检索结果-内蒙古大学图书馆

29th International Joint Conference on Artificial Intelligence, IJCAI 2020

作者： Li, Chao Liu, Baolin Wei, Jianguo College of Intelligence and Computing Tianjin Key Laboratory of Cognitive Computing and Application Tianjin University Tianjin China School of Computer and Communication Engineering University of Science and Technology Beijing Beijing China

ISBN: (纸本)9780999241165

Using a convolutional neural network to build visual encoding and decoding models of the human brain is a good starting point for the study on relationship between deep learning and human visual cognitive mechanism. However, related studies have not fully considered their differences. In this paper, we assume that only a portion of neural network features is directly related to human brain signals, which we call shared features. In the encoding process, we extract shared features from the lower and higher layers of the neural network, and then build a non-negative sparse map to predict brain activities. In the decoding process, we use back-propagation to reconstruct visual stimuli, and use dictionary learning and a deep image prior to improve the robustness and accuracy of the algorithm. Experiments on a public fMRI dataset confirm the rationality of the encoding models, and comparing with a recently proposed method, our reconstruction results obtain significantly higher accuracy. © 2020 Inst. Sci. inf., Univ. Defence in Belgrade. All rights reserved.

关键词： Signal encoding

来源：评论

学校读者我要写书评

暂无评论

Holographic performances of graphene oxide photopolymer [Invited] 10

Holographic performances of graphene oxide photopolymer [Inv...

引用

Holography, Diffractive Optics, and applications X 2020

作者： Zhang, Yaping Zhu, Xufeng Poon, Ting-Chung Key Laboratory of Laser Information Processing Technology and Application Kunming University of Science and Technology Kunming650500 China Bradley Department of Electrical and Computer Engineering Virginia Tech BlacksburgVA24061 United States

ISBN: (纸本)9781510639171

Graphene oxide (GO) is a precursor material for producing graphene. The electrical and optical properties of GO can be modified by reduction of the oxygen-containing groups. In this report, we have prepared graphene oxide polymers (GO-polymer) with different vol. % of GO and reduced the polymer by direct laser writing. We have found the refractive indexmodulation ofthe GO-polymerup to for15 vol.%. © 2020 SPIE.

关键词： Graphene

来源：评论

学校读者我要写书评

暂无评论

Smart Contract Service Optimization in Blockchain-Cloud Collaborative Computing

Smart Contract Service Optimization in Blockchain-Cloud Coll...

引用

International Conference on Mobile Data Management

作者： Ji Wan Kai Hu Jie Li Hao Su Qingshun Wu Mingyuan Li Libo Feng Yan Pan State Key Laboratory of Software Development Environment Beihang University Beijing China Yunnan Key Laboratory of Blockchain Application Technology Beihang Yunnan Innovation Institute Kunming China School of Computer and Artificial Intelligence Zhengzhou University Zhengzhou China The First Affiliated Hospital of Zhengzhou University Zhengzhou China National Pilot School of Software Yunnan University Kunming China Institute of Software China Industrial Control Systems Cyber Emergency Response Team Beijing China

Smart contract is a trusted service provided on the blockchain, while cloud service is a traditional service mode with a large number of resources. The combination of the blockchain and cloud service is of great significance to the trusted expansion of services and the access to services inside and outside the blockchain. In this paper, we study the smart contract extension service in blockchain-cloud collaborative computing. The service module decoupling method of smart contract is proposed, and the parallel execution algorithm of smart contract service is designed, which improves the execution efficiency of smart contract service. Finally, this paper designs a secure data interaction method of smart contract and cloud service, which helps to maintain the data consistency between cloud computing and blockchain. The experimental results show that the proposed method can save at most 42.13% of the running time, and it can promote the data consistency between the cloud service and the blockchain.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Large-Scale Target Detection and Classification Based on Improved Candidate Regions 11th

Large-Scale Target Detection and Classification Based on Imp...

引用

11th International Conference on Image and Graphics, ICIG 2021

作者： Xi, Runping Han, Qianqian Jia, Gaoyun Kou, Xuefeng School of Computer Science and Techology Northwest Polytechnical University Xi’an710072 China National Engineering Laboratory of Integrated Aero-Space-Ground-Ocean Big Data Application Technology Xi’an710129 China Shaanxi Provincial Key Laboratory of Speech and Image Information Processing Xi’an710129 China Shaanxi Baocheng Aviation instrument Co. Ltd. Baoji China

ISBN: (纸本)9783030873578

Target detection of aerial images has become a frontier subject of concern in the image processing field. Using existing method to detect and classify large-scale building objects in aerial images, the accuracy is still a little low. This is mainly because the current method does not make full use of the prior information of the target to be detected, so there are too much redundant information in the candidate box. In this paper, our own dataset were built and then utilize the Hough transform to filter out the images that may exist in the sequence image. For images with dense lines or circles, it is possible that there is an artificial building target which will be detected, otherwise it is excluded directly. Besides, this paper exploits significance analysis from the filtered image and then extract the area of interest where the potential target is located. The results of the above-mentioned processing lay a good foundation for the subsequent detection and classification which can help improve the accuracy. © 2021, Springer Nature Switzerland AG.

关键词： Antennas

来源：评论

学校读者我要写书评

暂无评论

A Reference Vector-Assisted Many-Objective Optimization Algorithm with Adaptive Niche Dominance Relation

引用

Intelligent Automation & Soft Computing 2024年第2期39卷 189-211页

作者： Fangzhen Ge Yating Wu Debao Chen Longfeng Shen School of Computer Science and Technology Huaibei Normal UniversityHuaibei340604China School of Physic and Electronic Information Huaibei Normal UniversityHuaibei340604China Anhui Engineering Research Center for Intelligent Computing and Application on Cognitive Behavior(ICACB) Huaibei Normal UniversityHuaibei340604China Anhui Province Key Laboratory of Intelligent Computing and Applications Huaibei Normal UniversityHuaibei340604China Institute of Artificial Intelligence Hefei Comprehensive National Science CenterHefei230000China

It is still a huge challenge for traditional Pareto-dominatedmany-objective optimization algorithms to solve manyobjective optimization problems because these algorithms hardly maintain the balance between convergence and diversity and can only find a group of solutions focused on a small area on the Pareto front,resulting in poor performance of those *** this reason,we propose a reference vector-assisted algorithmwith an adaptive niche dominance relation,for short *** new dominance relation forms a niche based on the angle between candidate *** comparing these solutions,the solutionwith the best convergence is found to be the non-dominated solution to improve the selection *** reproduction,a mutation strategy of k-bit crossover and hybrid mutation is used to generate high-quality *** 23 test problems with up to 15-objective,we compared the proposed algorithm with five state-of-the-art *** experimental results verified that the proposed algorithm is competitive.

关键词： Many-objective optimization evolutionary algorithm Pareto dominance reference vector adaptive niche

来源：评论

学校读者我要写书评

暂无评论

ATASI-Net: An Efficient Sparse Reconstruction Network for Tomographic SAR Imaging with Adaptive Threshold

arXiv

引用

arXiv 2022年

作者： Wang, Muhan Zhang, Zhe Qiu, Xiaolan Gao, Silin Wang, Yue Suzhou Key Laboratory of Microwave Imaging Processing and Application Technology China Suzhou Aerospace Information Research Institute Jiangsu Suzhou China Aerospace Information Research Institute Chinese Academy of Sciences China School of Electronic Electrical and Communication Engineering University of Chinese Academy of Sciences Beijing China The Key Laboratory of Technology in Geo-spatial Information Processing and Application System Chinese Academy of Sciences Beijing China Electrical and Computer Engineering Department George Mason University FairfaxVA United States

Tomographic SAR technique has attracted remarkable interest for its ability of three-dimensional resolving along the elevation direction via a stack of SAR images collected from different cross-track angles. The emerged compressed sensing (CS)-based algorithms have been introduced into TomoSAR considering its super-resolution ability with limited samples. However, the conventional CS-based methods suffer from several drawbacks, including weak noise resistance, high computational complexity, and complex parameter fine-tuning. Aiming at efficient TomoSAR imaging, this paper proposes a novel efficient sparse unfolding network based on the analytic learned iterative shrinkage thresholding algorithm (ALISTA) architecture with adaptive threshold, named Adaptive Threshold ALISTA-based Sparse Imaging Network (ATASI-Net). The weight matrix in each layer of ATASI-Net is pre-computed as the solution of an offline optimization problem, leaving only two scalar parameters to be learned from data, which significantly simplifies the training stage. In addition, adaptive threshold is introduced for each azimuth-range pixel, enabling the threshold shrinkage to be not only layer-varied but also element-wise. Moreover, the final learned thresholds can be visualized and combined with the SAR image semantics for mutual feedback. Finally, extensive experiments on simulated and real data are carried out to demonstrate the effectiveness and efficiency of the proposed method. Copyright © 2022, The Authors. All rights reserved.

关键词： Semantics

来源：评论

学校读者我要写书评

暂无评论

Technological Knowledge Flow Forecasting through A Hierarchical Interactive Graph Neural Network

Technological Knowledge Flow Forecasting through A Hierarchi...

引用

IEEE International Conference on Data Mining (ICDM)

作者： Huijie Liu Han Wu Le Zhang Runlong Yu Ye Liu Chunli Liu Qi Liu Enhong Chen Anhui Province Key Laboratory of Big Data Analysis and Application School of Data Science & School of Computer Science and Technology University of Science and Technology of China School of Management Hefei University of Technology China

ISBN: (纸本)9781665423991

With the accelerated technology development, technological trend forecasting through patent mining has become a hot issue for high-tech companies. In this term, extensive attention has been attracted to forecasting technological knowledge flows (TKF), i.e., predicting the directional flows of knowledge from one technological field to another. However, existing studies either rely on labor intensive empirical analysis or do not consider the intrinsic characteristics inherent in TKF, including the double-faced aspects (i.e., act as both the source and target) of technology nodes, multiple complex relationships among different technologies, and dynamics of the TKF process. To this end, in this paper, we make a further study and propose a data-driven solution, i.e., a Hierarchical Interactive Graph Neural Network (HighTKF), to automatically find the potential flow trends of technologies. Specifically, HighTKF makes final predictions through two kinds of representations of each technology node (a diffusion vector and an absorption vector), which is realized by three components: High-Order Interaction Module (HOI), Hierarchical Delivery Module (HD) and technology Flow Tracing Module (TFT). For one thing, HOI and HD aim to model high-order network relationships and hierarchical relationships among technologies. For another, TFT is designed for capturing the dynamic feature evolution of technologies with the above relations involved. Also, we design a hybrid loss function and propose a new evaluation metric for better predicting the unprecedented flows between technologies. Finally, we conduct extensive experiments on a real-world patent dataset, the results verify the effectiveness of our approach and reveal some interesting phenomenons on technological knowledge flow trends.

关键词： Measurement Knowledge engineering Patents Databases Predictive models Market research Graph neural networks

来源：评论

学校读者我要写书评

暂无评论

Towards Variable-Length Textual Adversarial Attacks

arXiv

引用

arXiv 2021年

作者： Guo, Junliang Zhang, Zhirui Zhang, Linlin Xu, Linli Chen, Boxing Chen, Enhong Luo, Weihua Anhui Province Key Laboratory of Big Data Analysis and Application School of Computer Science and Technology University of Science and Technology of China China Alibaba DAMO Academy Zhejiang University China

Adversarial attacks have shown the vulnerability of machine learning models, however, it is non-trivial to conduct textual adversarial attacks on natural language processing tasks due to the discreteness of data. Most previous approaches conduct attacks with the atomic replacement operation, which usually leads to fixed-length adversarial examples and therefore limits the exploration on the decision space. In this paper, we propose variable-length textual adversarial attacks (VL-Attack) and integrate three atomic operations, namely insertion, deletion and replacement, into a unified framework, by introducing and manipulating a special blank token while attacking. In this way, our approach is able to more comprehensively find adversarial examples around the decision boundary and effectively conduct adversarial attacks. Specifically, our method drops the accuracy of IMDB classification by 96% with only editing 1.3% tokens while attacking a pre-trained BERT model. In addition, fine-tuning the victim model with generated adversarial samples can improve the robustness of the model without hurting the performance, especially for length-sensitive models. On the task of non-autoregressive machine translation, our method can achieve 33.18 BLEU score on IWSLT14 German-English translation, achieving an improvement of 1.47 over the baseline model. Copyright © 2021, The Authors. All rights reserved.

关键词： Natural language processing systems

来源：评论

学校读者我要写书评

暂无评论

Decentralized Optimization on Compact Submanifolds by Quantized Riemannian Gradient Tracking

引用

IEEE Transactions on Signal Processing 2025年 73卷 1851-1861页

作者： Chen, Jun Liu, Lina Zhu, Tianyi Liu, Yong Dai, Guang Jiang, Yunliang Tsang, Ivor W. Zhejiang Normal University National Special Education Resource Center for Children with Autism Hangzhou311231 China Zhejiang Normal University School of Computer Science and Technology Jinhua321004 China China Mobile Research Institute Beijing100032 China Zhejiang University Institute of Cyber-Systems and Control Hangzhou310027 China State Grid Corporation of China SGIT AI Lab China Zhejiang Normal University Zhejiang Key Laboratory of Intelligent Education Technology and Application Jinhua321004 China Huzhou University School of Information Engineering Huzhou313000 China Centre for Frontier Artificial Intelligence Research A*STAR Singapore

This paper considers the problem of decentralized optimization on compact submanifolds, where a finite sum of smooth (possibly non-convex) local functions is minimized by n agents forming an undirected and connected graph. However, the efficiency of distributed optimization is often hindered by communication bottlenecks. To mitigate this, we propose the Quantized Riemannian Gradient Tracking (Q-RGT) algorithm, where agents update their local variables using quantized gradients. The introduction of quantization noise allows our algorithm to bypass the constraints of the accurate Riemannian projection operator (such as retraction), further improving iterative efficiency. To the best of our knowledge, this is the first algorithm to achieve an O(1/K) convergence rate in the presence of quantization, matching the convergence rate of methods without quantization. Additionally, we explicitly derive lower bounds on decentralized consensus associated with a function of quantization levels. Numerical experiments demonstrate that Q-RGT performs comparably to non-quantized methods while reducing communication bottlenecks and computational overhead. © 1991-2012 IEEE.

关键词： Iterative methods

来源：评论

学校读者我要写书评

暂无评论

Dual Conditioned Motion Diffusion for Pose-Based Video Anomaly Detection

arXiv

引用

arXiv 2024年

作者： Wang, Hongsong Xu, Andi Ding, Pinle Gui, Jie School of Computer Science and Engineering Southeast University Nanjing210096 China Key Laboratory of New Generation Artificial Intelligence Technology and Its Interdisciplinary Applications Southeast University Ministry of Education China School of Cyber Science and Engineering Southeast University Nanjing210096 China Engineering Research Center of Blockchain Application Supervision And Management Southeast University Ministry of Education China Purple Mountain Laboratories Nanjing210000 China

Video Anomaly Detection (VAD) is essential for computer vision research. Existing VAD methods utilize either reconstruction-based or prediction-based frameworks. The former excels at detecting irregular patterns or structures, whereas the latter is capable of spotting abnormal deviations or trends. We address pose-based video anomaly detection and introduce a novel framework called Dual Conditioned Motion Diffusion (DCMD), which enjoys the advantages of both approaches. The DCMD integrates conditioned motion and conditioned embedding to comprehensively utilize the pose characteristics and latent semantics of observed movements, respectively. In the reverse diffusion process, a motion transformer is proposed to capture potential correlations from multi-layered characteristics within the spectrum space of human motion. To enhance the discriminability between normal and abnormal instances, we design a novel United Association Discrepancy (UAD) regularization that primarily relies on a Gaussian kernel-based time association and a self-attention-based global association. Finally, a mask completion strategy is introduced during the inference stage of the reverse diffusion process to enhance the utilization of conditioned motion for the prediction branch of anomaly detection. Extensive experiments on four datasets demonstrate that our method dramatically outperforms state-of-the-art methods and exhibits superior generalization performance. © 2024, CC BY-SA.

关键词： Motion capture

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：