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IEEE International Conference on Electronic Information and Communication Technology (ICEICT)

作者： Junwei Qi Yuhao Deng Qingchun Wang Zhen Yang Yingsong Li College of Information and Communication Engineering Harbin Engineering University Harbin China College of Computer Science and Technology Harbin Engineering University Harbin China Shanghai Yanding Information Technology Co. Ltd. Shanghai China Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education Anhui University China

We present a no-reference image-quality - assessment algorithm based on active reasoning module. This algorithm has three modules: the feature extraction module, the active reasoning module, and the quality assessment module. The active reasoning module incorporates the generator component of the generative adversarial network and enhances its structure with the Res2Net architecture. By integrating this module into the backbone feature extraction network, we improve the receptive field of each convolutional layer, enabling the network to capture information at different scales of the image. To preserve the texture information of the image, we input the gradient map of the distorted image, the distorted image itself, and the image features generated by the generator into the quality assessment module, which has a multi-feature regression networks. This module establishes a mapping model from image-feature to image-quality scores. We conducted experimental analysis of this algorithm on three widely used public datasets, confirming the excellent performance and superiorities of the presented algorithm. The results validate the effectiveness of the designed algorithm and its ability to assess image quality accurately.

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Singular Value Decomposition Compressed Ghost Imaging Based on Non-negative Constraints 11

Singular Value Decomposition Compressed Ghost Imaging Based ...

引用

2019第十一届数字图像处理国际会议

作者： Cheng Zhang Jun Tang Yuanyuan Zhu Meiqin Wang Qianwen Chen Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education Anhui University

ISBN: (数字)9781510630765

ISBN: (纸本)9781510630758

Compressed ghost imaging can effectively enhance the quality of original image from far fewer measurements,but due to the non-negativity of the measurement matrix,the recover quality is thus *** this paper,singular value decomposition compressed ghost imaging is proposed;First,the singular value decomposition be used to decompose the measurement matrix,and then the optimized measurement matrix and measurements are used to recover the original *** experiments verify the superiority of our proposed singular value decomposition compression ghost imaging method.

关键词： ghost imaging compressed ghost imaging singular value decomposition compressed ghost imaging

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Robust DOA Estimation Against Outliers via Joint Sparse Representation

TechRxiv

引用

TechRxiv 2023年

作者： Li, Yingsong Xiao, Wudang Zhao, Luyu Huang, Zhixiang Li, Qiang Li, Liping de Lamare, Rodrigo C. Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education Anhui University Anhui Hefei230601 China PUC-Rio Brazil University of York United Kingdom Gávea 22451-900 Brazil Department of Electronic Engineering University of York YorkYO10 5DD United Kingdom

Standard Direction of Arrival (DOA) estimation methods are typically derived based on the Gaussian noise assumption, making them highly sensitive to outliers. Therefore, in the presence of impulsive noise, the performance of these methods may significantly deteriorate. In this paper, we model impulsive noise as Gaussian noise mixed with sparse outliers. By exploiting their statistical differences, we propose a novel DOA estimation method based on sparse signal recovery (SSR). Furthermore, to address the issue of grid mismatch, we utilize an alternating optimization approach that relies on the estimated outlier matrix and the on-grid DOA estimates to obtain the off-grid DOA estimates. Simulation results demonstrate that the proposed method exhibits robustness against large outliers. © 2023, CC BY.

关键词： Direction of arrival

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Multi-Layer Visual Perception for No-Reference Image Quality Assessment

Multi-Layer Visual Perception for No-Reference Image Quality...

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IEEE International Conference on Electronic Information and Communication Technology (ICEICT)

作者： Junwei Qi Yingzhen Wang Qingchun Wang Yingsong Li College of Computer Science and Technology Harbin Engineering University Harbin China College of Information and Communication Engineering Harbin Engineering University Harbin China Shanghai Yanding Information Technology Co. Ltd. Shanghai China Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education Anhui University Hefei Anhui China

In this work, we propose a no-reference image quality evaluation approach, aiming to solve the problem that the traditional convolutional neural network is insufficient to express the global information of the image. Therefore, in order to make the captured image features have the coherence of global context information, we combine a Transformer structure widely used in NLP (natural language processing) with the traditional CNN to realize the attention mechanism in the human visual perception characteristics. Firstly, the self-attention mechanism of Transformer is used to learn the global representation of the image from the multi-layer features extracted from different levels of CNN. Additionally, to forecast the ultimate image quality score, the global and local attributes are combined. Finally, the proposed algorithm is evaluated on three public datasets commonly used in CSIQ [1], TID2013 [2] and LIVE [3]. Compared with eight traditional no-reference image quality evaluation algorithms and five methods based on deep learning, the proposed algorithm achieves competitive results.

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Tiny Object Tracking: A Large-scale Dataset and A Baseline

arXiv

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arXiv 2022年

作者： Zhu, Yabin Li, Chenglong Liu, Yao Wang, Xiao Tang, Jin Luo, Bin Huang, Zhixiang Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education Key Laboratory of Electromagnetic Environmental Sensing Anhui Higher Education Institutes Anhui Provincial Key Laboratory of Multimodal Cognitive Computation Anhui University Hefei230601 China Anhui Provincial Key Laboratory of Multimodal Cognitive Computation School of Artificial Intelligence Anhui University Hefei230601 China School of Computer Science and Technology Anhui University Hefei230601 China Peng Cheng Laboratory Shenzhen China Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education Key Laboratory of Electromagnetic Environmental Sensing Anhui Higher Education Institutes Anhui University Hefei230601 China

Tiny objects, frequently appearing in practical applications, have weak appearance and features, and receive increasing interests in meany vision tasks, such as object detection and segmentation. To promote the research and development of tiny object tracking, we create a large-scale video dataset, which contains 434 sequences with a total of more than 217K frames. Each frame is carefully annotated with a high-quality bounding box. In data creation, we take 12 challenge attributes into account to cover a broad range of viewpoints and scene complexities, and annotate these attributes for facilitating the attribute-based performance analysis. To provide a strong baseline in tiny object tracking, we propose a novel Multilevel Knowledge Distillation Network (MKDNet), which pursues three-level knowledge distillations in a unified framework to effectively enhance the feature representation, discrimination and localization abilities in tracking tiny objects. Extensive experiments are performed on the proposed dataset, and the results prove the superiority and effectiveness of MKDNet compared with state-of-the-art methods. The dataset, the algorithm code, and the evaluation code are available at https://***/mmic-lcl/Datasets-andbenchmark-code. Copyright © 2022, The Authors. All rights reserved.

关键词： Distillation

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Capacitive Flexible Three-Axis Force Tactile Sensor Based on Porous Composite Dielectric Layer for Dexterous Robotic Manipulation

SSRN

引用

SSRN 2022年

作者： Guo, Xiaohui Li, Cuicui Zheng, Guoqing Wang, Jingyi Tang, Guopeng Hong, Weiqiang Wang, Yifan Pan, Mingqi Xu, Yaohua Hong, Qi Zhao, Yunong Zhang, Hongwei Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education Anhui University Hefei230601 China Anhui Province Key Laboratory of Target Recognition and Feature Extraction Lu’an237010 China East China Institute of Photo-electron ICs Jiangsu Suzhou215163 China

Flexible tactile sensors that can detect both normal and tangential forces with good flexibility, high sensitivity, wide detection range and rapid dynamic response are imminently needed for electronic skin (e-skin). Thus, we innovatively demonstrated a flexible capacitive three-axis tactile sensor with satisfactory flexibility, high sensitivity (0.693 N -1 at 0-5 N and 0.483 N -1 at 5-14 N for normal force, as well as 0.551 N -1 at 0-2 N and 0.481 N -1 at 2-6 N for tangential force), fast response time (30 ms) and a low hysteresis (6.8%), which was fabricated by combining advanced sensor structure with porous composite dielectric layer in a simple and low-cost three-dimensional (3D) printing method and layer-by-layer (LBL) self-assembly method. The working principle and sensing characteristics of the sensor were elaborated by establishing the theoretical mechanism, and further simulation verification was carried out by the finite element modeling (FEM). Our sensor was employed in soft manipulator grasping and gamepad rotation, suggestive of the application potential of the three-axis force tactile sensor as flexible e-skin in the field of tactile sensing. Our work may pave a way to softness haptic perception strategy, which could be widely utilized in e-skin, soft robot, dexterous robotic manipulation, and intelligent prosthesis. © 2022, The Authors. All rights reserved.

关键词： Composite materials

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A Hybrid Tourism Recommendation System Based on Multi-Objective Evolutionary Algorithm and Re-Ranking

SSRN

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SSRN 2022年

作者： Cao, Ruifen Li, Zijue Wei, Pijing Tian, Ye Zheng, Chunhou Information Materials and Intelligent Sensing Laboratory of Anhui Province School of Computer Science and Technology Anhui University Heifei230601 China Laboratory of Intelligent Computing and Signal Processing Ministry of Education School of Artificial Intelligence Anhui University Hefei230601 China Institutes of Physical Science and Information Technology Anhui University Hefei230601 China

The tourism recommendation system (TRS) can intelligently recommend the next attractions for users according to their historical visit records. To improve tourists’ travel experience, it is very important for TRS to select the attractions that users are interested in from a large number of attractions. Most tourism recommendation methods only consider accuracy as an evaluation index, which can no longer meet the needs of users who are increasingly seeking for diversified attractions. Actually, there is often a conflict between accuracy and diversity, and how to balance these two conflict objectives is a difficulty problem for recommendation system. In order to solve the problem, a hybrid recommendation model based on multi-objective optimization and re-ranking (MOEA/D-HRR) is proposed in this study. To overcome the limited predictive power of a single recommendation algorithm, MOEA/D-HRR mixes three different classical techniques by weighted summation of their recommended results, and then improve the diversity of the recommendation list by using the re-ranking algorithm based on Maximal Marginal Relevance (MMR). In addition, we construct a multi-objective optimization problem in which accuracy and diversity are formulated as two objectives, and use a multi-objective evolutionary algorithm (MOEA) to optimize the weights and parameter of the re-ranking algorithm. A lot of experiments on two public tourism datasets and a new tourism dataset were carried out. Experimental results showed that the model could provide users with diversified attractions while ensuring the accuracy of recommendation attraction. © 2022, The Authors. All rights reserved.

关键词： Multiobjective optimization

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Super-Broadband Rectifier With Wide-band Resistance Compression Network and Harmonic Cycling for RF-Harvesting

TechRxiv

引用

TechRxiv 2022年

作者： Liu, Xin Zhang, Dawei Li, Yingsong Huang, Zhixiang College of Information and Communication Engineering Harbin Engineering University Harbin150001 China Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education Anhui University Hefei230601 China Anhui Province Key Laboratory of Target Recognition and Feature Extraction Lu'An230088 China

In this paper, a super-broadband (SBB) rectifier using a wideband resistance compression network (WRCN) and harmonic cycling is proposed, simulated, fabricated, measured and analyzed in detail for the harvesting of ambient Radio frequency (RF) energy. Meanwhile, impedance compression and matching are achieved to implement the SBB using WRCN and impedance operation networks. Additionally, harmonic cycling structure and bending technology are employed to improve the power conversion efficiency (PCE) and reduce the size, respectively. For demonstration, a prototype of the proposed rectifier is fabricated and measured. The measured results are in good accordance with the simulated ones, indicating that the rectifier can provide high efficiency and ultra-broadband rectification characteristics. A PCE over 50% is realized at 3.5 GHz with an input power range of 6–24 dBm, and a PCE of 75% is obtained at an input power of 18 dBm. The PCE is greater than 50% at 17 dBm with an input frequency of 2.7–4.6 GHz. This work can find significant applications in the development of RF-harvesting. © 2022, CC BY.

关键词： Harvesting

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A quaternary analogue of Tang-Ding codes

arXiv

引用

arXiv 2023年

作者： Shi, Minjia Tao, Sihui Kim, Jon-Lark Solé, Patrick The Key Laboratory of Intelligent Computing Signal Processing Ministry of Education School of Mathematical Sciences Anhui University Hefei230601 China State Key Laboratory of Integrated Service Networks Xidian University Xi’an710071 China Department of Mathematics Sogang University Seoul Korea Republic of Aix Marseille Univ CNRS Centrale Marseille I2M Marseille France

In a recent paper, Tang and Ding introduced a class of binary cyclic codes of rate close to one half with a designed lower bound on their minimum distance. The definition involves the base 2 expansion of the integers in their defining set. In this paper we propose an analogue for quaternary codes. In addition, the performances of the subfield subcode and of the trace code (two binary cyclic codes) are investigated. Copyright © 2023, The Authors. All rights reserved.

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ULA Fitting for MIMO Radar

TechRxiv

引用

TechRxiv 2022年

作者： Shi, Wanlu Liu, Xiaoguang Li, Yingsong College of Information and Communication Engineering Harbin Engineering University Harbin150001 China School of Microelectronics Southern University of Science and Technology Shenzhen China Key Laboratory of Intelligent Computing Signal Processing Ministry of Education Anhui University Anhui Hefei China

Uniform linear array (ULA) fitting (UF) principle is a newly proposed sparse array (SA) design scheme that aims to design SAs using cascaded ULAs, based on which a number of SAs with desired capacity are devised. In this letter, we aim to introduce the UF idea to devise sparse MIMO arrays with reduced mutual coupling and increased uniform degrees of freedom. However, existing sparse MIMO array design approach needs the transmit and receive arrays in MIMO radar have hole-free difference coarrays (DCAs), which is no longer the best choice for UF principle due to the fact that SAs designed via UF cannot guarantee hole-free DCAs. In this regard, considering the difference coarray of the sum coarray (DCSC) concept, a novel sparse MIMO array design strategy which is suitable for UF principle is proposed. Based on the novel strategy and UF principle, a new sparse MIMO array is designed. Numerical simulations verify the good performance of the proposed sparse MIMO array in high coupling scenarios. © 2022, CC BY.

关键词： MIMO radar

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