检索结果-内蒙古大学图书馆

signal, Information and Data processing (ICSIDP), IEEE International Conference on

作者： Hao Wu Hao Zheng Yinghui Zhang Junkun Yan College of Electronic Information Engineering Inner Mongolia University Hohhot China Inner Mongolia Key Laboratory of Intelligent Communication and Sensing and Signal Processing Inner Mongolia University Hohhot China National Key Laboratory of Radar Signal Processing Xidian University Xian China

ISBN: (数字)9798331515669

ISBN: (纸本)9798331515676

Intercepting and repeatedly retransmitting radar signals, interrupted sampling repeater jamming (ISRJ) generates higher power false signals that can seriously affect radar operation. To combat this interference, a scheme for countering ISRJ with Doppler frequency shifts by designing a multiple input multiple output (MIMO) radar with pulse train encoding and decoding is proposed. On the one hand, the scheme can suppress the pulse compression sidelobes of the target and ISRJ with Doppler frequency shifts. On the other hand, a detection matrix is designed to identify spurious peaks formed by interfering signals. Finally, the proposed scheme can accurately obtain target and jamming information in the environment while satisfying the constant mode (CM) constraints.

关键词： Hands MIMO radar Interference Repeaters Encoding MIMO Doppler radar Decoding Doppler effect Jamming

来源：评论

学校读者我要写书评

暂无评论

Spatio-Temporal Context Modeling for Road Obstacle Detection 1

引用

4th International Conference on Machine Learning for Cyber Security, ML4CS 2022

作者： Wu, Xiuen Wang, Tao Liang, Lingyu Li, Zuoyong Ching, Fum Yew College of Computer and Data Science Fuzhou University Fuzhou350108 China Fujian Provincial Key Laboratory of Information Processing and Intelligent Control Minjiang University Fuzhou350108 China The Key Laboratory of Cognitive Computing and Intelligent Information Processing of Fujian Education Institutions Wuyi University Wuyishan354300 China School of Electronic and Information Engineering South China University of Technology Guangzhou510641 China Ministry of Education Key Laboratory of Computer Network and Information Integration Southeast University Nanjing211189 China Guangzhou510320 China Penang11800 Malaysia

ISBN: (数字)9783031200960

ISBN: (纸本)9783031200953

Road obstacle detection is an important problem for vehicle driving safety. In this paper, we aim to obtain robust road obstacle detection based on spatio-temporal context modeling. Firstly, a data-driven spatial context model of the driving scene is constructed with the layouts of the training data. Then, obstacles in the input image are detected via the state-of-the-art object detection algorithms, and the results are combined with the generated scene layout. In addition, to further improve the performance and robustness, temporal information in the image sequence is taken into consideration, and the optical flow is obtained in the vicinity of the detected objects to track the obstacles across neighboring frames. Qualitative and quantitative experiments were conducted on the Small Obstacle Detection (SOD) dataset and the Lost and Found dataset. The results indicate that our method with spatio-temporal context modeling is superior to existing methods for road obstacle detection. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Object detection

来源：评论

学校读者我要写书评

暂无评论

Improving Transferability Reversible Adversarial Examples Based on Flipping Transformation

Improving Transferability Reversible Adversarial Examples Ba...

引用

作者： Youqing Fang Jingwen Jia Yuhai Yang Wanli Lyu Key Lab of Intelligent Computing and Signal Processing of Ministry of Education School of Computer Science and Technology Anhui University

Adding subtle perturbations to an image can cause the classification model to misclassify, and such images are called adversarial examples. Adversarial examples threaten the safe use of deep neural networks, but when combined with reversible data hiding(RDH) technology, they can protect images from being correctly identified by unauthorized models and recover the image lossless under authorized models. Based on this, the reversible adversarial example(RAE) is rising. However, existing RAE technology focuses on feasibility, attack success rate and image quality, but ignores transferability and time complexity. In this paper,we optimize the data hiding structure and combine data augmentation technology,which flips the input image in probability to avoid overfitting phenomenon on the dataset. On the premise of maintaining a high success rate of white-box attacks and the image's visual quality, the proposed method improves the transferability of reversible adversarial examples by approximately 16% and reduces the computational cost by approximately 43% compared to the state-of-the-art method. In addition, the appropriate flip probability can be selected for different application scenarios.

关键词：

来源：评论

学校读者我要写书评

暂无评论

On some properties of the bibasic Humbert hypergeometric functions Ξ_(1) and Ξ_(2)

引用

Applied Mathematics(A Journal of Chinese Universities) 2023年第4期38卷 614-630页

作者： CAI Qing-bo Ghazi S.Khammash Shimaa I.Moustafa Ayman Shehata Provincial Key Laboratory of Data-Intensive Computing Key Laboratory of Intelligent Computing and Information ProcessingSchool of Mathematics and Computer ScienceQuanzhou Normal UniversityQuanzhou 362000China Department of Mathematics Al-Aqsa UniversityGazaGaza StripPalestine Department of Mathematics Faculty of ScienceAssiut UniversityAssiut 71516Egypt Department of Mathematics Unaizah College of Science and ArtsUnaizah 56264Qassim UniversityBuraydah 52571QassimSaudi Arabia

The main object of this paper is to deduce the bibasic Humbert functions Ξ_(1) and Ξ_(2)Some interesting results and elementary summations technique that was successfully employed,q-recursion,q-derivatives relations,the q-differential recursion relations,the q-integral representations for Ξ_(1) and Ξ_(2)are *** summation formula derives a list of p-analogues of transformation formulas for bibasic Humbert functions that have been studied,also some hypergeometric functions properties of some new interesting special cases have been given.

关键词： q-calculus bibasic Humbert hypergeometric functions q-derivative

来源：评论

学校读者我要写书评

暂无评论

CLIMS++: Cross Language Image Matching with Automatic Context Discovery for Weakly Supervised Semantic Segmentation

引用

International Journal of computer Vision 2025年 1-20页

作者： Xie, Jinheng Deng, Songhe Hou, Xianxu Luo, Zhaochuan Shen, Linlin Huang, Yawen Zheng, Yefeng Shou, Mike Zheng Computer Vision Institute School of Computer Science and Software Engineering Shenzhen University Shenzhen518060 China Department of Computer Science Wenzhou-Kean University Wenzhou325060 China Guangdong Provincial Key Laboratory of Intelligent Information Processing Shenzhen University Shenzhen China Show Lab National University of Singapore Singapore639798 Singapore School of AI and Advanced Computing Xi’an Jiaotong-Liverpool University Suzhou215400 China Jarvis Research Center Tencent YouTu Lab Shenzhen518703 China

While promising results have been achieved in weakly-supervised semantic segmentation (WSSS), limited supervision from image-level tags inevitably induces discriminative reliance and spurious relations between target classes and background regions. Thus, Class Activation Map (CAM) usually tends to activate discriminative object regions and falsely includes lots of class-related backgrounds. Without pixel-level supervisions, it could be very difficult to enlarge the foreground activation and suppress those false activation of background regions. In this paper, we propose a novel framework of Cross Language Image Matching with Automatic Context Discovery (CLIMS++), based on the recently introduced Contrastive Language-Image Pre-training (CLIP) model, for WSSS. The core idea of our framework is to introduce natural language supervision to activate more complete object regions and suppress class-related background regions in CAM. In particular, we design object, background region, and text label matching losses to guide the model to excite more reasonable object regions of each category. In addition, we propose to automatically find spurious relations between foreground categories and backgrounds, through which a background suppression loss is designed to suppress the activation of class-related backgrounds. The above designs enable the proposed CLIMS++ to generate a more complete and compact activation map for the target objects. Extensive experiments on PASCAL VOC 2012 and MS COCO 2014 datasets show that our CLIMS++ significantly outperforms the previous state-of-the-art methods. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2025.

关键词： Semantic Segmentation

来源：评论

学校读者我要写书评

暂无评论

Fully Hyperbolic Rotation for Knowledge Graph Embedding 27

Fully Hyperbolic Rotation for Knowledge Graph Embedding

引用

27th European Conference on Artificial Intelligence, ECAI 2024

作者： Liang, Qiuyu Wang, Weihua Bao, Feilong Gao, Guanglai College of Computer Science Inner Mongolia University Hohhot China National and Local Joint Engineering Research Center of Intelligent Information Processing Technology for Mongolian Hohhot China Inner Mongolia Key Laboratory of Multilingual Artificial Intelligence Technology Hohhot China

ISBN: (纸本)9781643685489

Hyperbolic rotation is commonly used to effectively model knowledge graphs and their inherent ***, existing hyperbolic rotation models rely on logarithmic and exponential mappings for feature *** models only project data features into hyperbolic space for rotation, limiting their ability to fully exploit the hyperbolic *** address this problem, we propose a novel fully hyperbolic model designed for knowledge graph *** of feature mappings, we define the model directly in hyperbolic space with the Lorentz *** model considers each relation in knowledge graphs as a Lorentz rotation from the head entity to the tail *** adopt the Lorentzian version distance as the scoring function for measuring the plausibility of *** results on standard knowledge graph completion benchmarks demonstrated that our model achieves competitive results with fewer *** addition, our model get the state-ofthe-art performance on datasets of CoDEx-s and CoDEx-m, which are more diverse and challenging than *** code is available at https://***/llqy123/FHRE. © 2024 The Authors.

关键词： Knowledge graph

来源：评论

学校读者我要写书评

暂无评论

Image Quality Assessment Method Based on Cross-Modal 20th

Image Quality Assessment Method Based on Cross-Modal

引用

20th Pacific Rim International Conference on Artificial Intelligence, PRICAI 2023

作者： Long, Teng Chen, Li Wang, Yubo School of Computer Science and Technology Wuhan University of Science and Technology Hubei Wuhan430065 China Hubei Province Key Laboratory of Intelligent Information Processing and Real-time Industrial System Wuhan University of Science and Technology Hubei Wuhan430065 China

ISBN: (纸本)9789819970247

Deep learning methods have achieved remarkable results in the direction of image quality assessment tasks. However, most of the related studies focus only on image unimodal, ignoring the potential advantages that come with the development of cross-modal techniques. Cross-modal models have implied a wealth of information, which provides new research directions and possibilities in the field of image quality assessment. In this paper, the feasibility of cross-modal models in image quality assessment is first explored for the image quality binary classification task. Subsequently, the optimization prompting method is combined with the tuning of the image encoder in the cross-modal model so that the cross-modal model can be used for image quality assessment scoring. To verify the feasibility of the cross-modal model on the image quality assessment task, an empirical analysis was conducted on the binary image quality dataset PQD, and it was found that the F1 score improved by 18% over the baseline model. Further, we propose an adaptive cross-modal image quality assessment method AC-IQA. On the image quality scoring dataset, compared with the previous optimal methods, AC-IQA improves the PLCC and SROCC metrics on the TID2013 dataset by 5.5% and 9.5%, respectively, and on the KADID dataset by 6.2% and 5.2%. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd 2024.

关键词： Image quality

来源：评论

学校读者我要写书评

暂无评论

Cascade Temporal Convolutional Network for Multitask Learning 6

Cascade Temporal Convolutional Network for Multitask Learnin...

引用

6th International Conference on Artificial Intelligence and Big Data, ICAIBD 2023

作者： Zhang, Huiyun Huang, Heming Han, Henry Baylor University School of Engineering and Computer Science Department of Computer Science United States Qinghai Normal University School of Computer Science Xining China Qinghai Normal University The State Key Laboratory of Tibetan Intelligent Information Processing and Application School of Computer Science Xining China

ISBN: (纸本)9781665491259

Multi-task learning (MTL) is a powerful technique in machine learning that enables the simultaneous training of multiple tasks. In this paper, we propose a novel MTL approach for the recognition of emotions, speakers, and gender in speech signals. Our approach presents a novel deep learning model called the Cascade Temporal Convolutional Network (CTCN to handle MTL efficiently. CTCN is designed to effectively improve the parallel processing ability of the model in multitasking learning. It provides an effective solution for improving the performance of deep learning in multitasking scenarios. CTCN is particularly adept at processing sequences of data with varying lengths and extracting features that are relevant to multiple tasks. Our experimental results demonstrate that the proposed CTCN approach for MTL achieves significantly superior performance on all tasks on benchmark datasets compared to other deep learning models. This study will inspire more future work in the MTL field. © 2023 IEEE.

关键词： Speech recognition

来源：评论

学校读者我要写书评

暂无评论

Research on CMUTs Design with Different Cell Arrangements

引用

Recent Patents on Engineering 2024年第1期18卷 110-118页

作者： Cao, Xuewen Yu, Yuanyu Liu, Xin Ma, Jingyi Zhang, Hua Wang, Lijia Intelligent Manufacturing Institute Hebei Vocational University of Industry and Technology Shi Jiazhuang050091 China School of Artificial Intelligence Neijiang Normal University Neijiang641100 China State Key Laboratory of Analog and Mixed-Signal VLSI University of Macau Macau 999078 China Department of Electrical and Computer Engineering Faculty of Science and Technology University of Macau Macau 999078 China

Background: Capacitive micromachined ultrasonic transducers (CMUTs) is a promising component of mechanical-electrical-acoustical conversion, which shows valuable applications in non-distructive testing and obstacle detection fields. In order to study the influence of dimension parameters on the directivity of CMUTs, the three-dimensional multi-physics coupling model is proposed for CMUTs in this paper. Methods: The model combines multiple physical fields through finite element method (FEM), which is more efficient and accurate. The influence of dimension parameters on the transducer is studied from two aspects: the pitch between adjacent cells and cell number, respectively. Results: When increasing the pitch, the directivity becomes better if the pitch is less than half of the wavelength, the grating lobe and side lobe are aroused. However, the bandwidth at-3dB is reduced by up to 71.1% at the same time. When increasing the cell number, the better the direcitvity, while the change of the cell number has little effect on the bandwidth of the array. However, 5.4% frequency shift was caused due to the effective mass change of the transducer. Conclusion: In this study, a 3D model based on FEM is proposed for the influence of dimension parameter on CMUTs. The simulation results indicate that the directivity can be enhanced by chang-ing the dimension. At the same time, it also introduces other performance issues, such as bandwidth decrease and frequency shift through this approach. Therefore, the simulation proposed the guidance of CMUTs performance optimization and patented technology application work in the future. © 2024, Bentham Science Publishers. All rights reserved.

关键词： Finite element method

来源：评论

学校读者我要写书评

暂无评论

Path Planning based on Reinforcement Learning with Improved APF model for Synergistic Multi-UAVs 26

Path Planning based on Reinforcement Learning with Improved ...

引用

26th International Conference on computer Supported Cooperative Work in Design, CSCWD 2023

作者： Ding, Qun Xu, Xiaolong Gui, Wenming Jiangsu Key Laboratory of Big Data Security & Intelligent Processing Nanjing210023 China Nanjing University of Posts and Telecommunications School of Computer Science Nanjing210023 China Jinling Institute of Technology School of Computer Science Nanjing211169 China

ISBN: (纸本)9798350331684

As the emerging technology of Unmanned Aerial Vehicles (UAVs) becomes mature, UAVs are widely used in environmental monitoring, communication and other fields. In view of this, this paper analyzed the task of synergistic multi-UAVs exploration of unknown environments, and proposed a path planning method for them based on reinforcement learning. Firstly, the path planning task of the UAVs was divided into two parts: the path travel strategy module and the information exploration strategy module. Models of the two modules were based on the Deep Deterministic Policy Gradient algorithm (DDPG), and an improved Artificial Potential Field (APF) force traction mechanism was introduced in the path travel strategy module. Its aim was to assist in guiding the generation of UAV flight path trajectories. Also it could enhance the learning capability of the model. The path travel strategy module would generate the complete flight path of the whole cluster in a distributed manner. A series of temporary target points provided by the information exploration strategy module helped. In maps with 21.5%, 25.3% and 29.6% of obstacles, multi-UAVs could achieve 84.2%, 76.7% and 69.9% of environmental exploration by the designed method. Compared with the APF method, the A star method and the Breath First Search (BFS) method, the proposed method is not only able to plan feasible paths in a more complex map model, but also the curvature of the planned paths is smoother, thus achieving the goal of reducing the energy cost of UAVs. © 2023 IEEE.

关键词： Reinforcement learning

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：