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Culture-oriented Science & technology (ICCST), International Conference on

作者： Zhi-bin Su Bing Liu Li-jing Zhang Hui Ren School of Information and Communication Engineering Communication University of China Key Laboratory of Acoustic Visual Technology and Intelligent Control System Ministry of Culture and Tourism Beijing China

ISBN: (数字)9781728181387

ISBN: (纸本)9781728181394

With the rapid development of intelligent image processing and computer vision, interpreting and extracting emotion information from images have become a hot research topic, especially the studies on film and television scene images with rich expressions and certain feelings from the aspect of audience. To investigate the distribution of emotions and its affect on the result of machine learning, this paper established the emotion classification models with different salient and non-salient regions based on self-built dataset from film and television works. Three salient extraction algorithms were used to the regional segmentation, and the color and texture features of each region were extracted. Emotion classification models were established based on SVM and RF algorithms respectively. Since features of the salient region could not cover all the information of the original image, the prediction accuracy of the unprocessed image was the highest. Nevertheless, when models made an error in the emotion prediction of the original image, the experimental results of salient region could get the correct answer under the certain circumstances. Through the analysis, the areas of interest can be used for emotion prediction to reduce the redundancy; however, to make it more accurate, the appropriate salient region extraction algorithm should be selected for different types of images and features. Our study provides data and theoretical guidance for image understanding and retrieval, and it has practical significance for more detailed classification based on the affective sensation.

关键词： Feature extraction Image color analysis TV Classification algorithms Support vector machines Motion pictures Visualization

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China Land Carbon Budget(CLCB1.0):a comprehensive estimate of the land carbon budget in China

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national Science Review 2025年第4期 15-18页

作者： Jiangzhou Xia Xiaosheng Xia Xuhui Wang Weimin Ju Zhengyang Lin Zhangcai Qin Yuxing Sang Yanzi Yan Wenping Yuan Xu Yue Haicheng Zhang Hao Zhou Qiuan Zhu Tianjin Key Laboratory of Water Resources and Environment Tianjin Normal University School of Atmospheric Sciences Sun Yat-sen University Institute of Carbon Neutrality Sino-French Institute for Earth System ScienceCollege of Urban and Environmental SciencesPeking University International Institute for Earth System Sciences Nanjing University Jiangsu Center for Collaborative Innovation in Geographic Information Resource Development and Application School of Atmospheric Sciences Guangdong Province Key Laboratory for Climate Change and Natural Disaster Studies Key Laboratory of Tropical Atmosphere-Ocean System (Ministry of Education) Sun Yat-sen University Department of Soil and Environment Swedish University of Agricultural Sciences Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control Collaborative Innovation Center of Atmospheric Environment and Equipment Technology School of Environmental Science and Engineering Nanjing University of Information Science & Technology (NUIST) Carbon-Water Research Station in Karst Regions of Northern Guangdong School of Geography and Planning Sun Yat-sen University College of Meteorology and Oceanography National University of Defense Technology College of Geography and Remote Sensing Hohai University

The terrestrial ecosystem plays an important role in regulating the regional carbon balance, in particular for China, where ecological projects during past decades [1,2] have led to large increases in China's land carbon sinks, partially offsetting fossil fuel emissions. Therefore, accurate evaluation of land carbon fluxes in China is critical for improving our understanding of the magnitude of China's carbon budget, and projecting its future changes.

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Design and Implementation of an Linkage control system for Stage Visual Effect Equipment

Design and Implementation of an Linkage Control System for S...

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Culture-oriented Science & technology (ICCST), International Conference on

作者： Shilei Bai Yihan Suo Kai Xu Xiujun Tang Jiaxin Zhang School of Information and Communication Engineering Communication University of China Key Laboratory of Acoustic Visual Technology and Intelligent Control System Ministry of Culture and Tourism (Communication University of China) Beijing Key Laboratory of Modern Entertainment Technology (Communication University of China) State Key Laboratory of Media Convergence of Communication Beijing China

ISBN: (数字)9781728181387

ISBN: (纸本)9781728181394

In view of the problems of low equipment integration, difficult equipment operation, and high technical threshold existing in the current stage visual effect linkage control system, a highly integrated linkage control system for stage visual effect equipment, which is suitable for small and medium-sized performance venues, is proposed in this paper. This system can control the stage lighting and the playback of multi-channel and multi-format media content, and it is easy to control. The design scheme of the system is described in detail, and the feasibility of the system is verified through tests in this paper.

关键词： Visual effects Lighting Couplings control systems Libraries Software Process control

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Recent Few-Shot Object Detection Algorithms: A Survey with Performance Comparison

arXiv

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arXiv 2022年

作者： Liu, Tianying Zhang, Lu Wang, Yang Guan, Jihong Fu, Yanwei Zhao, Jiajia Zhou, Shuigeng Department of Computer Science and Technology Tongji University Shanghai201804 China The Project Management Office of China National Scientific Seafloor Observatory Tongji University Shanghai200092 China Shanghai Key Lab of Intelligent Information Processing The School of Computer Science Fudan University Shanghai200438 China Shanghai Key Lab of Intelligent Information Processing The School of Data Science Fudan University Shanghai200433 China Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing100074 China

The generic object detection (GOD) task has been successfully tackled by recent deep neural networks, trained by an avalanche of annotated training samples from some common classes. However, it is still non-trivial to generalize these object detectors to the novel long-tailed object classes, which have only few labeled training samples. To this end, the Few-Shot Object Detection (FSOD) has been topical recently, as it mimics the humans' ability of learning to learn, and intelligently transfers the learned generic object knowledge from the common heavy-tailed, to the novel long-tailed object classes. Especially, the research in this emerging field has been flourishing in recent years with various benchmarks, backbones, and methodologies proposed. To review these FSOD works, there are several insightful FSOD survey articles [58, 59, 74, 78] that systematically study and compare them as the groups of fine-tuning/transfer learning, and meta-learning methods. In contrast, we review the existing FSOD algorithms from a new perspective under a new taxonomy based on their contributions, i.e., data-oriented, model-oriented, and algorithm-oriented. Thus, a comprehensive survey with performance comparison is conducted on recent achievements of FSOD. Furthermore, we also analyze the technical challenges, the merits and demerits of these methods, and envision the future directions of FSOD. Specifically, we give an overview of FSOD, including the problem definition, common datasets, and evaluation protocols. The taxonomy is then proposed that groups FSOD methods into three types. Following this taxonomy, we provide a systematic review of the advances in FSOD. Finally, further discussions on performance, challenges, and future directions are presented. Copyright © 2022, The Authors. All rights reserved.

关键词： Object detection

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A Classification–Detection Approach of COVID-19 Based on Chest X-ray and CT by Using Keras Pre-Trained Deep Learning Models

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Computer Modeling in Engineering & Sciences 2020年第11期125卷 579-596页

作者： Xing Deng Haijian Shao Liang Shi Xia Wang Tongling Xie School of Computer Science Jiangsu University of Science and TechnologyZhenjiang212003China School of Automation Key Laboratory of Measurement and Control for CSEMinistry of EducationSoutheast UniversityNanjing210096China School of Computer Science and Communication Engineering Jiangsu UniversityZhenjiang212003China School of Information Science and Technology Nantong UniversityNantong226019China Department of Electrical and Computer Engineering National University of Singapore117583Singapore The People’s Hospital of RUGAO Nantong226500China

The Coronavirus Disease 2019(COVID-19)is wreaking havoc around the world,bring out that the enormous pressure on national health and medical staff *** of the most effective and critical steps in the fight against COVID-19,is to examine the patient’s lungs based on the Chest X-ray and CT generated by radiation *** this paper,five keras-related deep learning models:ResNet50,InceptionResNetV2,Xception,transfer learning and pre-trained VGGNet16 is applied to formulate an classification-detection approaches of *** benchmark methods SVM(Support Vector Machine),CNN(Conventional Neural Networks)are provided to compare with the classification-detection approaches based on the performance indicators,i.e.,precision,recall,F1 scores,confusion matrix,classification accuracy and three types of AUC(Area Under Curve).The highest classification accuracy derived by classification-detection based on 5857 Chest X-rays and 767 Chest CTs are respectively 84%and 75%,which shows that the keras-related deep learning approaches facilitate accurate and effective COVID-19-assisted detection.

关键词： COVID-19 detection deep learning transfer learning pre-trained models

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Recent progress of integrated circuits and optoelectronic chips

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Science China(information Sciences) 2021年第10期64卷 103-135页

作者： Yue HAO Shuiying XIANG Genquan HAN Jincheng ZHANG Xiaohua MA Zhangming ZHU Xingxing GUO Yahui ZHANG Yanan HAN Ziwei SONG Yan LIU Ling YANG Hong ZHOU Jiangyi SHI Wei ZHANG Min XU Weisheng ZHAO Biao PAN Yangqi HUANG Qi LIU Yimao CAI Jian ZHU Xin OU Tiangui YOU Huaqiang WU Bin GAO Zhiyong ZHANG Guoping GUO Yonghua CHEN Yong LIU Xiangfei CHEN Chunlai XUE Xingjun WANG Lixia ZHAO Xihua ZOU Lianshan YAN Ming LI School of Microelectronics Xidian University State Key Laboratory of Integrated Service Networks Xidian University National Integrated Circuit Innovation Center School of Microelectronics Fudan University School of Integrated Circuit Science and Engineering Beihang University China Center for Information Industry Development Frontier Institute of Chip and System Fudan University Institute of Microelectronics Peking University Nanjing Electronic Devices Institute State Key Laboratory of Functional Material for Informatics Shanghai Institute of Microsystem and Information Technology Chinese Academy of Sciences Institute of Microelectronics Tsinghua University Center for Carbon-based Electronics Department of Electronics Peking University CAS Key Laboratory of Quantum Information University of Science and Technology of China CAS Center for Excellence and Synergetic Innovation Center in Quantum Information and Quantum Physics University of Science and Technology of China Origin Quantum Computing Company Limited Key Laboratory of Flexible Electronics & Institute of Advanced Materials Nanjing Tech University State Key Laboratory of Electronic Thin Films and Integrated Devices School of Optoelectronic Science and EngineeringUniversity of Electronic Science and Technology of China National Laboratory of Solid State Microstructures & College of Engineering and Applied Sciences Nanjing University State Key Laboratory on Integrated Optoelectronics Institute of Semiconductors Chinese Academy of Sciences Center of Materials Science and Optoelectronics Engineering University of Chinese Academy of Sciences State Key Laboratory of Advanced Optical Communication Systems and Networks School of Electronics Engineering and Computer Science Peking University School of Electrical and Electronic Engineering Tiangong University Center for Information Photonics and Communications School of Information Science and TechnologySouthwest Jiaotong University School of Electronic Electrical and Communication Engineering

Integrated circuits(ICs) and optoelectronic chips are the foundation stones of the modern information society. The IC industry has been driven by the so-called "Moore's law" in the past 60 years, and now has entered the post Moore's law era. In this paper, we review the recent progress of ICs and optoelectronic chips. The research status, technical challenges and development trend of devices, chips and integrated technologies of typical IC and optoelectronic chips are focused on. The main contents include the development law of IC and optoelectronic chip technology, the IC design and processing technology, emerging memory and chip architecture, brain-like chip structure and its mechanism, heterogeneous integration, quantum chip technology, silicon photonics chip technology, integrated microwave photonic chip, and optoelectronic hybrid integrated chip.

关键词： integrated circuit semiconductor science and technology optoelectronic device and chip photonic integrated circuit wide bandgap semiconductors silicon photonics hybrid integration quantum chip integrated microwave photonic photonic neural computing

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Performance Analysis of Phase Pre-Configured Spatial Modulation Empowered by RIS With Discrete Phase Alphabet

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IEEE Transactions on Vehicular technology 2025年

作者： Liu, Chaowen Shi, Zhengmin Zheng, Tong-Xing Liu, Boyang Wen, Miaowen Wang, Wenjie Lu, Guangyue Xi'an University of Posts and Telecommunications Shaanxi Key Laboratory of Information Communication Network and Security Xi'an710121 China National Key Laboratory of Multi-domain Data Collaborative Processing and Control Xi'an710068 China Xi'an Jiaotong University School of Information and Communications Engineering Xi'an710049 China South China University of Technology School of Electronics and Information Engineering Guangzhou510641 China

In this paper, we are motivated to introduce and investigate a novel reconfigurable intelligent surface assisted phase preconfigured spatial modulation (RIS-PPSM) scheme, which can be employed to achieve reliability enhanced transmissions. In the RIS-PPSM scheme, pre-configured phases are injected at the transmitter, and the reflection coefficients are designed for the RIS with a practical discrete phase alphabet, such that the resolution of transmit antennas is increased, and hence the overall transmission performance is remarkably elevated. Upon utilizing the moment generating function based unified analysis framework, we deduce out the closed-form expressions for the average bit error probability upper bound and discrete input continuous-output memoryless channel capacity. Finally, simulation results are depicted to demonstrate the accuracy of the theoretical analysis and the superiority of the proposed RIS-PPSM. © 1967-2012 IEEE.

关键词： discrete phase alphabet performance analysis phase pre-configuration Reconfigurable intelligent surface (RIS) spatial modulation

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Stage actor positioning method based on realsense point cloud

Stage actor positioning method based on realsense point clou...

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2019 International Joint Conference on information, Media, and Engineering, IJCIME 2019

作者： Lv, Chaohui Yang, Lexuan Li, Min Yin, Jun School of Information and Communication Engineering Communication University of China China Key Laboratory of Acoustic Visual Technology and Intelligent Control System Ministry of Culture and Tourism Beijing China

ISBN: (纸本)9781728155869

A novel and convenient method for human positioning based on computer vision is proposed. The new camera Realsense D435 from Intel is used to provide richer and more effective visual information. The positioning problem can be simplified to the conversion problem between point cloud and space coordinate system. Experimental results indicated that only several test points were needed to establish the conversion relationship between the two coordinate systems, thereby obtaining the position of the person. The accuracy meets the demand of the stage performance. © 2019 IEEE.

关键词： Computer vision

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Robust Beamforming Based on Covariance Matrix Reconstruction and ADMM

Robust Beamforming Based on Covariance Matrix Reconstruction...

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IEEE International Conference on Radar

作者： Pengcheng Gong Zhaobin Wang Kaiyan Xu School of Information and Communication Engineering University of Electronic Science and Technology of China Chengdu China School of Computer Science and Engineering Wuhan Institute of Technology Wuhan China Hubei Key Laboratory for High-efficiency Utilization of Solar Energy and Operation Control of Energy Storage System Hubei University of Technology Wuhan China

ISBN: (纸本)9781665468893

Considering at the issue that the performance of the traditional beamforming algorithm will decrease sharply when the disturbance occurs at the disturbed position and the steering vector mismatch occurs, a new robust beamforming method based on covariance matrix reconstruction and Alternating Direction Method of Multipliers (ADMM) is proposed. Firstly, based on the maximum output power criterion of beamformers, an optimization model is designed to solve the optimal steering vector. Then, the covariance matrix is reconstructed by using the defined interference range to widen the nullity and enhance the anti-motion interference ability of the system. Then, for the quadratic inequality constraint problem of the steering vector, this paper uses ADMM to solve the model iteratively, and obtains the specific solution of the steering vector in each iteration. In addition, the complexity of the algorithm is also analyzed. The experimental results show that, compared with the existing beamforming algorithms, the proposed method Widen the width of zero notch in the interference area, improves the anti-interference performance of the beam, and can well correct the mismatched steering vector.

关键词： systematics Array signal processing Interference Radar Resists Convex functions Robustness

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Towards Secure Semantic Transmission In the Era of GenAI: A Diffusion-based Framework

arXiv

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arXiv 2025年

作者： He, Boxiang Chen, Zihan Luo, Junshan Liu, Chuanhong Wang, Shilian Wang, Fanggang Quek, Tony Q.S. College of Electronic Science and Technology National University of Defense Technology Changsha410073 China Information Systems Technology and Design Singapore University of Technology and Design Singapore Beijing Key Laboratory of Network System Architecture and Convergence School of Information and Communication Engineering Beijing University of Posts and Telecommunications Beijing100876 China School of Electronic and Information Engineering Beijing Jiaotong University Beijing100044 China

Semantic communication, due to its focus on the transmitting meaning rather than the raw bit data, poses unique security challenges compared to the traditional communication systems. In particular, semantic communication systems are vulnerable to the malicious attacks that focus on the semantic layer, with the intention of understanding or distorting the intended meaning of the transmitted privacy data. Diffusion models, a class of generative artificial intelligence (GenAI), are well-suited for ensuring data security to attack. Through iteratively adding and then removing noise, diffusion models can generate meaningful information despite the presence of the unknown noise. This article proposes a diffusion-based framework to enhance the security of semantic transmission for the attacks including eavesdropping and jamming. Specifically, the proposed framework incorporates both the artificial noise and natural channel noise into the forward process of the diffusion models during the semantic transmission, with the reverse process used to remove noise at the legitimate receiver. In the eavesdropping scenarios, the artificial noise is the friendly noise designed to prevent semantic eavesdropping. In the jamming scenarios, the artificial noise is the malicious jamming generated by the jammer, which disrupts the semantic transmission. The case studies show that the proposed diffusion-based framework is promising in securing the semantic transmission. We also consolidate several broad research directions associated with the proposed framework. Copyright © 2025, The Authors. All rights reserved.

关键词： Electroosmosis

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