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6th International Conference on Electronic information technology and Computer Engineering, EITCE 2022

作者： Huang, Maojun Hong, Mei Dong, Lin Yuan, Da Key Laboratory of Intelligent Information Processing Shandong Technology and Business University Shandong Yantai264005 China

ISBN: (纸本)9781450397148

In the context of rapid development of the Internet, the place of spreading financial public opinion is converted from traditional offline places to major online social platforms. Mastering the development mechanism of financial social opinion dissemination on online social media can effectively estimate the length of influence of public opinion and the scope of affected people, and provide effective guidance to relevant staff. Based on the Susceptible Infected Recovered Model, this paper divides the people involved in opinion diffusion into commenters and discussers, and introduces the variation mechanism to design the Susceptible-comment-discussion-removal model, then simulates the model to study the effects of different initial states and parameters on the model, and finally verifies the validity of the model by combining the real data of stock bars. The simulation experiments and validation show that the model can effectively describe the spread of public opinion among the user groups of financial social platforms when it occurs, and provide a valid reference for related workers. However, the content of public opinion, the personal influence of communicators, and the lag effect of communication all have an impact on communication, and these issues need to be addressed in future research. © 2022 Association for Computing Machinery.

关键词： Social aspects

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A Survey of Multimodal Composite Editing and Retrieval

arXiv

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arXiv 2024年

作者： Li, Suyan Huang, Fuxiang Zhang, Lei The Chongqing Key Laboratory of Bio-perception and Multimodal Intelligent Information Processing Chongqing University Chongqing400044 China The Hong Kong University of Science and Technology Hong Kong The Chongqing Key Laboratory of Bio-perception and Multimodal Intelligent Information Processing the School of Microelectronics and Communication Engineering Chongqing University Chongqing400044 China

In the real world, where information is abundant and diverse across different modalities, understanding and utilizing various data types to improve retrieval systems is a key focus of research. Multimodal composite retrieval integrates diverse modalities such as text, image and audio, etc. to provide more accurate, personalized, and contextually relevant results. To facilitate a deeper understanding of this promising direction, this survey explores multimodal composite editing and retrieval in depth, covering image-text composite editing, image-text composite retrieval, and other multimodal composite retrieval. In this survey, we systematically organize the application scenarios, methods, benchmarks, experiments, and future directions. Multimodal learning is a hot topic in large model era, and have also witnessed some surveys in multimodal learning and vision-language models with transformers published in the PAMI journal. To the best of our knowledge, this survey is the first comprehensive review of the literature on multimodal composite retrieval, which is a timely complement of multimodal fusion to existing reviews. To help readers’ quickly track this field, we build the project page for this survey, which can be found at https://***/fuxianghuang1/Multimodal-Composite-Editing-and-Retrieval. © 2024, CC BY-NC-ND.

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Polynomial stacked-attention network for nationality classification

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Frontiers of Computer Science 2022年第4期16卷 215-217页

作者： Kunyan Li Jie Zhang Shiguang Shan Key Laboratory of Intelligent Information Processing of Chinese Academy of Sciences(CAS) Institute of Computing TechnologyCASBeijing100190China University of Chinese Academy of Sciences Beijing100049China

1Introduction In recent years,nationality and region inference has atracted more and_more *** anthropological researches indicate that human faces are influenced by genes,and other external factors,e.g-,geographical environment[1].This relevance provides possible solutions for geographical area inference by ***,it remains a challenging task due to the tiny differences on faces for various countries,which is even hard for human beings to tell.

关键词： Polynomial s. network

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Dual Fusion Network for Hyperspectral Semantic Segmentation 12th

Dual Fusion Network for Hyperspectral Semantic Segmentation

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12th International Conference on Image and Graphics, ICIG 2023

作者： Ding, Xuan Gu, Shuo Yang, Jian PCA Laboratory Key Laboratory of Intelligent Perception and Systems for High-Dimensional Information of Ministry of Education Jiangsu Key Laboratory of Image and Video Understanding for Social Security School of Computer Science and Engineering Nanjing University of Science and Technology Nanjing China

ISBN: (纸本)9783031463075

With the development of imaging technology, it becomes increasingly easy to obtain hyperspectral images (HSI) containing rich spectral information. The application of hyperspectral images in autonomous driving is expected to become a reality. Hyperspectral images have higher dimensions and more information than RGB images, which brings the challenge of training with limited samples. It is not easy to train satisfactory semantic segmentation models directly from hyperspectral images. In this paper, we propose a hyperspectral dual-fusion (hyperDF) network that can fully utilize the pre-training knowledge of the RGB modality to improve the performance of hyperspectral semantic segmentation. Specifically, we generate pseudo-color images from hyperspectral images to simulate RGB signals in order to make better use of the pre-trained RGB semantic segmentation models. The pseudo-color and hyperspectral images are processed in a dual encoder structure and then fused through a channel-wise attention fusion module. Finally, a multi-scale decoder injected with low-level features is used to predict the semantic segmentation results. Experimental results on the Hyperspectral City V2.0 dataset show that our method achieves state-of-the-art results, with a mIoU of 51.68%. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023.

关键词： Semantic Segmentation

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Object Detection Algorithm Based on Coordinate Attention and Context Feature Enhancement 11

Object Detection Algorithm Based on Coordinate Attention and...

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11th International Conference on Computing and Pattern Recognition, ICCPR 2022

作者： Liu, Lingzhi Qiang, Baohua Wang, Yuanchun Yang, Xianyi Tian, Jubo Zhang, Shihao Guilin University of Electronic Technology Guilin China The 54th Research Institute of Cetc Shijiazhuang China Hebei Key Laboratory of Intelligent Information Perception and Processing Shijiazhuang China

ISBN: (纸本)9781450397056

In recent years, object detection has been widely used in various fields such as face detection, remote sensing image detection and pedestrian detection. Due to the complex environment in the actual scene, we need to fully obtain the feature information in the image to improve the accuracy of object detection. This paper proposes an object detection algorithm based on coordinate attention and contextual feature enhancement. We design a multi-scale attention feature pyramid network, which first uses multi-branch atrous convolution to capture multi-scale context information, and then fuses the coordinate attention mechanism to embed location information into channel attention, and finally uses a bidirectional feature pyramid structure to effectively fuse high-level features and low-level features. We also adopt the GIoU loss function to further improve the accuracy of object detection. The experimental results show that the proposed method has certain advantages compared with other detection algorithms in the PASCAL VOC datasets. © 2022 ACM.

关键词： Object detection

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IsoVISoR: Towards 3D Mesoscale Brain Mapping of Large Mammals at Isotropic Sub-micron Resolution

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Neuroscience Bulletin 2025年第2期41卷 344-348页

作者： Chao-Yu Yang Yan Shen Xiaoyang Qi Lufeng Ding Yanyang Xiao Qingyuan Zhu Hao Wang Cheng Xu Pak-Ming Lau Pengcheng Zhou Fang Xu Guo-Qiang Bi Division of Life Sciences and Medicine CAS Key Laboratory of Brain Function and DiseaseUniversity of Science and Technology of ChinaHefei230026China Interdisciplinary Center for Brain Information Shenzhen-Hong Kong Institute of Brain ScienceShenzhen Institute of Advanced TechnologyChinese Academy of SciencesShenzhen518055China Center for Integrative Imaging Hefei National Research Center for Physical Sciences at the MicroscaleUniversity of Science and Technology of ChinaHefei230027China National Engineering Laboratory for Brain-Inspired Intelligence Technology and Application MoE Key Laboratory of Brain-Inspired Intelligent Perception and CognitionSchool of Information Science and TechnologyUniversity of Science and Technology of ChinaHefei230026China Anhui Province Key Laboratory of Biomedical Imaging and Intelligent Processing Institute of Artificial IntelligenceHefei Comprehensive National Science CenterHefei230088China Faculty of Life and Health Sciences Shenzhen University of Advanced TechnologyShenzhen518107China CAS Key Laboratory of Brain Connectome and Manipulation The Brain Cognition and Brain Disease InstituteShenzhen Institute of Advanced TechnologyChinese Academy of SciencesShenzhen518055China

Dear Editor,The mammalian brain exhibits cross-scale complexity in neuronal morphology and connectivity,the study of which demands high-resolution morphological reconstruction of individual neurons across the entire brain[1-4].Current commonly used approaches for such mesoscale brain mapping include two main types of three-dimensional fluorescence microscopy:the block-face methods,and the lightsheet-based methods[5,6].In general,the high imaging speed and light efficiency of light-sheet microscopy make it a suitable tool for high-throughput volumetric imaging,especially when combined with tissue-clearing ***,large brain samples pose major challenges to this approach.

关键词： brain mapping three dimensional fluorescence microscopy mesoscale brain mapping lightsheet based methods block face methods high throughput volumetric imaging tissue clearing techniques

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QoT Assured RBMSA Design for Shared Path Protection based C+L Bands EONs

QoT Assured RBMSA Design for Shared Path Protection based C+...

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

作者： Liu, Yunxuan Feng, Nan Shen, Lingfei Lv, Jingjing Hu, Jinhua Zhao, Jijun School of Information and Electrical Engineering Hebei University of Engineering Handan056038 China Hebei Key Laboratory of Security Information Perception and Processing Handan056038 China 54 Institute of China Electronic Technology Corporation Shijiazhuang050081 China Hebei Key Laboratory of Photonic Information Technology and Application Shijiazhuang050081 China

ISBN: (纸本)9798350312614

关键词： C+L bands EONs Physical layer impairment survivability

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DEHRFormer: Real-Time Transformer for Depth Estimation and Haze Removal from Varicolored Haze Scenes 48

DEHRFormer: Real-Time Transformer for Depth Estimation and H...

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48th IEEE International Conference on Acoustics, Speech and Signal processing, ICASSP 2023

作者： Chen, Sixiang Ye, Tian Shi, Jun Liu, Yun Jiang, Jingxia Chen, Erkang Chen, Peng Xinjiang University School of Information Science and Engineering Uruqmi China Southwest University College of Artificial Intelligence Chongqing China Jimei University School of Ocean Information Engineering Xiamen China Fujian Provincial Key Laboratory of Oceanic Information Perception and Intelligent Processing China

ISBN: (纸本)9781728163277

Varicolored haze caused by chromatic casts poses haze removal and depth estimation challenges. Recent learning-based depth estimation methods are mainly targeted at dehazing first and estimating depth subsequently from haze-free scenes. This way, the inner connections between colored haze and scene depth are lost. In this paper, we propose a real-Time transformer for simultaneous single image Depth Estimation and Haze Removal (DEHRFormer). DEHRFormer consists of a single encoder and two task-specific decoders. The transformer decoders with learnable queries are designed to decode coupling features from the task-Agnostic encoder and project them into clean image and depth map, respectively. In addition, we introduce a novel learning paradigm that utilizes contrastive learning and domain consistency learning to tackle weak-generalization problem for real-world dehazing, while predicting the same depth map from the same scene with varicolored haze. Experiments demonstrate that DEHRFormer achieves significant performance improvement across diverse varicolored haze scenes over previous depth estimation networks and dehazing approaches. © 2023 IEEE.

关键词： Signal encoding

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keycap character detection model based on target classification 7

Keycap character detection model based on target classificat...

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2024 7th International Conference on intelligent Manufacturing and Automation, IMA 2024

作者： Xiong, Taiping Zhu, Zhiguo Wang, Tinghao School of Computer and Information Security Guilin University of Electronic Technology Guangxi Guilin541004 China Key Laboratory of Image Graphics and Intelligent Processing in Guangxi Guilin University of Electronic Technology Guangxi Guilin541004 China

The production process of keycaps may result in surface character defects. The existing keycap character defect detection technology has low efficiency and accuracy, hindering the automation of keycap manufacturing. Addressing the challenge of extracting the entire keyboard from illuminated regions, this paper proposes a method using image feature points for template matching to extract the region of interest. Subsequently, leveraging prior knowledge, the paper addresses character segmentation and extraction on the keyboard. For character detection, the paper preprocesses images and classifies them by using an S-VGG network, yielding corresponding labels. © Published under licence by IOP Publishing Ltd.

关键词： Template matching

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Infrared ship target detection method under complex sea background conditions

Infrared ship target detection method under complex sea back...

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2024 Applied Optics and Photonics China: Optical Sensing, Imaging technology, and Applications, AOPC 2024

作者： Chuangang, Xu Yuexing, Wang Tian, Tian Tianjin Jinhang Institute of Technical Physics Tianjin300308 China National Key Laboratory of Multispectral Information Intelligent Processing Technology School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan430074 China

ISBN: (数字)9781510687820

ISBN: (纸本)9781510687813

In complex sea environments, the signal-to-noise ratio and contrast of infrared images constantly change due to factors such as wave motion, wave reflection, changes in solar altitude angle, target distance, and uneven distribution of thermal radiation, resulting in missed and false detections in infrared ship detection. In the image, ship targets are generally present in the vicinity of the sea antenna. Therefore, by determining the position of the sea sky line, the approximate area of the ship target in the image can be determined, thereby suppressing possible interference from unrelated objects in the sky and sea outside this range and reducing the probability of false detection of infrared ship targets. And in order to solve the possible interference effects of sea clutter and clouds in traditional sea antenna extraction methods, this paper proposes a sea antenna difference extraction algorithm. By enhancing the gray vertical gradient difference between rows, the sea antenna is extracted. Compared with other typical sea antenna extraction algorithms, the accuracy of the sea antenna extraction method in this paper is improved by 7.2%. The infrared image of ships has significant noise, which is affected by the attenuation of atmospheric transmission over long distances on the sea surface. The contrast of ship targets is low, making it difficult to directly extract ship features;Moreover, the infrared imaging of ship targets is greatly affected by factors such as season, weather, and lighting, especially in harsh weather conditions such as clouds, rain, and snow, which can seriously affect the imaging effect and make the infrared images of ships blurry. Therefore, in order to effectively achieve the detection and recognition of ship targets, this paper preprocesses the infrared images of ships before detection. An improved inverse harmonic filtering algorithm is proposed, which first adopts a gradient enhancement strategy, and then eliminates the bright spot interf

关键词： Submarine geophysics

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