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检索条件"机构=Key Laboratory of Computer Application Technology"

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Image segmentation with texture-oriented superpixel 2

Image segmentation with texture-oriented superpixel

引用

2nd International Symposium on computer applications and Information Systems, ISCAIS 2023

作者： Song, Dongke Huang, Heming Zhang, Huiyun School of computer science and technology Qinghai Normal University Xining810008 China State Key Laboratory of Tibetan intelligent information processing and application Xining810008 China

ISBN: (纸本)9781510666665

Superpixel segmentation is an image preprocessing technique that uses pixel blocks instead of pixels to improve the efficiency of subsequent image tasks. Existing methods are not sensitive to image texture. To solve this problem, a texture-oriented superpixel (TOS) segmentation method is proposed. Firstly, an adaptive parameter function based on pixel boundary probability is used to calculate the distance. Secondly, a gradual merging strategy is used for merging. And finally, a loop iterative framework is used to optimize the seeds. The experimental results show that TOS can effectively preserve the smaller texture information, generate seeds that are more consistent with image texture, and better detect image texture. © 2023 SPIE.

关键词： Superpixels

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A Novel Approach with Fusion Edge Prediction Strategy for Table Structure Recognition 11

A Novel Approach with Fusion Edge Prediction Strategy for Ta...

引用

11th International Conference on Information Systems and Computing technology, ISCTech 2023

作者： Liu, Yingli Zhang, Guangtao Shen, Tao Kunming University of Science and Technology Faculty of Information Engineering and Automation Kunming650093 China Kunming University of Science and Technology Yunnan Key Laboratory of Computer Technologies Application Kunming650500 China

ISBN: (纸本)9798350342406

Table, as an information carrier with high information density and direct display form, are widely used in scientific literature and social production documents. Accurately identifying tables from various documents will significantly promote the intelligent application of documents. The table's structural information is crucial for comprehending how the text content in the table relates to one another, but teaching a computer to fully understand a table's structure is still a very difficult undertaking. In this research work, we provided a unique edge-based method to recognize table structures. Specifically, we define the inter-cell relationships as an edge prediction problem and leverage graph convolutional networks to learn representations of the cells. These learned representations are then utilized to directly predict the connections between the cells. The experimental results conducted on three publicly available datasets for table structure recognition provide compelling evidence supporting the feasibility and usefulness of our presented methodology. © 2023 IEEE.

关键词： Forecasting

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Palette-Based Content-Aware Image Recoloring 12th

Palette-Based Content-Aware Image Recoloring

引用

12th International Conference on Computational Visual Media, CVM 2024

作者： Du, Zheng-Jun Zhou, Jia-Wei Xia, Zi-Xun Seng, Bing-Feng Xu, Kun Department of Computer Technology and Application Qinghai University Xining810016 China Qinghai Provincial Key Laboratory of Media Integration Technology and Communication Xining810016 China BNRist Department of CS &T Tsinghua University Beijing100084 China

ISBN: (纸本)9789819720910

Palette-based image recoloring is a popular image editing technique in recent years. It allows users to perform global color edits to an image by manipulating a small set of representative colors. Many approaches have been proposed for palette extraction and palette-based image recoloring. However, existing methods primarily leverage low-level visual information to extract color palettes, so that different objects with similar colors will share the same palette colors. It is impossible to individually recolor one of multiple objects with similar colors, as altering a specific palette color may cause unwanted color changes to many non-interesting objects. To address this issue, in this paper, we present a novel, palette-based content-aware image recoloring approach. Different from previous methods, we extract the color palette of an image in a high-dimensional space that combines low-level visual features and high-level semantic features, allowing generating separate palette colors for different objects with similar colors. This enables users to perform targeted local editing, i.e., distinguish and recolor objects with similar colors separately, without producing unexpected global color changes. Extensive experiments demonstrate the flexibility, local control, and effectiveness of our method. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Color

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Multi-objective performance prediction based on a self-constructed Al-Si alloy dataset 11

Multi-objective performance prediction based on a self-const...

引用

11th International Conference on Information Systems and Computing technology, ISCTech 2023

作者： Hu, Dan Liu, Yingli Shen, Tao Kunming University of Science and Technology Faculty of Information Engineering and Automation Kunming650093 China Kunming University of Science and Technology Yunnan Key Laboratory of Computer Technologies Application Kunming650500 China

ISBN: (纸本)9798350342406

The combination of data-driven approaches and machine learning techniques has changed the design approach for new materials, propelling materials science research into the realm of the fourth paradigm. Researchers in the field of materials science have increasingly focused on utilizing machine learning methods to uncover the underlying nonlinear relationships within material data. However, there is currently limited research in the field of aluminum-silicon alloys regarding the prediction of alloy performance based on the composition-process-structure relationship. Additionally, there is a lack of data sharing in the aluminum-silicon alloy domain. Therefore, this study proposes a methodology. Firstly, an aluminum-silicon alloy dataset is constructed by mining relevant information from materials literature. Then, high-dimensional features in the dataset are subjected to feature selection techniques for dimensionality reduction. Subsequently, a multilayer perceptron model is applied to investigate the relationship between input features such as alloy composition, preparation process, and microstructural parameters, and output features such as yield strength, ultimate tensile strength, and elongation, enabling performance prediction. © 2023 IEEE.

关键词： Feature Selection

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NCCNet: Arbitrary Neural Style Transfer with Multi-channel Conversion 12th

NCCNet: Arbitrary Neural Style Transfer with Multi-channel ...

引用

12th International Conference on Image and Graphics, ICIG 2023

作者： Xiang, Jin Zhao, Huihuang Lin, Mugang Liu, Qingyun College of Computer Science and Technology Hengyang Normal University Hengyang421002 China Hunan Provincial Key Laboratory of Intelligent Information Processing and Application Hengyang421002 China

ISBN: (纸本)9783031463136

Arbitrary style transfer aims to create a novel image from a content image and a style image, stylizing the content image with the style of the style image. However, recent algorithms are prone to unnatural output due to focusing on the statistical distribution of deep features and ignoring the relationship between channels in feature maps. In this paper, we devise a novel Arbitrary Neural Style Transfer Network called NCCNet, which is useful for artistic style transfer. Specifically, NCCNet creates good visual effects by fusing different layers of textures. Moreover, we design an Effective Channel Conversion Modules (ECCM) which uses a multi-channel matrix to rearrange style feature maps to the appropriate range by analyzing the relationship between channels. Then, we can obtain a covariance based on the rearranged style feature map. At the same time, we design a decoder named Self-Adaptive Decoder (SA-Decoder) that conforms to our algorithm. Moreover, we apply our algorithm to the video style transfer and get good results. Qualitative and quantitative evaluations demonstrate that NCCNet performs well in arbitrary video and image style transfer tasks. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023.

关键词： Textures

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Research RSA Accumulator-Based Stateless Blockchain Optimisation for Smart Contracts

Research RSA Accumulator-Based Stateless Blockchain Optimisa...

引用

2023 International Conference on Cyber Security, Artificial Intelligence, and Digital Economy, CSAIDE 2023

作者： Zhuang, Jinyu Fan, Hongbo Li, Xiang Faculty of Information Engineering and Automation Kunming University of Science and Technology Yunnan Kunming650500 China Yunnan Key Laboratory of computer technology application Kunming University of Science and Technology Yunnan Kunming650500 China

ISBN: (纸本)9781510666597

Scalability has grown more important as blockchain technology is adopted. This study introduces RSA-accumulator-based stateless blockchain performance optimization. Verifiable computing technology and distributed design compress node state data and prove smart contract validity, while a new smart contract execution logic and transaction verification scheme solve the problem of transaction verification and execution under stateless conditions, increasing system throughput. The technique reduces consensus node storage and improves throughput compared to Ethereum blockchains, according to experiments. This study examines the scheme's concept, implementation, and blockchain scalability potential. © 2023 SPIE.

关键词： Smart contract

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Dangerous Goods Detection in X-ray Security Inspection Images Based on Improved YOLOv7 5

Dangerous Goods Detection in X-ray Security Inspection Image...

引用

5th International Conference on Video, Signal and Image Processing, VSIP 2023

作者： Zhang, Enyan Yang, Yunhong Feng, Yanxiang Hu, Zeyu Wang, Aili Iwahori, Yuji Heilongjiang Province Key Laboratory Of Laser Spectroscopy Technology And Application Harbin University Of Science And Technology Harbin150080 China Department Of Computer Science Chubu University Aichi487- 8501 Japan

ISBN: (纸本)9798400709272

According to multi-scale targets and overlapping targets in X-ray security inspection images, this paper proposes a dangerous goods detection algorithm called as YOLOv7-MPCN(MaxPooling with CA and BiFPN). As the convolutional network layers overlap, the resolution of the feature map decreases, resulting in the loss of some position information. Firstly, the coordinate attention mechanism is combined with the MPConv structure in the downsampling stage to enrich semantic information while preserving position perception information, improving the ability to extract dangerous goods feature information in complex overlapping backgrounds. Secondly, using the BiFPN(Bidirectional Feature Pyramid Network) feature fusion module with smaller parameter values as the feature pyramid structure of the model effectively reduces the computational complexity of the model;Finally, referring to the residual network structure in RepVGG, adding skip connections in the lower branch of MPConv enables the network to reach deeper depths without the gradient vanishing. The average detection accuracy of YOLOv7-MPCN on the public dataset SIXray reached 92.5%, which is 0.9% higher than YOLOV7. The experimental results show that the proposed algorithm in this paper has an improvement in detection accuracy compared to the original YOLOv7, proving the effectiveness of YOLOv7-MPCN. © 2023 ACM.

关键词： Network layers

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Delay-Beat Differential Phase Demodulation for Laser Phase Noise Immunity in Phase-Sensitive OTDR

Delay-Beat Differential Phase Demodulation for Laser Phase N...

引用

2023 Asia Communications and Photonics Conference/2023 International Photonics and Optoelectronics Meetings, ACP/POEM 2023

作者： Qian, Heng Li, Chuan Li, Chengli Kunming University of Science and Technology Yunnan Key Laboratory of Computer Technologies Application Faculty of Information Engineering and Automation Kunming China School of Physics and Electronic Information Yunnan Normal University Yunnan Key Laboratory of Opo-electronic Information Technology Kunming China

ISBN: (纸本)9798350312614

A phase demodulation method immune to laser phase noise based on time-delay beat-frequency coherent Φ-OTDR is proposed. In this method, the two Rayleigh backscattered light beams with time delay are beat with local light beams respectively, and the phase difference of the two beat signals is used instead of the traditional distance-difference phase to obtain the local disturbance information. In this way, the impact of laser phase noise introduce by the distance-difference phase is avoid, and the constraint of laser linewidth on phase demodulation performance is weakened. In the experiment, a demodulation accuracy of -63.5dB rad2/Hz is achieved under the condition of a laser with a linewidth of 100kHz, which is improve by 11dB compared to traditional phase demodulation method. © 2023 IEEE.

关键词： distributed optical fiber sensing laser phase noise phase demodulation phase-sensitive optical time-domain reflectometry

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Deep Learning Assisted Enhance Vertical Field Confinement of Spot Size Converter

Deep Learning Assisted Enhance Vertical Field Confinement of...

引用

2023 Cross Strait Radio Science and Wireless technology Conference, CSRSWTC 2023

作者： Tan, Qinghao Huang, Jiandao Chen, Zan Hui School of Computer Science and Information Security Guilin University of Electronic Technology Guilin541004 China Guilin University of Electronic Technology Guangxi Key Laboratory of Precision Navigation Technology and Application Guilin541004 China

We propose a spot size converter using pixelated nano-dots waveguide, to enhance the vertical field confinement. Theoretical analysis shows a converter efficiency of -2.1 dB for the TE mode at λ0=1.55 μm by using 30... 详细信息

ISBN: (纸本)9798350358971

关键词： deep learning Integrated optics spot size converter

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NOFTrack: Efficient Multi-Object Tracking with a Speed Advantage

NOFTrack: Efficient Multi-Object Tracking with a Speed Advan...

引用

2024 International Symposium on Digital Home, ISDH 2024

作者： Jiang, Ming Ke, Jiehao Guo, Biao Metaverse Application Engineering Center Guilin University of Electronic Technology Guilin China School of Computer Science and Information Security Guilin University of Electronic Technology Guilin China Guilin University of Electronic Technology Guangxi Key Laboratory of Trusted Software Guilin China

ISBN: (纸本)9798331509873

In the field of multi-object tracking (MOT), accurately tracking the position and characteristics of targets is crucial. However, traditional methods often overlook detection results with low confidence, which can lead to the omission of targets and the fragmentation of trajectories. To overcome these challenges, we have introduced a novel NOF algorithm. This algorithm efficiently handles detection boxes through a tiered strategy, initially using an adaptive Kalman filter for preliminary matching, followed by a secondary screening of detection boxes with lower confidence, and a final stage for processing dubious detection results. This approach not only enhances the speed and accuracy of tracking but also performs exceptionally well when dealing with complex scenes. Moreover, it is capable of achieving high efficiency, with a rate of over 300 frames per second (FPS), ensuring the efficiency and precision of the tracking process. © 2024 IEEE.

关键词： Target tracking

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