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检索条件"机构=Guangxi Key Laboratory of Image Graphics and Intelligent Processing"

共 222 条记录，以下是71-80 订阅

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Research on YOLOv8-Based Household Item Detection for Indoor Scenes

Research on YOLOv8-Based Household Item Detection for Indoor...

引用

Data Intelligence and Innovative Application (DIIA), IEEE International Conference on

作者： Jingwen Wu Xiaonan Luo Guangxi Key Laboratory of Image and Graphic Intelligent Processing Guilin University of Electronic Technology Guilin China

ISBN: (数字)9798331504434

ISBN: (纸本)9798331504441

This research is driven by the growing need for efficient, scalable object detection in smart home applications with real-time performance and resource constraints. In this study, we utilize the YOLOv8 deep learning model for household item detection, focusing on its performance in real-time scenarios. We compare different versions of YOLOv8—specifically, YOLOv8n, YOLOv8s, and YOLOv8m—using a preprocessed custom dataset. The results indicate that YOLOv8n stands out due to its lower parameter count and faster inference speed, making it ideal for real-time applications, even though it has slightly lower precision and recall. In contrast, while YOLOv8s and YOLOv8m show improvements in certain metrics, their higher computational demands limit their effectiveness in resource-constrained settings. Overall, YOLOv8n effectively balances speed and accuracy, offering a viable solution for household item detection.

关键词： Training Measurement Analytical models Accuracy Computational modeling Heuristic algorithms Smart homes Object detection Real-time systems Tuning

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Research on a rectangular microwave filter with rectangular groove

Research on a rectangular microwave filter with rectangular ...

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2022 International Symposium on Sensor Technology and Control, ISSTC 2022

作者： Qian, Jun Hou, Yifeng School of Electronic and Information Engineering Wuzhou University Wuzhou Guangxi China Guangxi Key Laboratory of Image Processing and Intelligent Information System Wuzhou University Wuzhou Guangxi China

In this paper, a rectangular microwave filter with rectangular groove is designed. The filter adopts symmetrical three-stage structure. The first section is the slot line waveguide section to realize the input / output of microwave signal, the second section is the transition section, which adopts the impedance gradient structure, and the third section is the sspps section composed of periodic symmetrical rectangular groove and 90 degree bending structure. By adjusting the geometric size of the rectangular groove and its air gap, the passband width and stopband characteristics of the filter can be adjusted, and its microwave sub wavelength binding effect can be further improved, making the anti space electromagnetic interference ability of sspps filter more excellent. The filter can be applied to L ?s Band civil microwave communication system. © Published under licence by IOP Publishing Ltd.

关键词： Electromagnetic pulse

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EOFD-Net: Edge Optimization and Feature Denoising for Weakly Supervised Deep Nuclei Segmentation with Point Annotations

EOFD-Net: Edge Optimization and Feature Denoising for Weakly...

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International Conference on Acoustics, Speech, and Signal processing (ICASSP)

作者： Xipeng Pan Feihu Hou Zhenbing Liu Siyang Feng Rushi Lan Guangxi Key Laboratory of Image and Graphic Intelligent Processing Guilin University of Electronic Technology Guilin China

Nuclei segmentation is a fundamental and critical step in digital pathological image analysis. Fully supervised nuclei segmentation requires a lot of pixel-by-pixel manual annotation by pathologists, which is very time-consuming and laborious. To minimize the labeling burden of pathologists, this paper uses only point annotations of nuclei data for weakly supervised learning. Specifically, a two-stage model named EOFD-Net with feature denoising and edge optimization is proposed. In the first stage, three weak labels (K-means cluster labels, Voronoi labels, and superpixel labels) with complementary information are used to train the encoder-decoder network to achieve coarse segmentation of nuclei. A feature denoising module(FDM) is designed in the encoder part, which can effectively reduce noise interference. In the second stage, we designed an edge optimization strategy using the prior knowledge of the trained model in the first stage. Confident learning is employed to denoise pseudo-label and rectify the mislabel. These optimized labels are input into the second stage to obtain the final segmentation results. The performance of our method outperforms current state-of-the-art methods on two publicly nuclei segmentation datasets, MoNuSeg and TNBC.

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Application of intelligent Schedule Management in Volunteer Service System

Application of Intelligent Schedule Management in Volunteer ...

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Data Intelligence and Innovative Application (DIIA), IEEE International Conference on

作者： Yongxin Li Xiaonan Luo Guangxi Key Laboratory of Image and Graphic Intelligent Processing Guilin University of Electronic Technology Guilin China

ISBN: (数字)9798331504434

ISBN: (纸本)9798331504441

As the demand for volunteer services grows, enhancing the efficiency and management of these services has become a key issue. This paper explores methods of integrating intelligent scheduling management functions with volunteer service systems to optimize volunteer time management and task allocation. By analyzing existing volunteer service systems, we propose a novel system framework that integrates intelligent scheduling management. This framework updates volunteer schedules in real- time, automatically matches tasks with volunteers' time windows, and optimizes task distribution using smart algorithms. Experimental results show that volunteer service systems with integrated intelligent scheduling management significantly improve task allocation accuracy and volunteer satisfaction. This research provides new ideas and practical basis for the intelligent development of volunteer services.

关键词： Training Performance evaluation Schedules Data analysis Organizations Scheduling User experience Resource management System analysis and design Testing

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An English Pronunciation Evaluation Model Based on Acoustic Phonetics Features

An English Pronunciation Evaluation Model Based on Acoustic ...

引用

Computer Science and Blockchain (CCSB), International Conference on

作者： Hongkang Wang Qingkai Guo Guimin Huang Ya Zhou Guangxi Key Laboratory of Image and Graphic Intelligent Processing Guilin University of Electronic Technology Guilin China

ISBN: (数字)9798350356502

ISBN: (纸本)9798350356519

Oral English practice constitutes a crucial component of English language acquisition for non-native speakers; however, traditional classroom teaching methods are increasingly insufficient to address the diverse needs of learners. This paper enhances the evaluation of pronunciation quality within Computer-Assisted Language Learning (CALL) system. To assess the fluency of English learners' pronunciation, this paper introduces the innovative feature known as wordDurationRatio. Additionally, an intonation evaluation method utilizing dynamic time warping (DTW) algorithms is explored. Finally, this study incorporates support vector regression (SVR) algorithms to effectively fuse features, enhancing the assessment result of pronunciation quality.

关键词： Support vector machines Computer science Acoustic phonetics Fuses Heuristic algorithms Evaluation models Education Quality assessment Blockchains Standards

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Research on a Microwave Band-pass Filter 2

Research on a Microwave Band-pass Filter

引用

2nd International Conference on Electronic Materials and Information Engineering, EMIE 2022

作者： Qian, Jun Hou, Yifeng School of Electronic and Information Engineering Wuzhou University Guangxi Wuzhou China Guangxi Key Laboratory of Image Processing and Intelligent Information System Wuzhou University Guangxi Wuzhou China

ISBN: (纸本)9781713865629

This paper introduces a broadband microwave bandpass filter. The structure of the filter is a filter cavity formed by two balanced dielectric sheets. On the two dielectric sheets, the relative face of the microwave input end and the microwave output end is symmetrically provided with a guided wave surface, the middle face is symmetrically provided with a filter groove surface for filtering, and the surface of an exponential curve structure is arranged along the microwave transmission direction, A plurality of arc-shaped filter grooves are arranged on the opposite surface of the dielectric sheet perpendicular to the microwave transmission direction. This special structure is analyzed and calculated by the finite difference time domain method. The results show that the filter can fully improve the subwavelength binding effect in microwave band and make the anti electromagnetic interference ability of the filter better. © VDE VERLAG GMBH ∙ Berlin ∙ Offenbach.

关键词： Finite difference time domain method

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Liver Tumor image Segmentation Method Based on U-Net Network

Liver Tumor Image Segmentation Method Based on U-Net Network

引用

Data Intelligence and Innovative Application (DIIA), IEEE International Conference on

作者： Dinghong Lu Xiaonan Luo Guangxi Key Laboratory of Image and Graphic Intelligent Processing Guilin University of Electronic Technology Guilin China

ISBN: (数字)9798331504434

ISBN: (纸本)9798331504441

Liver tumors are the most common and fatal ones globally, bringing great harm to human life. In order to ascertain the precise location, size, and volume of tumors, the conventional method of manual segmentation necessitates that physicians delineate the tumor boundaries within the patients’ abdominal CT scans, a process that demands considerable expenditure of time and effort on the part of the medical staff. A method harnessing the U-Net neural network, predicated on deep learning, has been introduced in this study to augment the accuracy and efficiency of liver tumor segmentation in imaging. The U-Net network has been enhanced with the incorporation of Adam optimization and callback mechanisms to bolster the training efficacy and preserve the most effective model. Furthermore, the implementation of the binary crossentropy loss function has been pivotal for optimizing the neural network's convergence and predictive accuracy, which in turn has led to enhanced segmentation results. The experimental findings suggest that the proposed method is capable of automating the segmentation of liver tumor images, including the precise delineation of tumors and those with indistinct margins, achieving a segmentation accuracy of 99.64%.

关键词： Training image segmentation Accuracy Computed tomography Neural networks Liver Medical services Manuals Optimization Tumors

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CLIP-based Text-to-image Pedestrian Retrieval Algorithm

CLIP-based Text-to-image Pedestrian Retrieval Algorithm

引用

image processing, Computer Vision and Machine Learning (ICICML), International Conference on

作者： Xubin Shi Baohua Qiang Ruidong Chen Yuan Xie Guangxi Key Laboratory of Image and Graphic Intelligent Processing Guilin University of Electronic Technology Guilin China

ISBN: (数字)9798350355413

ISBN: (纸本)9798350355420

Text-to-image pedestrian retrieval involves querying a database of images based on a given textual description to find matching images. The main challenge lies in learning how to map visual and textual patterns to a common latent space. This paper improves upon the implicit learning inference framework based on the CLIP model, aiming to learn the relationship between images and text and enhance overall text-image matching. Through text matching learning, fine-grained detail representation learning is promoted. First, a masked language modeling paradigm is designed within the implicit relationship inference module. Then, cross-modal interaction is achieved through the modality alignment module using decomposable attention. Feed aligned image and text features into a multimodal synergy encoder to achieve cross modal interaction, and train the model using distribution consistency loss and ID loss. The improved method achieves better results on the RSTPReid public dataset, with the Rank-1 accuracy improving by approximately 3% compared to existing methods.

关键词： Representation learning Visualization Computer vision Pedestrians Databases image processing Semantics Text to image Transformers Feeds

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Research on a Microwave Filter with Pentagram Grooves 3

Research on a Microwave Filter with Pentagram Grooves

引用

2022 3rd International Conference on Electrical, Electronic Information and Communication Engineering, EEICE 2022

作者： Hou, Y.F. Qian, J. School of Electronic and Information Engineering Wuzhou University Guangxi Wuzhou China Guangxi Key Laboratory of Image Processing and Intelligent Information System Wuzhou University Guangxi Wuzhou China

This paper introduces a microwave filter with pentagram grooves, which belongs to an artificial surface plasmon (SSPPs) type microwave bandpass *** filter adopts a two-stage structure. The first section is a slot-line waveguide section, and one side of this section adopts an exponential curve structure to prevent sudden changes in electromagnetic impedance and achieve a good connection with the second *** second segment is the SSPPs segment, which adopts a novel mirror-symmetric pentagram-shaped groove air gap structure. By adjusting the geometric size of the pentagram-shaped groove, the microwave subwavelength confinement effect can be further improved,making the SSPPs filter more excellent in pass-band characteristics and anti-space electromagnetic *** filter can be applied to the civil microwave communication system of L~1/4S band. © Published under licence by IOP Publishing Ltd.

关键词： Microwave filters

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Design of Smart Home System Based on ZigBee Technology

Design of Smart Home System Based on ZigBee Technology

引用

Data Intelligence and Innovative Application (DIIA), IEEE International Conference on

作者： Yinfan Liang Xiaonan Luo Guangxi Key Laboratory of Image and Graphic Intelligent Processing Guilin University of Electronic Technology Guilin China

ISBN: (数字)9798331504434

ISBN: (纸本)9798331504441

With the rise of the Internet of Things (loT) and digital homes, smart home technology has also advanced. Smart homes can proactively sense people's needs, providing users with a more comfortable and secure living environment, while also saving energy and enhancing safety, thereby greatly improving the quality of life. Thanks to loT technology, smart home devices can connect to the home network, enabling data sharing and centralized control. This project applies ZigBee and MQTT protocols to the field of smart homes, achieving intelligent control and remote control of devices such as lighting, appliances, and security. The ZigBee protocol is used for networking, connecting terminal nodes in the facility layer with the coordinator node, while the MQTT protocol is used to connect the coordinator node to the internet. This project has realized remote control, intelligent control, and smart security of the home system, providing users with a more convenient and comfortable home experience.

关键词： Home appliances Protocols Zigbee Lighting Smart homes Safety Security Internet of Things Remote control intelligent control

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