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arXiv 2021年

作者： Lei, Yi Chen, Bin Liga, Gabriele Balatsoukas-Stimming, Alexios Sun, Kaixuan Alvarado, Alex The School of Computer Science and Information Engineering Hefei University of Technology China The Electronic Systems group Department of Electrical Engineering Eindhoven University of Technology Netherlands State Key Laboratory of Information of Photonics and Optical Communications Beijing University of Posts and Telecommunications China Group Department of Electrical Engineering Eindhoven University of Technology Netherlands

The soft-aided bit-marking (SABM) algorithm is based on the idea of marking bits as highly reliable bits (HRBs), highly unreliable bits (HUBs), and uncertain bits to improve the performance of hard-decision (HD) decoders. The HRBs and HUBs are used to assist the HD decoders to prevent miscorrections and to decode those originally uncorrectable cases via bit flipping (BF), respectively. In this paper, an improved SABM algorithm (called iSABM) is proposed for staircase codes (SCCs). Similar to the SABM, iSABM marks bits with the help of channel reliabilities, i.e., using the absolute values of the log-likelihood ratios. The improvements offered by iSABM include: (i) HUBs being classified using a reliability threshold, (ii) BF randomly selecting HUBs, and (iii) soft-aided decoding over multiple SCC blocks. The decoding complexity of iSABM is comparable of that of SABM. This is due to the fact that on the one hand no sorting is required (lower complexity) because of the use of a threshold for HUBs, while on the other hand multiple SCC blocks use soft information (higher complexity). Additional gains of up to 0.53 dB with respect to SABM and 0.91 dB with respect to standard SCC decoding at a bit error rate of 10−6 are reported. Furthermore, it is shown that using 1-bit reliability marking, i.e., only having HRBs and HUBs, only causes a gain penalty of up to 0.25 dB with a significantly reduced memory requirement. © 2021, CC BY.

关键词： Stairs

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In-Situ Fluorine-Doped Znsno Thin Film and Thin-Film Transistor

SSRN

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SSRN 2023年

作者： Yin, Xuemei Lin, Delang Zhong, Wei Deng, Sunbin Xu, Yuming Chen, Yayi Lu, Lei Li, Guijun Kwok, Hoi Sing Li, Yi Chen, Rongsheng The School of artificial intelligence Zhuhai City Polytechnic College Zhuhai China The School of Microelectronics South China University of Technology Guangzhou China The School of Integrated Circuits Guangdong University of Technology Guangzhou China Purdue University West Lafayette United States The State Key Laboratory of Advanced Displays and Optoelectronics Technologies Department of Electronic and Computer Engineering The Hong Kong University of Science and Technology Hong Kong The Hong Kong University of Science and Technology Hong Kong Zhuhai Southern Integrated Circuit Design Service Center Zhuhai China Peking University China

In this paper, in-situ fluorine-doped ZnSnO (ZTO:F) thin films prepared by co-sputtering are proposed. It was found that the F had been successfully introduced into the ZTO thin films and distributed uniformly in the bulk. The corresponding top-contact bottom-gated ZTO:F thin film transistors (TFTs) were fabricated with an annealing temperature of 350 oC. The fabricated TFTs exhibit a field-effect mobility of 14.2 cm2V-1s-1, on-off ratio of over 109, and subthreshold swing (SS) as low as 87 mV/decade due to the incorporation of F. In addition, the bias stability of fabricated TFTs was also examined and the Vth shifts under negative gate bias stress are not more than ±0.1V even without any passivation. It is expected that the In-free ZTO:F amorphous oxide semiconductor and the corresponding TFTs have potential for low-cost and environmentally safe fabrication. © 2023, The Authors. All rights reserved.

关键词： Thin film transistors

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Random Occlusion Recovery with Noise Channel for Person Re-identification 16th

Random Occlusion Recovery with Noise Channel for Person Re-i...

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16th International Conference on intelligent Computing, ICIC 2020

作者： Zhang, Kun Wu, Di Yuan, Changan Qin, Xiao Wu, Hongjie Zhao, Xingming Zhang, Lijun Du, Yuchuan Wang, Hanli Institute of Machine Learning and Systems Biology School of Electronics and Information Engineering Tongji University Shanghai China Guangxi Academy of Science Nanning530025 China School of Computer and Information Engineering Nanning Normal University Nanning530299 China School of Computer Science and Technology Soochow University Suzhou215006 China School of Electronic and Information Engineering Suzhou University of Science and Technology Suzhou215009 China Fudan University Shanghai200433 China Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence Ministry of Education Shanghai China Collaborative Innovation Center of Intelligent New Energy Vehicle and School of Automotive Studies Tongji University Shanghai201804 China The Key Laboratory of Road and Traffic Engineering of the Ministry of Education Department of Transportation Engineering Tongji University Shanghai201804 China Department of Computer Science and Technology the Key Laboratory of Embedded System and Service Computing and Shanghai Institute of Intelligent Science and Technology Tongji University Shanghai200092 China

ISBN: (纸本)9783030607982

Person re-identification, as the basic task of a multi-camera surveillance system, plays an important role in a variety of surveillance applications. However, the current mainstream person re-identification model based on deep learning requires a lot of labeled data, which takes a lot of time and manpower. In this study, we proposed a person re-identification method based on random occlusion recovery with noise channel. We add random occlusion blocks to the original image, use the GAN model for repair, and use the repaired image to expand the original training set. After that, the generated image is adjusted through the noise channel. Finally, we use the enhanced data set to train the baseline model. Our model achieves the state-of-the-art on Market-1501 dataset, proving that the method is effective. © 2020, Springer Nature Switzerland AG.

关键词： Generative adversarial networks

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Regionsketch: Interactive and rapid creation of 3D models with rich details 27

Regionsketch: Interactive and rapid creation of 3D models wi...

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27th Pacific Conference on computer Graphics and Applications, Pacific Graphics 2019

作者： Liu, Shuai Hou, Fei Hao, Aimin Qin, Hong State Key Laboratory of Virtual Reality Technology and Systems Beihang University China State Key Laboratory of Computer Science Institute of Software Chinese Academy of Sciences China Department of Computer Science Stony Brook University United States

ISBN: (纸本)9783038680994

In this paper, we articulate a new approach to interactive generation of 3D models with rich details by way of sketching sparse 2D strokes. Our novel method is a natural extension of Poisson vector graphics (PVG). We design new algorithms that distinguish themselves from other existing sketch-based design systems with three unique features: (1) A novel sketch metaphor to create freeform surface based on Poisson's equation, which is simple, intuitive, and free of ambiguity;(2) Convenient and flexible user interface that affords the user to add rich details to the surface with simple sketch input;and (3) Rapid model creation with sparse strokes, which enables novice users to enjoy the utilities of our system to create expected 3D models. We validate the proposed method through a large repository of interactively sketched examples. Our experiments and produced results confirm that our new method is a simple yet efficient design tool for modeling free-form shapes with simple and intuitive 2D sketches input. © 2019 The Author(s) Eurographics Proceedings © 2019 The Eurographics Association.

关键词： User interfaces

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Student-teacher feature pyramid matching for anomaly detection

arXiv

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arXiv 2021年

作者： Wang, Guodong Han, Shumin Ding, Errui Huang, Di State Key Laboratory of Software Development Environment Beihang University Beijing China School of Computer Science and Engineering Beihang University Beijing China Department of Computer Vision Technology Baidu Inc. Beijing China

Anomaly detection is a challenging task and usually formulated as an one-class learning problem for the unexpectedness of anomalies. This paper proposes a simple yet powerful approach to this issue, which is implemented in the student-teacher framework for its advantages but substantially extends it in terms of both accuracy and efficiency. Given a strong model pre-trained on image classification as the teacher, we distill the knowledge into a single student network with the identical architecture to learn the distribution of anomaly-free images and this one-step transfer preserves the crucial clues as much as possible. Moreover, we integrate the multi-scale feature matching strategy into the framework, and this hierarchical feature matching enables the student network to receive a mixture of multi-level knowledge from the feature pyramid under better supervision, thus allowing to detect anomalies of various sizes. The difference between feature pyramids generated by the two networks serves as a scoring function indicating the probability of anomaly occurring. Due to such operations, our approach achieves accurate and fast pixel-level anomaly detection. Very competitive results are delivered on the MVTec anomaly detection dataset, superior to the state of the art ones. © 2021, CC BY.

关键词： Anomaly detection

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Enhancing Motor Imagery EEG Signal Classification with Simplified GoogLeNet

Enhancing Motor Imagery EEG Signal Classification with Simpl...

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International Winter Workshop on Brain-computer Interface (BCI)

作者： Lu Wang Junkongshuai Wang Bo Wen Wei Mu Lusheng Liu Jiaguan Han Lihua Zhang Jie Jia Xiaoyang Kang Shanghai Engineering Research Center of AI & Robotics MOE Frontiers Center for Brain Science State Key Laboratory of Medical NeurobiologyAcademy for Engineering & Technology Laboratory for Neural Interface and Brain Computer Interface Engineering Research Center of AI & Robotics Ministry of Education Institute of AI & Robotics Institute of Meta-MedicalFudan University Shanghai China Ji Hua Laboratory Guangdong Province Foshan China Yiwu Research Institute of Fudan University Chengbei Road Yiwu City Zhejiang China Department of Rehabilitation Medicine Huashan Hospital Fudan University Shanghai China Research Center for Intelligent Sensing Zhejiang Lab Hangzhou China

The brain-computer interface is a novel tool for interaction between the brain and external devices, and is an important tool at the forefront of international brain science research. Motor imagery does not require external stimulation and is one of the most widely used BCI paradigms, and is now widely used to address the treatment of neurological impairments such as paralysis, stroke, and acromegaly. Electrophysiological source imaging is a technique based on the observation of electromagnetic signals from the cerebral cortex, reflecting the electrophysiological activity of brain nerve cells on the scalp surface of the brain. The wavelet transform, on the other hand, is commonly used for the processing of non-smooth signals and aims to extract excellent signal features. This paper combines these two algorithms as feature extraction methods. In recent years, deep learning has been increasingly combined with MI-EEG-based BCI. GoogLeNet is one of the most classical convolutional neural networks and has made a splash in ImageNet image recognition. However, using GoogLeNet to train the BCI public dataset BCI IV IIa and dataset HGD has shown problems such as long training time, overfitting, and gradient disappearance. In response, this paper proposes an improved and streamlined version of GoogLeNet for training based on this dataset to achieve an overall improvement in accuracy, training time, number of parameters, and other indicators. It is useful for the realistic application of MI-based BCI systems.

关键词： Training Wavelet transforms Surface waves Scalp Pattern classification Electrophysiology Streaming media

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A new family of binary sequences with low correlation via elliptic curves

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IEEE Transactions on Information Theory 2025年

作者： Jin, Lingfei Ma, Liming Xing, Chaoping Zhu, Runtian Fudan University Shanghai Key Laboratory of Intelligent Information Processing School of Computer Science Shanghai200433 China State Key Laboratory of Cryptology Beijing100878 China University of Science and Technology of China School of Mathematical Sciences Hefei230026 China Shanghai Jiao Tong University School of Electronic Information and Electrical Engineering Shanghai200240 China

In the realm of modern digital communication, cryptography, and signal processing, binary sequences with good correlation properties play a pivotal role. In the literature, considerable efforts have been dedicated to constructing good binary sequences of various lengths. As a consequence, numerous constructions of good binary sequences have been put forward. However, the majority of known constructions leverage the multiplicative cyclic group structure of finite fields Fpn, where p is a prime and n is a positive integer. Recently, the authors made use of the cyclic group structure of all rational places of the rational function field over the finite field F pn, and firstly constructed good binary sequences of length pn + 1 via cyclotomic function fields over Fpn for any prime p [8], [10]. This approach has paved a new way for constructing good binary sequences. Motivated by the above constructions, we exploit the cyclic group structure of rational points of elliptic curves to design a family of binary sequences of length 2n+1+t with low correlation for many given integers |t| ⩽ 2(n+2)/2. Specifically, for any positive integer d with gcd(d;2n+ 1 + t) = 1, we introduce a novel family of binary sequences of length 2n+ 1 + t, size qd−1 − 1, correlation bounded by (2d + 1) · 2(n+2)/2 + |t|, and large linear complexity via elliptic curves. © 1963-2012 IEEE.

关键词： Rational functions

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Continual Learning in the Presence of Repetition

arXiv

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arXiv 2024年

作者： Hemati, Hamed Pellegrini, Lorenzo Duan, Xiaotian Zhao, Zixuan Xia, Fangfang Masana, Marc Tscheschner, Benedikt Veas, Eduardo Zheng, Yuxiang Zhao, Shiji Li, Shao-Yuan Huang, Sheng-Jun Lomonaco, Vincenzo van de Ven, Gido M. Institute for Computer Science University of St. Gallen Rosenbergstrasse 30 St. Gallen9000 Switzerland Department of Computer Science University of Bologna Via dell’Università 50 Cesena47521 Italy The University of Chicago 5801 S Ellis Ave Chicago60637 United States Argonne National Laboratory 9700 S Cass Ave Lemont60439 United States Graz University of Technology Rechbauerstraße 12 Graz8010 Austria TU Graz - SAL Dependable Embedded Systems Lab Silicon Austria Labs Graz8010 Austria Know-Center GmbH Sandgasse 36/4 Graz8010 Austria MIIT Key Laboratory of Pattern Analysis and Machine Intelligence Nanjing University of Aeronautics and Astronautics Nanjing211106 China Department of Computer Science University of Pisa Piano Secondo Largo Bruno Pontecorvo 3 Pisa56127 Italy Department of Electrical Engineering KU Leuven Kasteelpark Arenberg 10 Leuven3001 Belgium

Continual learning (CL) provides a framework for training models in ever-evolving environments. Although re-occurrence of previously seen objects or tasks is common in real-world problems, the concept of repetition in the data stream is not often considered in standard benchmarks for CL. Unlike with the rehearsal mechanism in buffer-based strategies, where sample repetition is controlled by the strategy, repetition in the data stream naturally stems from the environment. This report provides a summary of the CLVision challenge at CVPR 2023, which focused on the topic of repetition in class-incremental learning. The report initially outlines the challenge objective and then describes three solutions proposed by finalist teams that aim to effectively exploit the repetition in the stream to learn continually. The experimental results from the challenge highlight the effectiveness of ensemble-based solutions that employ multiple versions of similar modules, each trained on different but overlapping subsets of classes. This report underscores the transformative potential of taking a different perspective in CL by employing repetition in the data stream to foster innovative strategy design. © 2024, CC BY.

关键词： Contrastive Learning

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Resilience of Quantum key Distribution Source Against Laser-Damage Attack by a Variety of Lasers

Resilience of Quantum Key Distribution Source Against Laser-...

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Conference on Lasers and Electro-Optics Europe (CLEO EUROPE)

作者： Daria Ruzhitskaya Irina Zhluktova Anastasiya Ponosova Daniil Trefilov Poompong Chaiwongkhot Anqi Huang Vladimir Kamynin Vadim Makarov Russian Quantum Center Skolkovo Moscow Russia NTI Center for Quantum Communications National University of Science and Technology MISiS Moscow Russia Prokhorov General Physics Institute of Russian Academy of Sciences Moscow Russia MIREA - Russian Technological University Moscow Russia Vigo Quantum Communication Center University of Vigo Vigo Spain Department of Physics Faculty of Science Mahidol University Bangkok Thailand State Key Laboratory of High Performance Computing Institute for Quantum Information College of Computer Science and Technology National University of Defense Technology Changsha China Shanghai Branch National Laboratory for Physical Sciences at Microscale CAS Center for Excellence in Quantum Information University of Science and Technology of China Shanghai People's Republic of China

ISBN: (纸本)9798350345995

Quantum key distribution (QKD) systems provide quantum-safe key exchange. Therefore, complete security analysis of implementations of QKD protocols is in the focus of interest of a worldwide information-security community. For today, a number of QKD loopholes are closed by countermeasures, which are also considered in emerging QKD security evaluation and certification [1]–[3]. However, new threats to practical QKD implementations are still found, such as the laser-damage attack, which is a powerful hacking strategy. In investigations, CW laser radiation is most often used, but in contrast to it, the interaction of pulsed laser radiation with optical materials may lead to a wide range of effects, like nonlinear effects, dielectric breakdown, etc.

关键词： Fiber optic components High power lasers Nonlinear effects Optical materials Quantum key distribution Quantum key distribution networks

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Comparative effect of allopolyploidy on transposable element composition and gene expression between Gossypium hirsutum and its two diploid progenitors

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Journal of Integrative Plant Biology 2019年第1期61卷 45-59页

作者： Hua Cheng Gaofei Sun Shoupu He Wenfang Gong Zhen Peng Ruiping Wang Zhongxu Lin Xiongming Du Research Base Anyang Institute of TechnologyState Key Laboratory of Cotton BiologyInstitute of Cotton Researchthe Chinese Academy of Agricultural Science College of Plant Science & Technology of Huazhong Agricultural University Department of Computer Science and Information Engineering Anyang Institute of Technology

An allopolyploidization event formed allotetraploid Gossypium species from an A-genome diploid species and a D-genome diploid species. To explore the responses of transposable elements(TEs) to allopolyploidy, we assembled parallel TE datasets from G. hirsutum, G. arboreum and G. raimondii and analyzed the TE types and the effects of TEs on orthologous gene expression in the three Gossypium *** was the most abundant TE type and most TEs were located $500 bp from genes in all three genomes. In G. hirsutum, 35.6% of genes harbored TE insertions, whereas insertions were more frequent in G. arboreum and G. raimondii. G. hirsutum had the highest proportion of uniquely matching 24-nt small interfering RNAs(siRNAs) that targeted TEs. TEs,particularly those targeted by 24-nt siRNAs, were associated with reduced gene expression, but the effect of TEs on orthologous gene expression varied substantially among species. Orthologous gene expression levels in G. hirsutum were intermediate between those of G. arboreum and G. raimondii, which did not experience TE expansion or reduction resulting from allopolyploidization. This study underscores the diversity of TEs co-opted by host genes and provides insights into the roles of TEs in regulating gene expression in Gossypium.

关键词： progenitors allopolyploidization

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