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2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition, CVPR 2023

作者： Zhu, Zijian Zhang, Yichi Chen, Hai Dong, Yinpeng Zhao, Shu Ding, Wenbo Zhong, Jiachen Zheng, Shibao Institute of Image Communication and Network Engineering Shanghai Jiao Tong University China Institute for Ai Tsinghua University BNRist Center Thbi Lab Dept. of Comp. Sci. and Tech. China School of Computer Science and Technology Anhui University Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education Information Materials and Intelligent Sensing Laboratory of Anhui Province China Saic Motor Ai Lab Zhongguancun Laboratory China

ISBN: (纸本)9798350301298

3D object detection is an essential perception task in autonomous driving to understand the environments. The Bird's-Eye-View (BEV) representations have significantly improved the performance of 3D detectors with camera inputs on popular benchmarks. However, there still lacks a systematic understanding of the robustness of these vision-dependent BEV models, which is closely related to the safety of autonomous driving systems. In this paper, we evaluate the natural and adversarial robustness of various representative models under extensive settings, to fully understand their behaviors influenced by explicit BEV features compared with those without BEV. In addition to the classic settings, we propose a 3D consistent patch attack by applying adversarial patches in the 3D space to guarantee the spatiotemporal consistency, which is more realistic for the scenario of autonomous driving. With substantial experiments, we draw several findings: 1) BEV models tend to be more stable than previous methods under different natural conditions and common corruptions due to the expressive spatial representations;2) BEV models are more vulnerable to adversarial noises, mainly caused by the redundant BEV features;3) Camera-LiDARfusion models have superior performance under different settings with multi-modal inputs, but BEV fusion model is still vulnerable to adversarial noises of both point cloud and image. These findings alert the safety issue in the applications of BEV detectors and could facilitate the development of more robust models. © 2023 IEEE.

关键词： Autonomous driving

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HD-KT: Advancing Robust Knowledge Tracing via Anomalous Learning Interaction Detection 24

HD-KT: Advancing Robust Knowledge Tracing via Anomalous Lear...

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33rd ACM Web Conference, WWW 2024

作者： Ma, Haiping Yang, Yong Qin, Chuan Yu, Xiaoshan Yang, Shangshang Zhang, Xingyi Zhu, Hengshu Information Materials and Intelligent Sensing Laboratory of Anhui Province Institutes of Physical Science and Information Technology Anhui University Anhui Hefei China Institutes of Physical Science and Information Technology Anhui University Anhui Hefei China Career Science Lab BOSS Zhipin PBC School of Finance Tsinghua University Beijing China School of Artificial Intelligence Anhui University Anhui Hefei China The Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education School of Computer Science and Technology Anhui University Anhui Hefei China Career Science Lab BOSS Zhipin Beijing China

ISBN: (纸本)9798400701719

Knowledge tracing (KT) is a crucial task in online learning, aimed at tracing and predicting each student's knowledge states throughout their learning process. Over the past decade, it has garnered widespread attention due to it provides the potential for more tailored and adaptive online learning experiences. Although most current KT methodologies emphasize optimizing network structures to enhance predictive accuracy for future student performance, they often neglect anomalous interactions in students' learning processes, which may arise from low data quality (i.e., inferior question quality) and abnormal student behaviors (i.e., guessing and mistakes). To this end, in this paper, we propose a novel framework, termed HD-KT, designed to enhance the robustness of existing KT methodologies with Hybrid learning interactions Denoising approach. Specifically, we introduce two detectors for anomalous learning interactions, namely knowledge state-guided anomaly detector and student profile-guided anomaly detector. In the first detection module, we design a sequential autoencoder to identify anomalous learning interactions by detecting atypical student knowledge states. In the second module, we incorporate an attention mechanism by modeling a student's long-term profile to capture irregular interactions. Extensive experiments on four real-world benchmark datasets have decisively shown our HD-KT markedly boosts the robustness of numerous prevailing KT models, consequently increasing the accuracy of future student performance predictions. Additionally, our case studies highlight the versatility of HD-KT in addressing diverse downstream tasks, such as exercise quality analysis and learning behavior-based student clustering. © 2024 ACM.

关键词： Students

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Yolov9-Spe: A Novel Deep Learning Method For Classroom Student Behavior Detection

SSRN

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SSRN 2024年

作者： Liu, Junxiu Wu, Fengxiang Lu, Baoshan Qin, Sheng Fu, Qiang Luo, Yuling Guangxi Key Lab of Brain-inspired Computing and Intelligent Chips School of Electronic and Information Engineering Guangxi Normal University Guilin541004 China Guangxi Wireless Broadband Communication and Signal Processing Key Laboratory Guilin University of Electronic Technology Guilin541004 China

Deep learning can significantly enhance student behavior detection in classrooms. However, challenges such as small target recognition, blurry data, occlusion, and multi-scale detection persist. To address these, we propose YOLOv9-SPE, an improved model based on YOLOv9, incorporating Space-to-Depth Convolution (SPD-Conv), Partial Convolution (PConv), and an Efficient Multi-Scale Attention (EMA) Module. SPD-Conv enhances small target recognition and improves feature extraction for blurry data, while PConv, adapted from FasterNet, addresses occlusion issues. EMA is integrated to handle multi-scale targets in classroom student behavior detection. Experimental results on a student behavior dataset show that YOLOv9-SPE achieves a 2.1% improvement in mean average precision over the original YOLOv9. These enhancements provide a more accurate and efficient method for monitoring and analyzing student behavior in educational settings. © 2024, The Authors. All rights reserved.

关键词： Contrastive Learning

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High Common-Mode Rejection Differential Filter Based on Coupled Lines

High Common-Mode Rejection Differential Filter Based on Coup...

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IEEE MTT-S International Microwave Workshop Series on Advanced Materials and Processes for RF and THz Applications (IMWS-AMP)

作者： Zhen Liu Haoran Zhu Information Materials and Intelligent Sensing Laboratory of Anhui Province Anhui University Hefei China Key Lab of Intelligent Computing & Signal Processing Ministry of Education Anhui University Hefei China

In this paper, a differential bandpass filter (BPF) based on enhanced coupling line structure has been suggested in this study. Two out-of-band transmission zeros are added to the differential mode by loading the coupling line at the output terminal, which raises the rectangular coefficient of the filter. Two common mode transmission zeros in the passband are additionally provided by the open/short stub that is already loaded at the output port. To accommodate the demands of various filter performances, the location of the transmission zeros can be modified by altering the values of the coupling lines' and stubs' impedances. Finally, the passband common mode suppression might be as high as 40 dB.

关键词： Band-pass filters Couplings Radio frequency Conferences Loading Microwave circuits Filtering theory

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ϵ-π: A Nonparametric Model for Neural Power Spectra Decomposition

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IEEE Journal of Biomedical and Health Informatics 2024年第5期28卷 2624-2635页

作者： Hu, Shiang Zhang, Zhihao Zhang, Xiaochu Wu, Xiaopei Valdes-Sosa, Pedro A. Anhui University Anhui Provincial Key Lab of Multimodal Cognitive Computation Key Lab of Intelligent Computing and Signal Processing of Ministry of Education School of Computer Science and Technology Hefei230601 China University of Science and Technology of China School of Humanities and Social Science Department of Psychology Hefei230026 China University of Electronic Science and Technology of China MOE Key Lab for Neuroinformation School of Life Science and Technology Chengdu611731 China

The power spectra estimated from the brain recordings are the mixed representation of aperiodic transient activity and periodic oscillations, i.e., aperiodic component (AC) and periodic component (PC). Quantitative neurophysiology requires precise decomposition preceding parameterizing each component. However, the shape, statistical distribution, scale, and mixing mechanism of AC and PCs are unclear, challenging the effectiveness of current popular parametric models such as FOOOF, IRASA, BOSC, etc. Here, was proposed to decompose the neural spectra by embedding the nonparametric spectra estimation with penalized Whittle likelihood and the shape language modeling into the expectation maximization framework. was validated on the synthesized spectra with loss statistics and on the sleep EEG and the large sample iEEG with evaluation metrics and neurophysiological evidence. Compared to FOOOF, both the simulation presenting shape irregularities and the batch simulation with multiple isolated peaks indicated that improved the fit of AC and PCs with less loss and higher F1-score in recognizing the centering frequencies and the number of peaks;the sleep EEG revealed that produced more distinguishable AC exponents and improved the sleep state classification accuracy;the iEEG showed that approached the clinical findings in peak discovery. Overall, offered good performance in the spectra decomposition, which allows flexible parameterization using descriptive statistics or kernel functions. is a seminal tool for brain signal decoding in fields such as cognitive neuroscience, brain-computer interface, neurofeedback, and brain diseases. © 2013 IEEE.

关键词： Electroencephalography

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A Metasurface-Based Wideband High Isolation Circularly Polarized Antenna For 5G MIMO Millimeter-Wave Systems

A Metasurface-Based Wideband High Isolation Circularly Polar...

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IEEE MTT-S International Microwave Workshop Series on Advanced Materials and Processes for RF and THz Applications (IMWS-AMP)

作者： Hui Zhu Haoran Zhu Information Materials and Intelligent Sensing Laboratory of Anhui Province Anhui University Hefei China Key Lab of Intelligent Computing & Signal Processing Ministry of Education Anhui University Hefei China

A wideband high isolation circularly polarized antenna for 5G MIMO millimeter-wave systems is presented in this paper. The presented antenna exhibits wideband characteristics due to the resonance of surface waves along the metasurface. The circularly polarized preliminary bandwidth is achieved by truncated corner patches when the truncation can be adjusted to implement the phase and amplitude values of the two quadrature modes. The port isolation is improved by the resonance of double-layer microstrip lines in the frequency. The size of the antenna is 17.8×17.8×1.02 mm 3 , the impedance bandwidth is 30.4% (23.29-31.66 GHz) and the 3-dB axial ratio bandwidth is 20.5% (24.47-30.12 GHz). In addition, the port isolation of the presented antenna is higher than 25 dB, and the peak gain is 8.4 dB. Therefore, the given antenna has the advantages of wideband, circularly polarized and high isolation.

关键词： Microwave antennas Surface impedance 5G mobile communication Surface waves Metasurfaces Broadband antennas Impedance

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A High-gain Triple Stopband Ultra-wideband MIMO Antenna

A High-gain Triple Stopband Ultra-wideband MIMO Antenna

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International Conference on Microwave and Millimeter Wave Technology Proceedings

作者： Jian Wu Yufa Sun Qing Wang Key Lab of Intelligent Computing & Signal Processing Ministry of Education Anhui University Hefei China School of Electronic Engineering Anhui Xinhua University Hefei China

ISBN: (纸本)9781665482271

This paper designs a three-stopband ultra-wideband MIMO antenna with high-gain using FR4 as the dielectric substrate. The antenna consists of two horizontally placed semicircle patches with chamfer and slot. By corroding two C-shaped grooves on the semicircular radiation patch and etching two symmetrical C-shaped grooves on both sides of the feeder on the floor, the interference of WiMAX, WLAN and 7.5GHz-X band is blocked. In order to realize the isolation of the dual ports, a groove is made on the defective metal surface and a branch shaped like Chinese character mountain is added. The simulation results show that the working frequency range of the antenna is 2.5-11GHz, and three S11 stopbands higher than −10dB are formed at 3.3-3.8GHz, 5.15-5.825GHz, and 7.1-7.9GHz respectively. Therefore, it has good application prospects in the ultra-wideband field that blocks narrowband communications.

关键词： Microwave antennas Wireless LAN Slot antennas Simulation Dielectric substrates Interference WiMAX

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A Design of Hign Gain Wideband Circular Polarization Antenna Based on All-Metal Vivaldi Antenna 2

A Design of Hign Gain Wideband Circular Polarization Antenna...

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2020 2nd International Conference on Artificial Intelligence Technologies and Application, ICAITA 2020

作者： Li, Xuemei Huang, Zhixiang Liu, Dui Wang, Chao Cheng, Yi Key Lab of Intelligent Computing and Signal Processing Ministry of Education AnHui University Heifei AnHui230000 China

This paper designs a broadband circularly polarized antenna covering the 25 GHz to 31 GHz band. The Vivaldi antenna is used as the basic structure to generate broadband electromagnetic waves;circular polarization is achieved by feeding through a circularly polarized bridge;a metal choke ring is used at the bottom to ensure the low side lobes of the antenna. The antenna consists of four basic Vivaldi antennas, a metal choke ring, a grounded substrate, and a feed network. The results show that the antenna covers the entire frequency band when the axial ratio is lower than 3 dB, and the impedance matching is better. The use of a choke ring structure ensures that the antenna electromagnetic waves are radiated upward, resulting in higher gain and lower side lobes. The highest gain in the included frequency band is 11.4 dB, and the simulation result is good. The antenna has high gain and low sidelobe characteristics. © 2020 Published under licence by IOP Publishing Ltd.

关键词： Circular polarization

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Design of Filtering Power Divider with Wide Stopband Based on QMSIW 2

Design of Filtering Power Divider with Wide Stopband Based o...

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2020 2nd International Conference on Artificial Intelligence Technologies and Application, ICAITA 2020

作者： Cheng, Yi Huang, Zhixiang Wang, Zhongmiao Wang, Chao Li, Xuemei Key Lab of Ministry of Education of Intelligent Computing and Signal Processing Anhui University Hefei Anhui230601 China

A miniaturized filtering power divider with wide stopband based on quarter-mode substrate integrated waveguide (QMSIW) is proposed. The physical size of the QMSIW is reduced by 3/4 comparing with the traditional SIW structure, which can achieve miniaturization, and its electromagnetic field distribution has little effect. Using the metal interference column and the etched U-shaped groove to adjust the resonance frequency, so that the main mode and the first higher mode form a passband, meanwhile, suppressing the second higher mode. The simulation results show that the center frequency is 4.42 GHz with insertion loss of 0.45 dB, the 3-dB bandwidth is 4.12-4.63 GHz with a fractional bandwidths of 9.7%, and there is a great stopband up to 11 GHz with 15 dB rejection level. Besides, the return loss of passband is better than 17.5 dB. To verify the validity of this design, a prototype is fabricated and measured. The measured results demonstrate that it has a good agreement with the design simulations. © 2020 Published under licence by IOP Publishing Ltd.

关键词： Substrate integrated waveguides

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Edge-guided and Class-balanced Active Learning for Semantic Segmentation of Aerial Images

arXiv

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arXiv 2024年

作者： Shan, Lianlei Wang, Weiqiang Lv, Ke Luo, Bin The School of Computer Science and Technology University of Chinese Academy of Sciences Beijing100049 China School of Engineering Science University of Chinese Academy of Sciences Beijing100049 China MOE Key Lab of Signal Processing and Intelligent Computing School of Computer Science and Technology Anhui University Hefei230601 China

Semantic segmentation requires pixel-level annotation, which is time-consuming. Active Learning (AL) is a promising method for reducing data annotation costs. Due to the gap between aerial and natural images, the previous AL methods are not ideal, mainly caused by unreasonable labeling units and the neglect of class imbalance. Previous labeling units are based on images or regions, which does not consider the characteristics of segmentation tasks and aerial images, i.e., the segmentation network often makes mistakes in the edge region, and the edge of aerial images is often interlaced and irregular. Therefore, an edge-guided labeling unit is proposed and supplemented as the new unit. On the other hand, the class imbalance is severe, manifested in two aspects: the aerial image is seriously imbalanced, and the AL strategy does not fully consider the class balance. Both seriously affect the performance of AL in aerial images. We comprehensively ensure class balance from all steps that may occur imbalance, including initial labeled data, subsequent labeled data, and pseudo-labels. Through the two improvements, our method achieves more than 11.2% gains compared to state-of-the-art methods on three benchmark datasets, Deepglobe, Potsdam, and Vaihingen, and more than 18.6% gains compared to the baseline. Sufficient ablation studies show that every module is indispensable. Furthermore, we establish a fair and strong benchmark for future research on AL for aerial image segmentation. Copyright © 2024, The Authors. All rights reserved.

关键词： Semantic Segmentation

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