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Automatic Segmentation of Nasopharyngeal Carcinoma in CT Images Using Dual Attention and Edge Detection 48

Automatic Segmentation of Nasopharyngeal Carcinoma in CT Ima...

引用

48th IEEE International Conference on Acoustics, Speech and signal processing, ICASSP 2023

作者： Wang, Qizhi Huang, Wei Zhang, Yuan Li, Xuanya Ye, Xiongjun Hu, Kai Xiangtan University Key Laboratory of Intelligent Computing and Information Processing of Ministry of Education Xiangtan411105 China The First Hospital of Changsha Department of Radiology Changsha410005 China Baidu Inc. Beijing100085 China Chinese Academy of Medical Sciences Peking Union Medical College National Cancer Center Cancer Hospital Beijing100021 China

ISBN: (纸本)9781728163277

Nasopharyngeal carcinoma (NPC) is a malignant tumor with a high incidence. Accurate segmentation of the tumor region in Computed Tomography (CT) images of NPC is the key to treatment. However, the features of uneven grayscale values and hazy boundaries of NPC regions make accurate NPC segmentation particularly challenging. To address these problems, we propose an accurate and effective NPC segmentation method using Dual Attention and Edge Detection Convolutional Neural Network (DAED-Net). Firstly, we combine a 2.5D convolutional neural network with UNet++ and propose a new backbone called Dual-dimension Dense UNet (DD-UNet), which can extract more beneficial features from 3D images. Secondly, a Dual Attention Module (DAM) is proposed to help the model better segment the target region of NPC by efficiently collecting spatial and channel attention information from feature maps. Moreover, an Edge Detection Module (EDM) is introduced in the network to enhance the segmentation of the target contours. Finally, we evaluate the proposed DAED-Net on the public MICCAI 2019 StructSeg NPC dataset from different perspectives. Numerical and visual results show that the proposed method outperforms nine state-of-the-art segmentation methods and yields more accurate NPC segmentation results. © 2023 IEEE.

关键词： Convolutional neural network Dual attention Edge detection Nasopharyngeal carcinoma segmentation

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OpenViewer: Openness-Aware Multi-View Learning 39

OpenViewer: Openness-Aware Multi-View Learning

引用

39th Annual AAAI Conference on Artificial Intelligence, AAAI 2025

作者： Du, Shide Fang, Zihan Tan, Yanchao Wang, Changwei Wang, Shiping Guo, Wenzhong College of Computer and Data Science Fuzhou University Fuzhou China Fujian Provincial Key Laboratory of Network Computing and Intelligent Information Processing Fuzhou University Fuzhou China Key Laboratory of Computing Power Network and Information Security Ministry of Education Shandong Computer Science Center Qilu University of Technology Jinan China

ISBN: (纸本)157735897X

Multi-view learning methods leverage multiple data sources to enhance perception by mining correlations across views, typically relying on predefined categories. However, deploying these models in real-world scenarios presents two primary openness challenges. 1) Lack of Interpretability: The integration mechanisms of multi-view data in existing black-box models remain poorly explained;2) Insufficient Generalization: Most models are not adapted to multi-view scenarios involving unknown categories. To address these challenges, we propose OpenViewer, an openness-aware multi-view learning framework with theoretical support. This framework begins with a Pseudo-Unknown Sample Generation Mechanism to efficiently simulate open multi-view environments and previously adapt to potential unknown samples. Subsequently, we introduce an Expression-Enhanced Deep Unfolding Network to intuitively promote interpretability by systematically constructing functional prior-mapping modules and effectively providing a more transparent integration mechanism for multi-view data. Additionally, we establish a Perception-Augmented Open-Set Training Regime to significantly enhance generalization by precisely boosting confidences for known categories and carefully suppressing inappropriate confidences for unknown ones. Experimental results demonstrate that OpenViewer effectively addresses openness challenges while ensuring recognition performance for both known and unknown samples. Copyright © 2025, Association for the Advancement of Artificial Intelligence (***). All rights reserved.

关键词： Multi-task learning

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Design of Low-profile Broadband Circularly Polarized Metasurface Antenna Based on CPW Feed

Design of Low-profile Broadband Circularly Polarized Metasur...

引用

Progress in Electromagnetic Research Symposium (PIERS)

作者： Yue Ma Bo Wu Changqing Liu Xianliang Wu Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education Anhui University Hefei China

ISBN: (纸本)9781665409889

This paper presents a low-profile broadband circularly polarized metasurface antenna based on CPW feed. The antenna works in the 3.9-8.5 GHz frequency band, the metasurface consists of $5\times 5$ square cut corner metal patches printed on the upper surface of the dielectric substrate. In order to make the metasurface have the same characteristics for X polarization and Y polarization, the structure is designed to be symmetric in the slant -45° direction, and the size of the cut angle is changed to generate a circularly polarized wave. According to the phase of the incident wave at different positions on the metasurface, the distance between the 9 radiation elements at the center of the metasurface is 0.3 mm, and the distance between the 16 radiation elements in the outermost layer is 0.4 mm, so as to obtain a more suitable phase compensation. The lower surface of the dielectric substrate adopts a CPW coupling aperture structure as a feed source, and the coupling aperture adopts a stair-shape structure to achieve broadband impedance matching, and the stair-shape aperture is attached to the end of the CPW. The proposed antenna has a simple structure and a low profile, which can be realized by a single-layer printed circuit board (PCB) substrate. To verify the simulation results, a model antenna with an overall size of 0.9$\lambda_{0}$× 0.9$\lambda_{0}$× 0.06$\lambda_{0}$, where $\lambda_{0}$ is the free-space wavelength at 5 GHz, is fabricated. The measurement results show that the -10dB return loss bandwidth reaches 72.8%, the circular polarization axis ratio (AR) is less than 3 dB with a bandwidth of 21.6%, and the highest gain reaches 8.34 dBi, which is almost consistent with the simulation results.

关键词： Antenna measurements Polarization Bandwidth Apertures Metasurfaces Antenna feeds Loss measurement

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Entity Alignment Through Joint Utilization of Multiple Pretrained Models for Attribution Relationship

Entity Alignment Through Joint Utilization of Multiple Pretr...

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IEEE International Conference on Cyber Security and Cloud computing (CSCloud)

作者： Liu Yujia Xu Tao Su Zhehan Li Xinsong Xue Kaipeng Liu Yuxin Key Laboratory of Minzu Languages and Cultures Intelligent Information Processing Northwest Minzu University Lanzhou Gansu Key Laboratory of Linguistic and Cultural Computing Ministry of Education Northwest Minzu University Lanzhou Gansu College of Information Engineering Shanghai Maritime University Shanghai

ISBN: (数字)9798350376982

ISBN: (纸本)9798350376999

Most existing models for entity alignment tasks are based on a single pre-training mode. Through multiple experiments, it has been verified that a single pre-training model is no longer sufficient to meet the needs of current entity alignment tasks. Based on considerations of multiple pre-training models, this paper proposes an entity alignment method that utilizes multiple pre-training models. The purpose of this method is to address the limited accuracy in entity alignment tasks, with a particular focus on separately pre-training the embedding of entity attribute information and link relationship information for matching. To achieve the goal of improving entity alignment accuracy, this paper adopts joint alignment using pre-training with BERT and GloVe word embeddings. Experimental evaluations are conducted on the DBP15k dataset, and the results demonstrate that leveraging multiple pre-training models for attribute and relationship joint alignment can enhance model performance. The evaluation metrics of the model on three different language datasets, Hits@1 and MRR, are as follows: 0.899, 0.930, 0.964, and 0.932, 0.951, 0.975, respectively. These metrics indicate that the model performs well in aligning entities and outperforms current mainstream entity alignment methods.

关键词： Training Measurement Deep learning Cloud computing Accuracy Computational modeling Semantics

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Design of Miniaturized UWB Antenna with Rectangular Slot

Design of Miniaturized UWB Antenna with Rectangular Slot

引用

Progress in Electromagnetic Research Symposium (PIERS)

作者： Minquan Li Ziyun Tu Ran Zhao Guangxiu Zhao Yajing Yan Xiaming Mo Key Laboratory of Intelligent Computing & Signal Processing Ministry of Education Anhui University Hefei China

ISBN: (纸本)9781665409889

A miniaturized ultra-wideband (UWB) antenna with excellent performance is designed in this paper. The antenna is based on hexagonal metal patch, and a circular arc structure is added on the top of the antenna, which widens the effective frequency band of the antenna. The current path is changed by opening rectangular slots on the surface and bottom of the antenna, which greatly improves the in-band characteristics of the antenna. The size of the antenna is 29mm × 31 mm × 1.5 mm after continuous optimization with HFSS. The final test results show that the impedance bandwidth of the antenna less than -10 dB is 3.5 GHz ∼ 19.5 GHz, and it has good radiation characteristics in this frequency band range. The antenna achieves the design goal of miniaturization and UWB, and has a good application prospect in communication system.

关键词： Surface impedance Slot antennas Simulation Ultra wideband communication Metals Bandwidth Ultra wideband antennas

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A Miniaturized Bandpass Filter Based on Hexagonal Resonator

A Miniaturized Bandpass Filter Based on Hexagonal Resonator

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Progress in Electromagnetic Research Symposium (PIERS)

作者： Minquan Li Yajing Yan Ran Zhao Baokun Jin Man Zhang Guangxiu Zhao Xiaming Mo Ziyun Tu Key Laboratory of Intelligent Computing & Signal Processing Ministry of Education Anhui University Hefei China

ISBN: (纸本)9781665409889

This paper proposes a miniaturized bandpass filter (BPF) based on hexagonal resonator. Compared with the rectangular filter structure the hexagonal structure is compact, which can realize the miniaturization of the filter. The Y-shape branches are added to the three inner corners of the hexagon which are not adjacent to each other. At the same time, the input/output ports (I/O ports) position of is changed, two transmission zeros (TZs) are introduced at the high frequency band, and the size of the filter is reduced to achieve further miniaturization. In order to obtain better selectivity at low frequency, a split-ring resonator (SRR) is etched on the ground plane, and a TZ is introduced at low frequency. The simulation results show that the filter designed in this paper has a center frequency of 7.3 GHz along with a fractional bandwidth of 7.8%, which achieves a minimum insertion loss of 0.43 dB in the passband and a return loss better than 20 dB, three transmission zeros are introduced at 6.61 GHz, 8.06 GHz and 10.04 GHz, respectively. The final size of this filter is $0.23\lambda_{g}*0.29\lambda_{g}$, a reduction of 48.2%.

关键词： Band-pass filters Simulation Resonator filters Resonant frequency Insertion loss Propagation losses Filtering theory

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Fast Node Selection of Networked Radar Based on Transfer Reinforcement Learning 5th

Fast Node Selection of Networked Radar Based on Transfer R...

引用

5th IFIP TC 12 International Conference on Intelligence Science, ICIS 2022

作者： Cao, Yanjun Wang, Yuan Guo, Jingjing Han, Li Zhang, Chao Zhu, Jin Zhang, Tianyang Zhang, Xiangrong The 54th Research Institute of China Electronics Technology Group Corporation Beijing China Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education Xidian University Shaanxi Xian710071 China National Laboratory of Radar Signal Processing Xidian University Xian710071 China

ISBN: (纸本)9783031149023

The networked radar system can synthesize different echo signals received by various radars and realize the cooperative detection of multiple radars, becoming more and more critical for data fusion sharing and network collaboration. However, due to the large number and wide range of nodes in the networked radar system, there exists a redundancy problem in radar node assignment, which causes additional resource consumption and slows down the task execution speed of radar node selection. To solve the above problem, this paper proposes a fast radar node selection method based on transfer reinforcement learning to quickly select the optimal and minimum node resources. The proposed method devises a novel reward function for the Monte Carlo Tree and a different termination state of iteration to select the minimize the number of radar nodes. In order to further accelerate the selection of radar nodes, transfer reinforcement learning is presented to fully leverage the previous knowledge. Experimental results show that our proposed method can quickly select the optimal and minimum radar nodes in a brief period, significantly improving the speed of radar node selection in the networked radar. © 2022, IFIP International Federation for Information processing.

关键词： Reinforcement learning

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The Invention Relates to a Wideband Circularly Polarized Metasurface Antenna

The Invention Relates to a Wideband Circularly Polarized Met...

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Progress in Electromagnetic Research Symposium (PIERS)

作者： Mengying Dong Xianliang Wu Yue Ma Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education Anhui University Hefei China

ISBN: (纸本)9781665409889

Aiming at the single characteristic of traditional antenna bandwidth and working polarization state, a broadband circularly polarized antenna based on metamaterial surface is proposed. The antenna is composed of a rectangular microstrip antenna and an upper metasurface. The distance between the two is h. The metasurface is composed of $5\times 5$ square metal elements with equiangular structures on both sides. The linearly polarized rectangular microstrip antenna as the feeding antenna radiates linearly polarized electromagnetic waves, and the metasurface converts the linearly polarized electromagnetic waves radiated by the feeding antenna into circularly polarized electromagnetic waves. This paper analyzes the principle of circular polarization after the antenna is loaded with a metasurface. The simulation software HFSS is used to perform parameter scanning and simulation analysis on the antenna with the size of 0.88$\lambda\times 0.88$$\lambda\times 0.04$$\lambda \mathrm{m}^{3}$ and the center frequency of 8.5 GHz. The results show that the impedance bandwidth of the atenna S 11

关键词： Polarization Microstrip antennas Bandwidth Metasurfaces Antenna feeds Broadband antennas Microstrip

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A Novel Design of Wide Stopband Filter with High Selectivity

A Novel Design of Wide Stopband Filter with High Selectivity

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Progress in Electromagnetic Research Symposium (PIERS)

作者： Minquan Li Xiaming Mo Ran Zhao Yajing Yan Guangxiu Zhao Ziyun Tu Key Laboratory of Intelligent Computing & Signal Processing Ministry of Education Anhui University Hefei China

ISBN: (纸本)9781665409889

In this paper, a wide stopband bandpass filter with high selectivity is designed, which uses three stepped impedance resonators to form the main body of the filter, which improves the stopband width of the filter, and has a wide stopband to 3f 0 . The parasitic passband of the filter is suppressed by etching the double T-shaped defected ground structure that changes the current distribution on the floor, generate a band gap with band-stop characteristics, the stopband width is over 4f 0 . Transmission zero is introduced by cross coupling resonance. There are two coupling paths for the signal from the input to output, one transmission zero is obtained on the upper stopband, then the selectivity of the filter is improved obviously. The simulation results show that the return loss of the filter can reach 46 dB and the insertion loss is less than 0.5 dB in the passband of 4.8 GHz-5.0 GHz. The stopband attenuation of 5.8 GHz-20 GHz is better than 20 dB. The rectangular coefficient of 30 dB/3dB is 3.72, and the size is 12 * 45.9 mm 2 .

关键词： Band-pass filters Couplings Photonic band gap Simulation Resonator filters Insertion loss Attenuation

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Highly Selective UWB Bandpass Filter with Dual Notch Bands Using Stub Loaded Multiple-mode Resonator

Highly Selective UWB Bandpass Filter with Dual Notch Bands U...

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Progress in Electromagnetic Research Symposium (PIERS)

作者： Guangxiu Zhao Minquan Li Ran Zhao Ziyun Tu Yajing Yan Xiaming Mo Key Laboratory of Intelligent Computing & Signal Processing Ministry of Education Anhui University Hefei China

ISBN: (纸本)9781665409889

In this paper, a low-loss ultra-wideband (UWB) bandpass filter with high selectivity and multiple notch bands is proposed. The filter is based on multi-mode resonator (MMR) which mainly consists of a step impedance transmission line that excites several resonant modes. The MMR structure is loaded a T-shaped open-circuited stub which generate two transmission zeros at the edge of the passband to improve selectivity. Meanwhile, MMR structure is also loaded two pairs of short high impedance stubs to extend the upper stopband of the filter. In addition, to address the in-band interference issues, by coupling a tunable parasitic unit to generate dual band notches at 5.8GHz (WLAN) and 8.1 GHz (X-band). Simulated result indicates that the designed filter’s passband is from 3.18 GHz to 10.67 GHz, the insertion loss is lower than 0.5 dB and its 3 dB relative bandwidth is 108.1%. At the same time, the filter has a high selectivity (30dB skirt factor is 0.917) and a stopband of up to 20 GHz (S 21 < −15dB).

关键词： Band-pass filters Couplings Wireless LAN Resonator filters Insertion loss Bandwidth Filtering theory

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