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2025 IEEE International Conference on Acoustics, Speech, and signal processing, ICASSP 2025

作者： Gao, Shihao Li, Caoshuo Mao, Cunli Zhang, Xulong Qu, Xiaoyang Jin, Taisong Wang, Jianzong Key Laboratory of Multimedia Trusted Perception and Efficient Computing Ministry of Education of China School of Informatics Xiamen University China Faculty of Information Engineering and Automation Kunming University of Science and Technology China Yunnan Key Laboratory of Artificial Intelligence Kunming University of Science and Technology China Key Laboratory of Oracle Bone Inscriptions Information Processing Ministry of Education of China Anyang Normal University China Ping An Technology Co. Ltd. Shenzhen China

ISBN: (纸本)9798350368741

Graph contrastive learning based on augmentation strategies has recently demonstrated remarkable performance. Existing methods typically jointly leverage attribute and structural augmentations to generate graph views, learning data invariance information through contrasting sample pairs. However, this joint approach may deviate from the expectation of semantically similar before and after augmentation. The propagation of attribute information in graphs usually occurs through their structure, meaning that structural and attribute augmentations can interfere with each other and potentially distort the graph's semantics. To address this, we propose a decoupled augmentation framework for graph contrastive learning, which eliminates the mutual interference between the two levels of augmentation while fully exploring graph information. Specifically, our framework employs separate encoders to learn data invariance under different augmentation levels, and it considers the positive gains generated between these levels. Experimental results on five public datasets show that the proposed method is more competitive than state-of-the-art approaches. © 2025 IEEE.

关键词： Contrastive learning Graph representation Self-supervised learning

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PianoPal: A Robotic Multimedia System for Interactive Piano Instruction Based on Q-Learning and Real-Time Feedback 31st

PianoPal: A Robotic Multimedia System for Interactive Piano...

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31st International Conference on Multimedia Modeling, MMM 2025

作者： Wang, Yufei Yao, Junfeng Wang, Zefeng Xiamen University Xiamen China Center for Digital Media Computing School of Film Xiamen University Xiamen China Institute of Artificial Intelligence Xiamen University Xiamen China 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: (纸本)9789819620630

Traditional piano learning often requires significant equipment and skill, which can be intimidating for novices. This paper introduces PianoPal, a multimedia piano instruction system based on robotic interaction, designed for novices. The system includes three modules: intelligent performance, piano interaction, and real-time feedback. To test PianoPal’s effectiveness, we conducted two experiments. The first evaluated the fingering planning function using Q-Learning, showing it outperformed alternatives across all metrics. The second experiment involved 24 novice users, with pre- and post-experience questionnaires and interviews indicating that PianoPal improved one- and two-handed performances and was effective in the short term. Overall, PianoPal proves effective in aiding novice piano learning and has been successfully integrated into our robotic piano device, laying a solid foundation for future piano tutoring robot developments. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Musical instruments

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A Gong-Si-Shaped Heterogeneous Circular-Polarization Array for 5G Application 5

A Gong-Si-Shaped Heterogeneous Circular-Polarization Array f...

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5th IEEE International Conference on Electronic Information and Communication Technology, ICEICT 2022

作者： Zhou, Wei Qi, Junwei Li, Yingsong Huang, Zhixiang Yang, Lixia College of Information and Communication Engineering Harbin Engineering University Harbin150001 China Anhui Province Key Laboratory of Target Recognition and Feature Extraction LuAn230088 China Anhui University Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education Hefei China

ISBN: (数字)9781665472111

ISBN: (纸本)9781665472111

In this work, a Gong-Si-shaped circularly polarized (CP) array with power driver for 5G is proposed. The radiator of the constructed CP array consists of two Chinese-like characters ' and '' with the similar size and pronunciation of 'gong' and 'si', Two L-shaped feeding probes of the same size are connected to the designed power driver printed on the bottom layer of ground plate, and the array can radiate circular polarization electromagnetic waves by changing the positions of the L-shaped probes and the angle of the horizontal parts of the L-shaped probes. From the simulating and optimizing, it is finally obtained that the -15 dB bandwidth of modeled Gong-Si-like CP antenna lies in 2.49 - 2.81 GHz and the presented Gong-Si-like CP antenna has a axial bandwidth covering 2.36 - 2.82 GHz, which meets the n41 5G band implementing at 2.515 - 2.675 GHz. © 2022 IEEE.

关键词： Circular polarization

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Evolutionary Neural Architecture Search for Transformer in Knowledge Tracing

arXiv

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arXiv 2023年

作者： Yang, Shangshang Yu, Xiaoshan Tian, Ye Yan, Xueming Ma, Haiping Zhang, Xingyi Anhui University China Guangdong University of Foreign Studies China Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education China

Transformer has achieved excellent performance in the knowledge tracing (KT) task, but they are criticized for the manually selected input features for fusion and the defect of single global context modelling to directly capture students’ forgetting behavior in KT, when the related records are distant from the current record in terms of time. To address the issues, this paper first considers adding convolution operations to the Transformer to enhance its local context modelling ability used for students’ forgetting behavior, then proposes an evolutionary neural architecture search approach to automate the input feature selection and automatically determine where to apply which operation for achieving the balancing of the local/global context modelling. In the search space design, the original global path containing the attention module in Transformer is replaced with the sum of a global path and a local path that could contain different convolutions, and the selection of input features is also considered. To search the best architecture, we employ an effective evolutionary algorithm to explore the search space and also suggest a search space reduction strategy to accelerate the convergence of the algorithm. Experimental results on the two largest and most challenging education datasets demonstrate the effectiveness of the architecture found by the proposed approach. Copyright © 2023, The Authors. All rights reserved.

关键词： Convolution

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HRTransNet: HRFormer-Driven Two-Modality Salient Object Detection

arXiv

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arXiv 2023年

作者： Tang, Bin Liu, Zhengyi Tan, Yacheng He, Qian School of Artificial Intelligence and Big Data Hefei University Hefei China Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education School of Computer Science and Technology Anhui University Hefei China

The High-Resolution Transformer (HRFormer) can maintain high-resolution representation and share global receptive fields. It is friendly towards salient object detection (SOD) in which the input and output have the same resolution. However, two critical problems need to be solved for two-modality SOD. One problem is two-modality fusion. The other problem is the HRFormer output’s fusion. To address the first problem, a supplementary modality is injected into the primary modality by using global optimization and an attention mechanism to select and purify the modality at the input level. To solve the second problem, a dual-direction short connection fusion module is used to optimize the output features of HRFormer, thereby enhancing the detailed representation of objects at the output level. The proposed model, named HRTransNet, first introduces an auxiliary stream for feature extraction of supplementary modality. Then, features are injected into the primary modality at the beginning of each multi-resolution branch. Next, HRFormer is applied to achieve forwarding propagation. Finally, all the output features with different resolutions are aggregated by intra-feature and inter-feature interactive transformers. Application of the proposed model results in impressive improvement for driving two-modality SOD tasks, e.g., RGB-D, RGB-T, and light field ***://***/liuzywen/HRTransNet Copyright © 2023, The Authors. All rights reserved.

关键词： Global optimization

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TransCoop: Cooperation of Transformers and CNNs for Camouflaged Object Segmentation

TransCoop: Cooperation of Transformers and CNNs for Camoufla...

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2022 IEEE International Conference on Multimedia and Expo, ICME 2022

作者： Wu, Fucai Li, Xuanya Zhang, Yuan Hu, Kai Xiangtan University Key Laboratory of Intelligent Computing and Information Processing of Ministry of Education Xiangtan411105 China Baidu Inc. Beijing100085 China Xiangnan University Key Laboratory of Medical Imaging and Artifical Intelligence of Hunan Province Chenzhou423000 China

ISBN: (数字)9781665485630

ISBN: (纸本)9781665485630

Camouflaged object segmentation (COS) is a challenging task due to the existence of high intrinsic similarities between the object and background. To overcome this challenge, we pro-pose a new framework, called TransCoop, for COS through the cooperation of Transformers and convolutional neural net-works (CNNs). Specifically, Transformer is used to model global context and structural information for accurately positioning potential target objects. Meanwhile, a well-designed texture feature fusion module (TFFM) is used to fuse the features encoded by CNN with the shallow Transformer to fully mine the low-level features in the scene. Furthermore, we propose a noise removal module (NRM), which can eliminate the background noise of low-level features with the guidance of precise target location. Notably, our TFFM and NRM can effectively realize the interaction between Transformer and CNN features. Extensive experiments on four benchmark datasets demonstrate the superiority of our TransCoop against existing state-of-the-art methods. © 2022 IEEE.

关键词： Convolutional neural networks

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A Dual-band Monopole Antenna with EBG for Wearable Wireless Body Area Networks

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Applied Computational Electromagnetics Society Journal 2021年第1期36卷 48-54页

作者： Wang, Chao Zhang, Liang Wu, Shenbing Huang, Shijie Liu, Changqing Wu, Xianliang Key Lab of Ministry of Education of Intelligent Computing & Signal Processing Anhui University Hefei City China AnHui Province Key Laboratory of Simulation and Design Electronic Information System Hefei Normal University Hefei City China

This paper proposes a dual-band wearable monopole antenna adopting an electromagnetic band-gap (EBG) structure, which operates at 2.45 and 5.8 GHz ISM bands and is suitable for wearable applications. Both the monopole antenna and the EBG structure are fabricated on an F4B semi-flexible substrate having a dielectric constant of 2.2. The EBG structure effectively isolates the human body from the radiation of the antenna and reduces the specific absorption rate (SAR) of it by more than 97.5%. This improves the antenna gain and the peak gain reaches 9.1 dBi at 5.8 GHz. The wearable performance of the antenna showed that it can sustain good performance even under realistic human body loading. Besides, the antenna has a small size, which makes it ideal for wearable applications. © ACES

关键词： Monopole antennas

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Femtosecond laser-induced flexible and highly sensitive capacitive pressure sensor with treefrog suckers bionic microstructure 2

Femtosecond laser-induced flexible and highly sensitive capa...

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2nd International Symposium on Sensor Technology and Control, ISSTC 2023

作者： Wang, Zhiyun Chu, Mengyang Su, Yahui Guo, Xiaohui Liu, Rui Anhui University Information Materials and Intelligent Sensing Laboratory of Anhui Province School of Electronic and Information Engineering Hefei China Anhui University Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education Anhui University School of Integrated Circuits Hefei China Anhui Xinhuai Electronics Co. Ltd Huaibei China

ISBN: (纸本)9798350314465

Flexible capacitive pressure sensors are optimal for wearable electronic equipment owing to their advantages of simplicity in architecture and low power consumption. However, fabricating a bionic flexible capacitive pressure sensor with high sensitivity and a wide dynamic range of detection is still a great challenge. In this article, we propose a flexible pressure sensor based on femtosecond laser ablation with a treefrog suckers bionic microstructure. The treefrog suckers capacitive pressure sensor (TSCPS) has high sensitivity (0-10 kPa, 0.0762 kPa-1), wide detection range (500 kPa), high repeatability (>12000 s at 10 kPa), and fast response time (62.5 ms). For practical applications, the TSCPS was positioned on the wrist, palm, and sole of the hand to detect the movements of each part accordingly. The experimental findings indicate that the TSCPS has broad promising applications in bionic wearable products such as human locomotion monitoring. © 2023 IEEE.

关键词： Pressure sensors

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A Simple Controllable Left-Right-Hand Circularly Polarized Antenna for GPS L2 Using Arc-like Slots

A Simple Controllable Left-Right-Hand Circularly Polarized A...

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IEEE Asia-Pacific Conference on Antennas and Propagation (APCAP)

作者： Lulu Meng Sixian Qian Zhixiang Huang Yingsong Li Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education Anhui University China

A single-layer, polarization adjustable circular-polarization (CP) antenna with four arc-like slots has been designed for GPS L2 band. The created antenna uses four arc-like slots to tune the phase difference to form a CP antenna, where the arc-like slots with a specific size relationship are etched on the patch. By adjusting the radius of the arc-like slots, Left-handed -circular-polarization (LHCP) and Right-handed-circular-polarization (RHCP) can be realized easily with simple structure. Simulations and optimizations show that the constructed CP-antenna has a good axial-ratio bandwidth of 10 MHz and impedance-bandwidth of 40 MHz and 30 MHz for LHCP and RHCP application.

关键词： Polarization Slot antennas Bandwidth Directive antennas Antenna feeds Optimization Global Positioning System

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Energy-Efficient UAV-Based IoT Communications With WiFi Suppression in 5 GHz ISM Bands

Energy-Efficient UAV-Based IoT Communications With WiFi Supp...

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作者： Lin, Deping Zuo, Peiliang Peng, Tao Qian, Rongrong Wang, Wenbo Beijing University of Posts and Telecommunications Wireless Signal Processing and Network Laboratory Key Laboratory of Universal Wireless Communication Ministry of Education Beijing100876 China Beijing Institute of Electronic Science and Technology Department of Electronics and Communication Engineering Beijing100070 China Beijing University of Posts and Telecommunications School of Artificial Intelligence Beijing100876 China

Unmanned Aerial Vehicle (UAV) based communication is a promising technology for offering wireless communication services. UAVs can typically be adopted as aerial base stations to collect data from ground Internet of Things (IoT) devices. However, the Ground-to-Air link of UAV-based IoT communications is prone to be interfered by surrounding WiFi devices in the Industrial, Scientific, Medical (ISM) band. This paper aims to enable reliable uplink communications for IoT devices in 5 GHz ISM bands, thereby reducing the hover time and energy consumption of the UAV. To this end, we first study and design suppression frames suitable for WiFi devices. Then a suppression method is proposed, which is shown to be effective for all the tested devices, based on emulation performance verification of the frames for multiple commercial off-the-shelf (COTS) WiFi devices. Moreover, by taking the energy consumption of the UAV and multiple transmission parameters of the suppression method into account, we formulate an optimization problem for the desired uplink, which is designed to minimize the energy consumption of the UAV, under the constraints of satisfying the link channel capacity. Given that the optimization problem is non-convex mixed-integer nonlinear programming, this paper proposes an efficient algorithm that takes advantage of the suppression performance of the utilized frames. Numerical simulations demonstrate the performance of the proposed algorithm in terms of the WiFi device density, UAV weight, channel capacity requirement and parameters of the suppression method. The communication quality of the desired Ground-to-Air link is shown to be significantly improved, while the consumed energy is demonstrated to be obviously reduced. © 1967-2012 IEEE.

关键词： Internet of things

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