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5th International Conference on Computer Vision and Data Mining, ICCVDM 2024

作者： Tan, Weiguo Xiao, Yannan Wen, Yayuan Deng, Zhenrong Huang, Wenming School of Computer Science and Information Security Guilin University of Electronic Technology Guangxi Guilin541004 China Guangxi Key Laboratory of Image and Graphic Intelligent Processing Guangxi Guilin China College of Electronic Engineering Guangxi Normal University Guangxi Guilin China

ISBN: (纸本)9781510682863

The significant progress of vision-language pre-trained models (VLMs) and large language models (LLMs) have provided a feasible new mode for image captioning, which relies on VLMs to process images and then utilizes LLMs to generate captions, simplifying the caption generation process and making it lighter. Based on this mode, to address the issues of deviation between the generated captions and the content of image expressions, incomplete descriptive information, and resource hungry in previous Chinese image captioning models, we propose a Chinese image captioning model via double decoding based on Visual Prompts, DDVP. This model employs the CLIP model as the encoder, the GPT2 model as the decoder, and introduces Visual Prompts, which are keywords related to image content. The model adopts a double decoding approach, first decoding to generate Visual Prompts and then decoding to generate the final captions based on the Visual Prompts. Through evaluation, we have demonstrated that our model achieves competitive results on the AIC-ICC dataset, and while maintaining fluency, the generated captions of DDVP can also cover the information in the image more comprehensively and accurately. © 2024 SPIE.

关键词： Visual languages

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Inspection Method of Track Facilities Using image Analysis of images Taken from Front of Trains

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Quarterly Report of RTRI (Railway Technical Research Institute) 2023年第3期64卷 205-210页

作者： Nagamine, Nozomi Goda, Wataru Maeda, Riho Tsubokawa, Yosuke Kato, So Itoi, Kensuke Head of Image Analysis Laboratory Information and Communication Technology Division Research Areas: Computer Vision Image Processing Signalling Systems Japan Image Analysis Laboratory Information and Communication Technology Division Research Areas: Computer Vision Image Processing Japan Head of Track Geometry and Maintenance Laboratory Track Technology Division Research Areas: Track Measuring Japan Track Geometry and Maintenance Laboratory Track Technology Division Research Areas: Track Measuring Japan Research Areas: Track Measuring Japan

Appropriate maintenance of tracks is vital for the safe operation of railways. Properly managing track facilities is necessary to prevent buckling of rails. Changes in society are creating a shortage of workers, a decrease in skilled engineers, a decrease in passenger income, and an increase in the need to develop low-cost inspection methods which do not require experience. Therefore, we have developed a method using only inexpensive camcorders, which can extract information from images to detect joint gaps, wooden sleeper deterioration and ballast shape, and estimate the kilometer point of these images to locate the installations in question. This paper describes the outline of the method and its application results. © 2023 Ken-yusha Inc.. All rights reserved.

关键词： Inspection

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Transclaw U-Net: Claw U-Net With Transformers for Medical image Segmentation 5

Transclaw U-Net: Claw U-Net With Transformers for Medical Im...

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5th International Conference on Information communication and Signal processing, ICICSP 2022

作者： Yao, Chang Hu, Menghan Li, Qingli Zhai, Guangtao Zhang, Xiao-Ping East China Normal University Shanghai Key Laboratory of Multidimensional Information Processing Shanghai China Institute of Image Communication and Information Processing Shanghai Jiao Tong University Shanghai China Ryerson University Department of Electrical Computer and Biomedical Engineering Toronto Canada

ISBN: (纸本)9781665485890

In medical image analysis, the long-range spatial features are often not accurately obtained by the traditional convolutional neural networks. Hence, we propose a TransClaw U-Net network structure. The transformer part is added after three convolution operations to fuse shallow features extracted by convolution operations for maximally encoding the long-range spatial features between patches. The 'Claw' in TransClaw U-net means that we add the bottom upsampling part to retain the deepest feature information for detail segmentation. In addition, the modified three-channel global attention mechanism to blend the outputs of three channels (the encoding part, the bottom upsampling part and the decoding part) to effectively extract image contours. The experimental results on Synapse Multi-organ Segmentation Dataset show that TransClaw U-Net performs better than other networks. The results of ablation experiments prove the effectiveness of the three improved components of the network and influence of input image size and skip-connection numbers on network performance. The source code will be publicly available once the paper is accepted. © 2022 IEEE.

关键词： Convolution

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Enhanced YOLOv7-Based Construction Site Environmental Detection Method 4

Enhanced YOLOv7-Based Construction Site Environmental Detect...

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4th International Conference on Big Data, Artificial Intelligence and Internet of Things Engineering, ICBAIE 2023

作者： Liang, Siheng Huang, Wenming Xiao, Yannan Guilin University of Electronic Technology School of Computer and Information Security Guangxi Key Laboratory of Image and Graphic Intelligent Processing Guilin China Guilin University of Electronic Technology School of Computer and Information Security Guilin China

ISBN: (纸本)9798350343618

This paper proposes an enhanced approach utilizing the YOLOv7 model for automated construction site environment detection and management. The method leverages high-resolution surveillance cameras and computer vision techniques to achieve this goal. The proposed method starts with data collection of the construction site environment. Then produce accurate bounding boxes. These bounding boxes serve as input to an improved YOLOv7 network model, enabling feature extraction and generating high-scoring feature maps with associated weights. Utilizing these weights, image segmentation is performed to obtain the desired detection heads. Experimental results demonstrate the effectiveness of the method in identifying and annotating various environmental features within the construction site, leading to significant improvements in detection accuracy. Compared to similar techniques, this method offers faster detection speed, higher accuracy, and reduced error rates. The proposed construction site environment detection method provides an efficient and automated solution for on-site management in the construction industry, with practical applications and value. © 2023 IEEE.

关键词： Construction industry

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Theoretical verification of intermolecular hydrogen bond induced thermally activated delayed fluorescence in SOBF-OMe

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Chinese Physics B 2021年第12期30卷 378-384页

作者： Mu-Zhen Li Fei-Yan Li Qun Zhang Kai Zhang Yu-Zhi Song Jian-Zhong Fan Chuan-Kui Wang Li-Li Lin Shandong Key Laboratory of Medical Physics and Image Processing&Shandong Provincial Engineering and Technical Center of Light Manipulations School of Physics and ElectronicsShandong Normal UniversityJinan 250358China

Thermally activated delayed fluorescence(TADF)molecules have attracted great attention as high efficient luminescent *** of TADF molecules possess small energy gap between the first singlet excited state(S_(1))and the first triplet excited state(T_(1))to favor the up-conversion from T_(1)to S_(1).In this paper,a new TADF generation mechanism is revealed based on theoretical *** systematic study of the light-emitting properties of SOBF-OMe in both toluene and in aggregation state,we find that the single SOBF-OMe could not realize TADF emission due to large energy gap as well as small up-conversion rates between S_(1)and T_(1).Through analysis of dimers,we find that dimers with intermolecular hydrogen bond(H-bond)are responsible for the generation of TADF,since smaller energy gap between S_(1)and T_(1)is found and the emission wavelength is in good agreement with experimental *** emission properties of SOBF-H are also studied for comparison,which reflect the important role of *** theoretical results agree ith experimental results well and confirm the mechanism of H-bond induced TADF.

关键词： organic light-emitting diodes thermally activated delayed fluorescence intermolecular hydrogen bond decay rates

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A Discrete Artificial Bee Colony Algorithm for Stochastic Vehicle Scheduling

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Complex System Modeling and Simulation 2022年第3期2卷 238-252页

作者： Yuanyuan Li Yindong Shen Jingpeng Li Key Laboratory of Image Processing and Intelligent Control School of Artificial Intelligence and AutomationHuazhong University of Science and TechnologyWuhan 430074China Division of Computer Science and Mathematics University of StirlingStirlingFK94LAUK

Vehicle scheduling plays a profound role in public ***,stochastic vehicle scheduling may lead to more robust *** solve the stochastic vehicle scheduling problem(SVSP),a discrete artificial bee colony algorithm(DABC)is *** to the discreteness of SVSP,in DABC,a new encoding and decoding scheme with small dimensions is designed,whilst an initialization rule and three neighborhood search schemes(i.e.,discrete scheme,heuristic scheme,and learnable scheme)are devised individually.A series of experiments demonstrate that the proposed DABC with any neighborhood search scheme is able to produce better schedules than the benchmark results and DABC with the heuristic scheme performs the best among the three proposed search schemes.

关键词： public transportation stochastic vehicle scheduling discrete artificial bee colony search scheme

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Immune microenvironment-reshaping Au@Bi_(2)Te_(3) nanoparticles for spectral computed tomography/photoacoustic imaging-guided synergetic photo/radio/immunotherapy

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Nano Research 2023年第1期16卷 771-781页

作者： Kai Zhu Zede Wu Qiuyu Li Meirong Hou Honglei Hu Shuting Zheng Li Qi Yikai Xu Chenggong Yan Bingxia Zhao Department of Medical Imaging Center Nanfang HospitalSouthern Medical UniversityGuangzhou 510515China Guangzhou Key Laboratory of Tumor Immunology Research Cancer Research InstituteSchool of Basic Medical SciencesSouthern Medical UniversityGuangzhou 510515China Guangdong Provincial Key Laboratory of Medical Image Processing Guangdong Province Engineering Laboratory for Medical Imaging and Diagnostic TechnologySchool of Biomedical EngineeringSouthern Medical UniversityGuangzhou 510515China Guangdong Provincial Key Laboratory of Shock and Microcirculation Guangzhou 510515China Experimental Education/Administration Center School of Basic Medical ScienceSouthern Medical UniversityGuangzhou 510515China

Radiotherapy(RT)mediated tumor immunogenicity offers an opportunity for simultaneous RT and immunotherapy via immunogenic cell death(ICD),which releases damaged-associated molecular patterns and generates“eat me”signals for the innate immune system to modulate the ***,tumor hypoxia significantly reduces the therapeutic efficacy of RT and hampers its mediation of ICD ***,Au@Bi_(2)Te_(3)-polyethylene glycol(PEG)was rationally constructed as theranostic nanozymes for mild photothermal therapy,tumor hypoxia modulation,and RT adjuvant cancer *** tumor-specific production of oxygen could not only augment the effects of RT by enhanced reactive oxygen species(ROS)generation,but also reduce hypoxia-related cytokines and downregulate programmed cell death-ligand 1(PD-L1)to unleash immune-enhancing T ***,Au@Bi_(2)Te_(3)-PEG could act as an immune-blocking inhibitor by efficient ICD induction with the combination of mild-photothermal therapy+RT to inhibit the tumor immune escape and improve antitumor immune *** amounts of CD^(4+) and CD^(8+) Tcells and elevated levels of cytokines could be observed that eventually led to effective post-medication inhibition of primary and abscopal *** computed tomography/photoacoustic imaging allowed noninvasive and real-time tracking of nanoparticle(NP)accumulation and oxygenation status at tumor ***,Au@Bi_(2)Te_(3)-PEG NPs could serve as effective theranostic nanoregulators with remarkable synergistic mildphotothermal/RT/immunotherapy effects that helped reshape the immune microenvironment and had remarkable molecular imaging properties.

关键词： radioresistance immunotherapy immunogenic cell death hypoxia programmed cell death-ligand 1(PD-L1) spectral computed tomography(CT)

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Enhancing Security in Smart Homes with IoT Using Logit-Boosted Techniques 6

Enhancing Security in Smart Homes with IoT Using Logit-Boost...

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6th International Conference on Computer Information Science and Application Technology, CISAT 2023

作者： Rahim, Asif Zhong, Yanru Ahmad, Tariq School of Computer and Information Security Guilin university of Electronic Technology Guilin54001 China Guangxi Key Laboratory of Intelligent Processing of Computer Image and Graphics Guilin University of Electronic Technology Guilin541001 China School of Information and Communication Engineering Guilin University of Electronic Technology Guilin541001 China

ISBN: (纸本)9781510668546

The utilization and advancement of Internet of Things (IoT) gadgets have noticeably increased in recent times. Various sectors, including intelligent homes, healthcare, sports analysis, and different industries, use IoT devices. Traffic is a crucial aspect of IoT devices, and it differs from conventional device traffic in several ways. This investigation employed 41 Internet of Things (IoT) devices. A machine learning model was developed that can classify IoT devices into multiple categories based on 13 different network traffic features. The raw data that was gathered was preprocessed using techniques like standardization and scaling techniques of the dataset. Algorithms for feature selecting can be utilized to extract characteristics from textual data. Following stratification, The dataset contains 106,234 sets of features that were utilized to enhance the predictive model. This research employed various evaluation metrics to demonstrate the effectiveness of the logistic-boosted algorithms. In this research, collaborative machine learning methods were utilized as a starting point to develop an intrusion detection system (IDS) that can identify abnormal network traffic. The principal aim of this investigation is to identify attacks and abnormalities within a Smart Home IoT setting. We have introduced a new technique for constructing Logit-Boosted algorithm, namely Logi-CatBoost Classifier. Once the logitboosted algorithm was employed to classify the dataset, Logi-CBC performed the best, with an accuracy of 88.70%. We suggested Logi-CBC algorithm achieved the top precision among previously used Logit-Boosted algorithms in past studies on the same dataset. © 2023 SPIE.

关键词： Internet of things

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Exploring Jaw Morphology and Patient-specific Dynamic Rotation Trajectory Using Cone Beam Computed Tomography

Exploring Jaw Morphology and Patient-specific Dynamic Rotati...

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International Conference on communication Engineering and Technology (ICCET)

作者： P S Anusree Bikram Keshari Parida Wonsang You Dept. of Information and Communication Engineering Artificial Intelligence and Image Processing Laboratory (AIIP Lab) Sun Moon University Asan South Korea

ISBN: (数字)9798350373271

ISBN: (纸本)9798350373288

Cone Beam Computed Tomography (CBCT) is a widely adopted technology in dental healthcare, particularly for surgical planning. However, effective visualization methods are crucial for formatting and analyzing volumetric data. Two primary formatting options - Curved Multi-planar Reformatting and Direct Volume Rendering - are used widely for evaluating jaw shape and creating panoramic views. Existing software methods frequently require the manual selection of several nodes along the jaw on an axial image that roughly represents the shape of the dental arch. Our work intends to introduce a novel and automatic algorithm for detecting the patient’s jaw from CBCT, suitable for defining a focal trough and evaluating an optimal patient-specific dynamic rotation trajectory applicable to rotational panoramic radiography based only on the CBCT volume data without the need to delineate a dental arch. Our findings showed that this approach works well even for patients without teeth or having heavy metal implants.

关键词： Shape Computed tomography Heuristic algorithms Software algorithms Surgery Teeth Rendering (computer graphics)

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NEAT-Net: An Unsupervised Cross-View Prior Inpainting Network for CBCT Metal Artifact Reduction 46

NEAT-Net: An Unsupervised Cross-View Prior Inpainting Networ...

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46th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2024

作者： Yang, Yang Tong, Zhan Zhong, Xinyun Shi, Yijie Xi, Yan Yu, Wenxue Wu, Zhan Chen, Yang First-Imaging Tech Shanghai China Southeast University Laboratory of Image Science and Technology The School of Computer Science and Engineering Nanjing China Southeast University Jiangsu Provincial Joint International Research Laboratory of Medical Information Processing The Key Laboratory of New Generation Artificial Intelligence Technology and Its Interdisciplinary Applications Nanjing China

ISBN: (纸本)9798350371499

Intraoperative Cone-Beam Computed Tomography (CBCT) facilitates intraoperative navigation for Minimally Invasive Spine Surgery (MISS). However, high-attenuation metal implants used in MISS often cause metal artifacts in the reconstructed CBCT images. Current algorithms do not consider the cross-view information in the projection-domain for metal artifact reduction (MAR). Inaccurate projection-domain inpainting results in CBCT MAR lead to tissue blurring and secondary artifacts, significantly compromising the accuracy of CBCT-guided MISS and increasing surgical risks. To address the above challenge, in this paper, we propose a novel unsupervised cross-view prior inpainting network for CBCT Metal Artifact Reduction named NEAT-Net. Firstly, a cross-view prior multi-scale inpainting module is constructed to learn the inter-view complementary information. Secondly, a hybrid feature attention module is proposed to adaptively fuse cross-view features. In addition, an unsupervised training approach is proposed to directly learn from metal-affected data. Extensive experiments are conducted to verify the effectiveness of our algorithm on a real clinical dataset. © 2024 IEEE.

关键词： Computerized tomography

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