 China Hunan Provincial Key Laboratory of Intelligent Computing and Language Information Processing Hunan Changsha410081 China

ISBN: (纸本)9783031211638

China’s independent innovation ability in the field of artificial intelligence is a key link to occupy the commanding heights of future science and technology and talent competition. The cultivation of artificial intelligent talents is crucial to promote the development of the artificial intelligent industry. There is a large demand for artificial intelligence talents in the market, but the development of artificial intelligence in colleges and universities is still faced with many problems, such as the construction of related disciplines and majors has just started, the strength of artificial intelligence teachers in colleges and universities is weak, the talent training is mainly based on postgraduate education and the education system is not perfect. This paper analyzes the current cultivation situation of artificial intelligence major in undergraduate colleges and vocational colleges, points out the shortcomings in the construction of artificial intelligence major, and gives some suggestions. © 2022, ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering.

关键词： Personnel training

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Food computing for Nutrition and Health

Food Computing for Nutrition and Health

引用

International Conference on Data Engineering Workshops

作者： Shuqiang Jiang Institute of Computing Technology Chinese Academy of Sciences Key Laboratory of Intelligent Information Processing Beijing University of Chinese Academy of Sciences Beijing

ISBN: (数字)9798350384031

ISBN: (纸本)9798350384048

Dietary intake is the main source of human nutrition and thus an important material foundation for maintaining human health. Food computing applies computational approaches to intelligently obtain dietary categories, ingredients, and nutrient intake from dietary data, and then provides dietary recommendations to users based on various dietary factors. Therefore, it can achieve intelligent dietary management to assist in solving human health issues. For its significant impact on human health, it has received more attention from both academia and industry, and has made rapid development, especially with the booming Artificial Intelligence (AI). This talk will first introduce the definition, methods, tasks and applications of food computing. Then we will discuss its various tasks, ranging from vision-based multi-granularity food analysis, multimodal recipe analysis, food knowledge graph construction and dietary recommendation. Finally, we will point out future research directions on food computing, such as large food language/multimodal models and the emerging interdisciplinary field AI4Food from the synergy between AI and food science. We expect that this talk will provide the researchers with a more comprehensive understanding of the field, and provide perspectives for the next wave of development in this rapidly growing field.

关键词： Industries Conferences Computational modeling Knowledge graphs Data engineering Distance measurement Artificial intelligence

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Research on A Multimodal Fusion Intention Understanding Algorithm for Geriatric Carer Robots 2

Research on A Multimodal Fusion Intention Understanding Algo...

引用

2nd International Conference on Computer Graphics, Image and Virtualization, ICCGIV 2022

作者： Li, WeiNa University of Jinan School of Information Science and Engineering Jinan250022 China Shandong Provincial Key Laboratory of Network Based Intelligent Computing Jinan250022 China

ISBN: (纸本)9781665492508

In the large application background of man-machine collaboration, the elderly are easy to lose direction or can't understand the map. When aging users express their intentions to robots, due to ambiguous language or incorrect gestures, robots may have a variety of intentions to understand and analyze. In this paper, an optimization algorithm model is proposed to avoid robot misunderstanding, which can choose the best intention among various kinds of intention understanding, and perform user feedback evaluation on the output intention, so as to understand the real intention of the user. In view of the traditional serial analysis of user behavior in multimodal fusion algorithm limitations, this paper puts forward the algorithm of model through voice recognition and image recognition input information user behavior, care layer parallel fusion user intent from the voice channel and the visual channel, use the feedback mechanism to determine the true intentions of the user from the user's intent to complete robot navigation links. © 2022 IEEE.

关键词： Speech recognition

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An Analysis on the Training Mode of Master Students in Artificial Intelligence Field for Electronic information Professional Degree—Take Hunan Normal University as an Example 8th

An Analysis on the Training Mode of Master Students in Artif...

引用

8th EAI International Conference on e-Learning, e-Education, and Online Training, eLEOT 2022

ISBN: (纸本)9783031211638

The ability of independent innovation in the field of artificial intelligence is a key element to occupy the commanding heights of future technology and talent competition in China. The cultivation of artificial intelligence talents, especially the cultivation high-end talent, it is essential to promote the development of artificial intelligence industry. At present, the market for artificial intelligence talents is in great demand. There is a shortage of high-end artificial intelligence talents, the weak strength of artificial intelligence teachers in universities, and the incomplete education system for talent training and many other issues. This paper combines some measures taken by Hunan Normal University for graduate students in the field of artificial intelligence in the degree of electronic information, the necessity and feasibility of artificial intelligence training senior talents are discussed for social needs in the field of artificial intelligence, The training goals and methods of postgraduate students in the field of artificial intelligence under the professional category of electronic information major are clarified, and the construction of artificial intelligence field is planned. © 2022, ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering.

关键词： Professional aspects

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