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arXiv 2021年

作者： Li, Chenglong Xue, Wanlin Jia, Yaqing Qu, Zhichen Luo, Bin Tang, Jin Sun, Dengdi Information Materials and Intelligent Sensing Laboratory of Anhui Province Anhui Provincial Key Laboratory of Multimodal Cognitive Computation School of Artificial Intelligence Anhui University Hefei230601 China Information Materials and Intelligent Sensing Laboratory of Anhui Province Key Lab of Intelligent Computing and Signal Processing of Ministry of Education Anhui Provincial Key Laboratory of Multimodal Cognitive Computation School of Computer Science and Technology Anhui University Hefei230601 China

RGBT tracking receives a surge of interest in the computer vision community, but this research field lacks a large-scale and high-diversity benchmark dataset, which is essential for both the training of deep RGBT trackers and the comprehensive evaluation of RGBT tracking methods. To this end, we present a Large-scale High-diversity benchmark for short-term RGBT tracking (LasHeR) in this work. LasHeR consists of 1224 visible and thermal infrared video pairs with more than 730K frame pairs in total. Each frame pair is spatially aligned and manually annotated with a bounding box, making the dataset well and densely annotated. LasHeR is highly diverse capturing from a broad range of object categories, camera viewpoints, scene complexities and environmental factors across seasons, weathers, day and night. We conduct a comprehensive performance evaluation of 12 RGBT tracking algorithms on the LasHeR dataset and present detailed analysis. In addition, we release the unaligned version of LasHeR to attract the research interest for alignment-free RGBT tracking, which is a more practical task in real-world applications. The datasets and evaluation protocols are available at: https://***/mmic-lcl/Datasets-and-benchmark-code. Copyright © 2021, The Authors. All rights reserved.

关键词： Large dataset

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A Wideband Millimeter Wave E-shape Antenna in Package with Embedded Wafer Level Ball Grid Array Technology

A Wideband Millimeter Wave E-shape Antenna in Package with E...

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International Conference on Numerical Electromagnetic Modeling and Optimization for RF, Microwave, and Terahertz Applications (NEMO)

作者： Bin Lu Haoran Zhu Zongming Duan Yuefei Dai Key Lab of Intelligent Computing & Signal Processing Ministry of Education Anhu University Hefei China Key Lab of Intelligent Computing & Signal Processing Ministry of Education Anhui University Hefei China Anhui Province Engineer Laboratory for Antennas and Microwave The 38th Research Institute of China Electronic Technology Group Corporationy Hefei China

ISBN: (数字)9781728169668

ISBN: (纸本)9781728169675

The feasibility of an antenna-in-package (AiP) concept is demonstrated for automotive radar sensors at the 77 GHz-band. Infineon's embedded wafer level ball grid array (eWLB) is employed as packaging technology. We developed a E-shape patch antenna in 6×6 mm 2 eWLB package that include 2×2 mm 2 dummy Si chips. From the simulated results of the proposed E-plane patch antenna, provides a wide bandwidth of 19.2% (|S 11 |

关键词： Patch antennas Radar antennas Sensors Broadband antennas Wideband Antenna arrays Electronics packaging

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A conditional-probability zone transformation coding method for categorical features 19

A conditional-probability zone transformation coding method ...

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2019 ACM Turing Celebration Conference - China, ACM TURC 2019

作者： He, Liang Shen, Chao Li, Yun National Key Laboratory of Science and Technology on Blind Signal Processing Chengdu Sichuan China MOE Key Lab for Intelligent Networks and Network Security Xi'an Jiaotong University Shaanxi Xi'an China

ISBN: (纸本)9781450371582

It has been a key issue for solving problems efficiently by machine learning models with code categorical features. The state-of-the-art one-hot coding is a widely accepted method to convert the categorical features into numerical values. However, it attracts a sparse space and meaningless value after coding. We come up with a novel coding method based on conditional probability after dividing the features into zones, which is called Conditional-probability-based Zone Transformation (CZT) coding. CZT coding calculates the conditional probability of each feature, then divides the features into several zones according to the probability and finally codes the features in each zone. We mathematically prove that compared with the state-of-the-art method, CZT coding reduces the code length by at least the mean of feature space and the issue becomes into an easier one after CZT coding for the following machine learning model. Finally, using the same neuron network as the classifier, we compare the performance of CZT coding and one-hot coding by using the titanic dataset, where most of the features are categorical, and the result is that CZT coding makes the classifier performs better both on the accuracy and steadiness. © 2019 Association for computing Machinery.

关键词： Probability

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An End to End Method of Whisper Enhancement

An End to End Method of Whisper Enhancement

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IEEE International Conference on Information Communication and signal processing (ICICSP)

作者： Yan Huang HaiLun Lian Jian Zhou HuaBin Wang Liang Tao MOE Key Laboratory of Intelligent Computing and Signal Processing Anhui University Hefei China

In this paper, we propose a method of enhancing whisper, using whisper without any pretreatment combined with Wavenet. Our method is end-to-end, that is, inputing noised whisper to get clean whisper. The input to our method is the original whisper without any processing, reducing the loss of features caused by other operations. We use speech denoising Wavenet to enhance whisper. Wavenet can not only enhance whisper well, but also tackle the issue of intelligibility. Specifically, use symmetric dilated convolution to obtain noisy speech context, help the model to enhance the speech for better denoising effect. Experimental results show that the enchanced whisper gains better performance both in the aspect of speech quality and intelligibility.

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Whispered Speech to Normal Speech Conversion Using Bidirectional LSTMs with Meta-network

Whispered Speech to Normal Speech Conversion Using Bidirecti...

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IEEE International Conference on Information Communication and signal processing (ICICSP)

作者： WeiWei Yu HaiLun Lian Jian Zhou HuaBin Wang Liang Tao MOE Key Laboratory of Intelligent Computing and Signal Processing Anhui University Hefei China

In this paper, we are interested in the conversion of whispered to normal speech. The baseline method uses standard bidirectional LSTM (BLSTM) RNN to predict both the spectral features and excitation parameters of the normal speech from whispered speech. Also, it employs STRAIGHT speech synthesizer. The BLSTM based whispered speech to normal speech conversion system is among the best systems in term of the naturalness of generated speech. However, in many cases, the model complexity and inference cost of BLSTM prevents its usage. As opposed to using standard BLSTM with sharing values, we propose a meta-network to generate non-shared weights for LSTM memory block in BLSTM (denote as meta-BLSTM). Besides, we use a low-rank approximation to generate the parameter matrix, which can reduce the model complexity. To our knowledge, this is the first study that uses meta-network to train a whispered to normal speech conversion system. To evaluate the performance of the proposed system, we performed experiments in the TIMIT dataset. Experimental results show that the proposed method achieves state-of-the-art performance.

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Multi-interactive dual-decoder for RGB-thermal salient object detection

arXiv

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arXiv 2020年

作者： Tu, Zhengzheng Li, Zhun Li, Chenglong Lang, Yang Tang, Jin Key Lab of Intelligent Computing and Signal Processing of Ministry of Education Anhui Provincial Key Laboratory of Multimodal Cognitive Computation School of Computer Science and Technology Anhui University Hefei230601 China

RGB-thermal salient object detection (SOD) aims to segment the common prominent regions of visible image and corresponding thermal infrared image that we call it RGBT SOD. Existing methods don’t fully explore and exploit the potentials of complementarity of different modalities and multi-type cues of image contents, which play a vital role in achieving accurate results. In this paper, we propose a multi-interactive dual-decoder to mine and model the multi-type interactions for accurate RGBT SOD. In specific, we first encode two modalities into multi-level multi-modal feature representations. Then, we design a novel dual-decoder to conduct the interactions of multi-level features, two modalities and global contexts. With these interactions, our method works well in diversely challenging scenarios even in the presence of invalid modality. Finally, we carry out extensive experiments on public RGBT and RGBD SOD datasets, and the results show that the proposed method achieves the outstanding performance against state-of-the-art algorithms. The source code has been released at: https://***/lz118/Multi-interactiveDual-decoder. Copyright © 2020, The Authors. All rights reserved.

关键词： Image segmentation

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An axial-ratio beam-width enhancement of antenna based on electromagnetic bandgap (EBG)

An axial-ratio beam-width enhancement of antenna based on el...

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IEEE Information Technology, Networking, Electronic and Automation Control Conference

作者： Shijie Huang Liang Zhang Chao Wang Changqing Liu Shenbing Wu Xianliang Wu Key Lab of Intelligent Computing & Signal Processing Ministry of Education Anhui University AnHui Province Key Laboratory of simulation and design for Electronic information system Hefei Normal university Hefei China

ISBN: (数字)9781728143903

ISBN: (纸本)9781728143910

In order to meet the requirements of the navigation system for antennas with wide 3-dB AR beam-width, this paper proposes an axial-ratio beam-width enhancement of antenna based on electromagnetic bandgap (EBG). The effect of surface wave on the circular polarization of the antenna is suppressed by loading two layers of mushroom-like EBG unit cells around the patch. The loading of the EBG increases the 3-dB AR beam-width of the antenna by 78% in the xoz plane and the by 84% in the yoz plane, the simulation and test results demonstrate the effectiveness of this method.

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Challenge-aware rgbt tracking

arXiv

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arXiv 2020年

作者： Li, Chenglong Liu, Lei Lu, Andong Ji, Qing Tang, Jin Key Lab of Intelligent Computing and Signal Processing Ministry of Education Anhui Provincial Key Laboratory of Multimodal Cognitive Computation School of Computer Science and Technology Anhui University Hefei230601 China

RGB and thermal source data suffer from both shared and specific challenges, and how to explore and exploit them plays a critical role to represent the target appearance in RGBT tracking. In this paper, we propose a novel challenge-aware neural network to handle the modality-shared challenges (e.g., fast motion, scale variation and occlusion) and the modality-specific ones (e.g., illumination variation and thermal crossover) for RGBT tracking. In particular, we design several parameter-shared branches in each layer to model the target appearance under the modality-shared challenges, and several parameter-independent branches under the modality-specific ones. Based on the observation that the modality-specific cues of different modalities usually contains the complementary advantages, we propose a guidance module to transfer discriminative features from one modality to another one, which could enhance the discriminative ability of some weak modality. Moreover, all branches are aggregated together in an adaptive manner and parallel embedded in the backbone network to efficiently form more discriminative target representations. These challenge-aware branches are able to model the target appearance under certain challenges so that the target representations can be learnt by a few parameters even in the situation of insufficient training data. From the experimental results we will show that our method operates at a real-time speed while performing well against the state-of-the-art methods on three benchmark datasets. Copyright © 2020, The Authors. All rights reserved.

关键词： Machine learning

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A circularly polarized low-profile Metasurface antenna based on CPW feed

A circularly polarized low-profile Metasurface antenna based...

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IEEE International Wireless Symposium (IWS)

作者： Changqing Liu Liang Zhang Shijie Huang Chao Wang Xingchuan Yu Xianliang Wu Key Lab of Intelligent Computing & Signal Processing Ministry of Education Anhui University AnHui Province Key Laboratory of simulation and design for Electronic information system Hefei Normal university Hefei China

ISBN: (数字)9781728167039

ISBN: (纸本)9781728167046

A low-profile circularly polarized Metasurfaces antenna based on compact coplanar waveguide (CPW) feed was proposed. The Metasurfaces consists of 16 periodic square-cut metal patches. An hourglass coupled slot was adopted to achieve broadband impedance matching. The antenna has a simple structure and a low cross section, and it can be implemented by a layer of a printed circuit substrate. A circular polarized wave is generated by changing the size of the cut angle of the Metasurfaces, and at the same time, the impedance bandwidth can be widened. To verify the simulation results, a 1λ 0 ×1λ 0 ×0.05λ 0 (at 10 GHz) model antenna was fabricated and measured. The simulation and measurement results show good consistency. The test results show that the -10dB return loss bandwidth reaches 45.3 %, and the circular polarization axis ratio(AR) is less than 3dB with a bandwidth of 18.5%.

关键词： Antenna measurements Polarization Bandwidth Metasurfaces Radar antennas Antenna feeds Coplanar waveguides

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Low Profile Dual-Band Antenna on an EBG Substrate

Low Profile Dual-Band Antenna on an EBG Substrate

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IEEE International Wireless Symposium (IWS)

作者： Shijie Huang Liang Zhang Chao Wang Changqing Liu Yifan Jiang Xianliang Wu Key Lab of Intelligent Computing & Signal Processing Ministry of Education Anhui University AnHui Province Key Laboratory of simulation and design for Electronic information system Hefei Normal university Hefei China

ISBN: (数字)9781728167039

ISBN: (纸本)9781728167046

This paper proposes a dual-band antenna based on the electromagnetic band gap structure suitable for WLAN communication systems. The proposed antenna is designed to work at 2.45/5.8 GHz WLAN band. By loading the EBG structure directly below a dual-frequency monopole antenna, the in-phase superposition of electromagnetic waves at the center frequency of the antenna is achieved. The antenna exhibits high gains of near 8.0 and 12.0 dB at the low and high working frequencies while maintaining the low profile characteristics.

关键词： Wireless LAN Directive antennas Reflector antennas Metamaterials Loaded antennas Gain Periodic structures

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