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International Conference on Acoustics, Speech, and signal processing (ICASSP)

作者： Jindong Xie Jiachen Liu Yupei Lin Jinbao Wang Xianxu Hou Linlin Shen Computer Vision Institute School of Computer Science and Software Engineering Shenzhen University National Engineering Laboratory for Big Data System Computing Technology Shenzhen University School of Information Engineering Guangdong University of Technology Guangzhou China Guangdong Provincial Key Laboratory of Intelligent Information Processing School of AI and Advanced Computing Xi’an Jiaotong-Liverpool University

ISBN: (数字)9798350368741

ISBN: (纸本)9798350368758

The 3D generative adversarial network (GAN) inversion converts an image into 3D representation to attain high-fidelity reconstruction and facilitate realistic image manipulation within the 3D latent space. However, previous approaches face challenges regarding the trade-off between the reconstruction ability and editability. That is, reversing a real-world image to a low-dimensional latent code would inevitably lead to information loss, and achieving a near-perfect reconstruction using high-rate triplane representation often limits the ability to manipulate the image freely in the latent space. To address these issues, we propose a novel latent conditioning encoder-based framework with the alignment between the low-dimensional latent and high-dimensional triplane. A non-semantic guided editing strategy bridges the intrinsic relation between the latent condition and triplane generation, making it possible to edit the high-dimensional representation by latent manipulation. As a result, our method can achieve high-fidelity reconstruction and editing simultaneously by directly controlling the latent code. Experimental results demonstrate that our approach excels in reconstruction and editing quality compared to previous 3D inversion methods. Furthermore, our method can also edit even real faces with large poses and out-of-domain cases.

关键词： Bridges Three-dimensional displays Codes signal processing Generative adversarial networks Vectors Acoustics Speech processing Image reconstruction Faces

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On the error coefficients of asymptotic frame error rate optimal binary linear codes

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IEEE Transactions on Information Theory 2025年

作者： Li, Shitao Luo, Gaojun Shi, Minjia Ling, San Anhui University Key Laboratory of Intelligent Computing Signal Processing Ministry of Education School of Mathematical Sciences Anhui Hefei230601 China Nanjing University of Aeronautics and Astronautics School of Mathematics Jiangsu Province Nanjing211106 China Nanyang Technological University School of Physical and Mathematical Sciences 637371 Singapore

A binary linear code is called asymptotic frame error rate (AFER)-optimal if it achieves the maximum possible value of the minimum distance while having the smallest value of the corresponding error coefficient. Over the additive white Gaussian noise channel and under maximum-likelihood decoding, AFER-optimal codes attain the best possible asymptotic frame error rate at high signal-to-noise ratio. In this paper, we present several bounds on the smallest error coefficients of binary linear codes and give several constructions of AFER-optimal binary linear codes. Many examples confirm that our bounds are sharp on numerous occasions. In addition, we give two families of AFER-optimal codes that respectively attain the proposed bounds with equality. © 1963-2012 IEEE.

关键词： Asymptotic analysis

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Emotional Knowledge Self-Distillation in Dialogue

Emotional Knowledge Self-Distillation in Dialogue

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International Conference on Acoustics, Speech, and signal processing (ICASSP)

作者： Zhongquan Jian Yancheng Wang Weichao Wu Junfeng Yao Meihong Wang Qingqiang Wu School of Informatics Xiamen University Xiamen China School of Computing and Data Science Xiamen University Malaysia Selangor Malaysia School of Mechanics and Civil Engineering China University of Mining & Technology Beijing China School of Film Xiamen University Xiamen China Xiamen Key Laboratory of Intelligent Storage and Computing School of Informatics Xiamen University Xiamen China Key Laboratory of Digital Protection and Intelligent Processing of Intangible Cultural Heritage of Fujian and Taiwan Ministry of Culture and Tourism Xiamen China

ISBN: (数字)9798350368741

ISBN: (纸本)9798350368758

Recognizing emotions in dialogues is vital for effective human-computer interaction, yet remains a challenging task in Natural Language processing (NLP). Previous studies in Emotion Recognition in Conversation (ERC) have primarily focused on contextual features, while overlooking the importance of emotional features in emotion recognition. To address this gap, we focus on the role of emotional features in ERC and propose a novel method, Emotional Knowledge Self-Distillation (EmoKSD 1 ), to enhance the model’s emotional sensitivity. In EmoKSD, utterances are enriched with implicit ⟨mask⟩ tokens to represent conveyed emotions, allowing the distillation of emotional knowledge from explicit emotional tokens to implicit ⟨mask⟩ tokens, thereby enhancing the model’s ability to perceive subtle emotions within the dialogue. Through thorough evaluations on two public ERC datasets (i.e., IEMOCAP and MELD) using proposed coarse-grained utterance distillation and fine-grained token distillation techniques, EmoKSD demonstrates superior performance compared to existing methods, highlighting the significance of emotional features in ERC.

关键词： Representation learning Human computer interaction Emotion recognition Sensitivity Speech recognition signal processing Natural language processing Acoustics Speech processing

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EDA: Enhanced Domain-Adversarial Training for Anatomical Landmark Detection

EDA: Enhanced Domain-Adversarial Training for Anatomical Lan...

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IEEE International Symposium on Biomedical Imaging

作者： Fan Yang S. Kevin Zhou School of Biomedical Engineering Division of Life Sciences and Medicine University of Science and Technology of China Hefei Anhui China Center for Medical Imaging Robotics Analytic Computing & Learning (MIRACLE) Suzhou Institute for Advanced Research University of Science and Technology of China Suzhou Jiangsu China Key Laboratory of Precision and Intelligent Chemistry USTC Hefei Anhui China Key Laboratory of Intelligent Information Processing of Chinese Academy of Sciences (CAS) Institute of Computing Technology CAS Beijing China

ISBN: (数字)9798331520526

ISBN: (纸本)9798331520533

Manually annotating anatomical landmarks in medical images requires experienced clinicians and is a labor-intensive process. However, recent AI-assisted methods for landmark detection often rely on the training and test data originating from the same domain. This work introduces a novel unsupervised domain adaptation (UDA) framework aimed at anatomical landmark detection from a medical image, designed to bridge the gap between a source domain with labels and an unlabeled target domain. Specifically, we have developed a new Domain-Adversarial Network that incorporates skip connections to transfer and fuse high-resolution feature maps. Additionally, we proposed Dynamic Gaussian Learning, which allows the model to escape from local error regions. We carry out experiments on landmark detection for both head and chest, and the results demonstrate that our method achieves state-of-the-art performances in each experiment.

关键词： Training Measurement Adaptation models Three-dimensional displays Smoothing methods Head Kernel Biomedical imaging

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Any-Angle Routing Algorithm for Microfluidic Biochips Driven by Flow Path

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Jisuanji Yanjiu yu Fazhan/Computer Research and Development 2025年第4期62卷 978-988页

作者： Youlin, Pan Shuai, Guo Xing, Huang Genggeng, Liu College of Computer and Data Science Fuzhou University Fuzhou350116 China Engineering Research Center of Big Data Intelligence Fuzhou University Ministry of Education Fuzhou350116 China Fujian Key Laboratory of Network Computing and Intelligent Information Processing Fuzhou University Fuzhou350116 China School of Computer Science Northwestern Polytechnical University Xi’an710072 China

Continuous-flow microfluidic biochips (CFMBs) have become a hot research topic in recent years due to their ability to perform biochemical assays automatically and efficiently. For the first time, PathDriver+ takes the requirements of the actual fluid transportation into account in the design process of CFMBs and implements the actual fluid transport and removal, and plans separate flow paths for each transport task, which have been neglected in previous work. However, PathDriver+ does not take full advantage of the flexibility of CFMBs routing because it only considers the optimization of flow channel length for the global routing in the mesh model, except for the detailed routing. In addition, PathDriver+ only considers the X architecture, while the existing work shows that the any-angle routing can utilize the routing resources more efficiently and shorten the flow channel length. To address the above issues, we propose a flow path-driven arbitrary angle routing algorithm, which can improve the utilization of routing resources and reduce the flow channel length while considering the actual fluid transportation requirements. The proposed algorithm constructs a search graph based on constrained Delaunay triangulation to improve the search efficiency of routing solutions while ensuring the routing quality. Then, a Dijkstra-based flow path routing method is used on the constructed search graph to generate a routing result with a short channel length quickly. In addition, in the routing process, channel reuse strategy and intersection optimization strategy are proposed for the flow path reuse and intersection number optimization problems, respectively, to further improve the quality of routing results. The experimental results show that compared with the latest work PathDriver+, the length of channels, the number of ports used, and the number of channel intersections are significantly reduced by 33.21%, 11.04%, and 44.79%, respectively, and the channel reuse rate is i

关键词： High level synthesis

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A Simple Single-Fed Penta-Band Omnidirectional Antenna with Independent Band Control

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IEEE Transactions on Antennas and Propagation 2025年

作者： Zhou, Changfei Gao, Tianyu Zhang, Ruyue Yu, Dapeng Zhang, Wenyu Li, Yingsong Wong, Hang Dalian University of Technology School of Information and Communication Engineering Dalian116024 China Hubei University of Automotive Technology School of Mathematics Physics and Optoelectronic Engineering Shiyan China Anhui University Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education Hefei230601 China City University of Hong Kong The State Key Laboratory of Terahertz and Millimeter Waves Hong Kong

A novel method of designing a penta-band omnidirectional low-profile antenna with independent band control is proposed. Single-band, dual-band, tri-band, quad-band, and penta-band antennas are investigated, respectively. The proposed penta-band antenna consists of a circular patch, three concentric metal pins, and two square metal plates. The evolutionary step of the penta-band antenna is achieved by adding metal rings and a small metal plate above the big ground. Each of the four metal rings is excited at TM01 mode resonance, while the 5th mode is generated by a small loop resonance formed by the small plate, shorting pin, stub, and the outer conductor of the cable. The penta-band antenna has a small volume of π × (0.109λ1.53GHz)2 × 0.053λ1.53GHz. The corresponding impedance bandwidths (IMBWs) of the five operating bands are 4.9%, 9.4%, 9.0%, 4.8%, 5.0%. Compared with other designs, the proposed antennas exhibit more flexible bands by using a simple structure. Meanwhile, the antenna has a stable omnidirectional radiation pattern across the five bands and a compact size. © 1963-2012 IEEE.

关键词： Monopole antennas

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Counting extreme U1 matrices and characterizing quadratic doubly stochastic operators

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Frontiers of Mathematics in China 2016年第3期11卷 647-659页

作者： Quanbing ZHANG Shangjun YANG Key Laboratory of Intelligent Computing & Signal Processing Ministry of EducationAnhui University Hefei 230039 China

The U1 matrix and extreme U1 matrix were successfully used to study quadratic doubly stochastic operators by R. Ganikhodzhaev and F. Shahidi [Linear Algebra Appl., 2010, 432： 24-35], where a necessary condition for a U1 matrix to be extreme was given. S. Yang and C. Xu [Linear Algebra Appl., 2013, 438： 3905-3912] gave a necessary and sufficient condition for a symmetric nonnegative matrix to be an extreme U1 matrix and investigated the structure of extreme U1 matrices. In this paper, we count the number of the permutation equivalence classes of the n × n extreme U1 matrices and characterize the structure of the quadratic stochastic operators and the quadratic doubly stochastic operators.

关键词： Extreme U1 matrix quadratic doubly stochastic operator,majorized permutation similar irreducible matrix

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Point Pattern Matching Based on Spectra of Directed Graphs

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电子学报(英文版) 2011年第4期20卷 662-666页

作者： LIANG Dong ZHU Ming FAN Yizheng YAN Pu Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education Anhui University Hefei China

We present a novel algorithm for point pattern matching by means of spectra of directed graphs. Given a feature point-set, we construct a weighted directed graph and skew-symmetric matrix associated with the graph. By using spectral decomposition of the matrix, we give a spectral representation of the feature points with half of the eigenvectors. We theoretically analyze that our method can well deal with the matching problem under affine transformation. The expreiments applied to synthetic data and real-world images show the effectiveness of our method.

关键词：点模式匹配图的谱反对称矩阵特征向量匹配问题仿射变换显示方法谱分解

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Control Logic Routing for Continuous-Flow Microfluidic Biochips Based on Deep Reinforcement Learning

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Jisuanji Yanjiu yu Fazhan/Computer Research and Development 2025年第4期62卷 950-962页

作者： Cai, Huayang Huang, Xing Liu, Genggeng College of Computer and Data Science Fuzhou University Fuzhou350116 China Engineering Research Center of Big Data Intelligence Fuzhou University Ministry of Education Fuzhou350116 China Fujian Key Laboratory of Network Computing and Intelligent Information Processing Fuzhou University Fuzhou350116 China School of Computer Science Northwestern Polytechnical University Xi’an710072 China

With the advancement of electronic design automation, continuous-flow microfluidic biochips have become one of the most promising platforms for biochemical experiments. This chip manipulates fluid samples in milliliters or nanoliters by utilizing internal microvalves and microchannels, and thus automatically performs basic biochemical experiments, such as mixing and detection. To achieve the correct bioassay function, the microvalves deployed inside the chip are usually managed by a multiplexer-based control logic, and valves receive control signals from a core input through the control channel for accurate switching. Since biochemical reactions typically require high sensitivity, the length of control paths connecting each valve needs to be reduced to ensure immediate signal propagation, and thus to reduce the signal propagation delay. In addition, to reduce the fabrication cost of chips, a vital issue to be addressed in the logic architecture design is how to effectively reduce the total channel length within the control logic. To address the above issues, we propose a deep reinforcement learning-based control logic routing algorithm to minimize the signal propagation delay and total control channel length, thereby automatically constructing an efficient control channel network. The algorithm employs the dueling deep Q-network architecture as the agent of the deep reinforcement learning framework to evaluate the tradeoff between signal propagation delay and total channel length. Besides, the diagonal channel routing is implemented for the first time for control logic, thus fundamentally improving the efficiency of valve switching operations and reducing the fabrication cost of the chip. The experimental results demonstrate that the proposed algorithm can effectively construct a high-performance and low-cost control logic architecture. © 2025 Science Press. All rights reserved.

关键词： Deep reinforcement learning

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An Effective Method to Solve the Induced Surface Current for Arbitrary Conducting Objects at Resonant Frequencies

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电子学报(英文版) 2010年第1期19卷 66-68页

作者： SONG Kaihong WU Xianliang Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education Anhui University Hefei China

A novel scheme is developed to compute correctly the induced current based on the Electric field integral equation (EFIE) by the Method of moments (MOM) at resonant frequencies. As a First step, the inaccurate induced current is obtained by solving the EFIE. Then, the scattered magnetic field due to the inaccurate induced current is calculated at any given point on the surface of the object. Finally, the accurate induced current at any given point is determined through the total magnetic field. The proposed approach is applied to the case of the infinitely Perfectly electric conducting (PEC) cylinder and PEC sphere to check its accuracy and efficiency. It is found that the numerical results match the analytical solution or the Combined field integral equation (CFIE) solution.

关键词：感应电流共振频率导体目标表面诱导电场积分方程数值结果总磁场

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