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A Dynamic Transformer Network for Vehicle Detection

IEEE Transactions on Consumer Electronics 2025年

作者： Tian, Chunwei Liu, Kai Zhang, Bob Huang, Zhixiang Lin, Chia-Wen Zhang, David Harbin Institute of Technology School of Computer Science and Technology Harbin15001 China Macao Special Administrative Region of China PAMI Research Group University of Macau 999078 China Anhui University Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education Key Laboratory of Electromagnetic Environmental Sensing Hefei230601 China National Tsing Hua University Department of Electrical Engineering Institute of Communications Engineering Hsinchu Taiwan School of Data Science Shenzhen518172 China

Stable consumer electronic systems can assist traffic better. Good traffic consumer electronic systems require collaborative work between traffic algorithms and hardware. However, performance of popular traffic algorithms containing vehicle detection methods based on deep networks via learning data relation rather than learning differences in different lighting and occlusions is limited. In this paper, we present a dynamic Transformer network for vehicle detection (DTNet). DTNet utilizes a dynamic convolution to guide a deep network to dynamically generate weights to enhance adaptability of an obtained detector. Taking into relations of different information account, a mixed attention mechanism based channel attention and Transformer is exploited to strengthen relations of channels and pixels to extract more salient information for vehicle detection. To overcome the drawback of difference in an image account, a translation-variant convolution relies on spatial location information to refine obtained structural information for vehicle detection. Experimental results illustrate that our DTNet is competitive for vehicle detection. Code of the proposed DTNet can be obtained at https://***/hellloxiaotian/DTNet. © 2025 IEEE.

关键词： Dynamic convolution Hybrid Attention Mechanism Transformer Vehicle Detection

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Emerging Technologies for 6G Non-Terrestrial-Networks: From Academia to Industrial Applications

arXiv

引用

arXiv 2024年

作者： Nguyen, Cong T. Saputra, Yuris Mulya Van Huynh, Nguyen Nguyen, Tan N. Hoang, Dinh Thai Nguyen, Diep N. Pham, Van-Quan Voznak, Miroslav Chatzinotas, Symeon Tran, Dinh-Hieu Institute of Fundamental and Applied Sciences Duy Tan University Ho Chi Minh City70000 Viet Nam Faculty of Information Technology Duy Tan University Da Nang50000 Viet Nam Internet Engineering Technology Department of Electrical Engineering and Informatics Vocational College Universitas Gadjah Mada Yogyakarta55281 Indonesia Department of Electrical Engineering and Electronics University of Liverpool LiverpoolL69 3GJ United Kingdom Communication and Signal Processing Research Group Faculty of Electrical and Electronics Engineering Ton Duc Thang University Ho Chi Minh City Viet Nam School of Electrical and Data Engineering University of Technology Sydney SydneyNSW2007 Australia Nokia Bell Labs Murray Hill NJ07974 United States Department of Telecommunications Faculty of Electrical Engineering and Computer Science VSB-Technical University of Ostrava Ostrava708 00 Czech Republic University of Luxembourg Esch-sur-Alzette4365 Luxembourg Nokia France

Terrestrial networks form the fundamental infrastructure of modern communication systems, serving more than 4 billion users globally. However, terrestrial networks are facing a wide range of challenges, from coverage and reliability to interference and congestion. As the demands of the 6G era are expected to be much higher, it is crucial to address these challenges to ensure a robust and efficient communication infrastructure for the future. To address these problems, Non-terrestrial Network (NTN) has emerged to be a promising solution. NTNs are communication networks that leverage airborne (e.g., unmanned aerial vehicles) and spaceborne vehicles (e.g., satellites) to facilitate ultra-reliable communications and connectivity with high data rates and low latency over expansive regions. This article aims to provide a comprehensive survey on the utilization of network slicing, Artificial Intelligence/Machine Learning (AI/ML), and Open Radio Access Network (ORAN) to address diverse challenges of NTNs from the perspectives of both academia and industry. Particularly, we first provide an in-depth tutorial on NTN and the key enabling technologies including network slicing, AI/ML, and ORAN. Then, we provide a comprehensive survey on how network slicing and AI/ML have been leveraged to overcome the challenges that NTNs are facing. Moreover, we present how ORAN can be utilized for NTNs. Finally, we highlight important challenges, open issues, and future research directions of NTN in the 6G era. © 2024, CC BY.

关键词： Radio access networks

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EU COST ACTION ON FUTURE GENERATION OPTICAL WIRELESS COMMUNICATION TECHNOLOGIES -NEWFOCUS CA19111 A White Paper

arXiv

引用

arXiv 2022年

作者： Ghassemlooy, Z. Khalighi, M. Ali Zvanovec, S. Stevens, N. Alves, L.N. Shrestha, A. Uysal, Murat Vegni, Anna Maria Diamantoulakis, Panagiotis D. Papanikolaou, Vasilis K. Karagiannidis, George K. Ortega, Beatriz Almenar, Vicenç Bouchet, Olivier Ladid, Latif Ozyegin University Turkey Department of Industrial Electrical and Mechanical Engineering Roma Tre University Italy Wireless Communications & Information Processing Group Department of Electrical and Computer Engineering Aristotle University of Thessaloniki Thessaloniki54 124 Greece Instituto de Telecomunicaciones y Aplicaciones Multimedia Universitat Politècnica deValència Camino de Vera s/n Valencia46022 Spain Orange Innovation Secan-Lab University of Luxembourg Luxembourg

The EU COST Action NEWFOCUS is focused on investigating radical solutions with the potential to impact the design of future wireless networks. It aims to address some of the challenges in OWC and establish it as an efficient technology that can satisfy the demanding requirements of backhaul and access network levels in 5G networks. This also includes the use of hybrid links that associate OWC with radiofrequency or wired/fiber-based technologies. The focus of this White Paper is on the use of optical wireless communication (OWC) as enabling technology in a range of areas outlined in HE's Pillar II including Health, Manufacturing, Intelligent Transportation Systems (ITS), Unmanned Aerial Vehicles and Network and Protocol. © 2022, CC BY-NC-ND.

关键词： 5G mobile communication systems

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Low-Complexity Loeffler DCT Approximations for Image and Video Coding

arXiv

引用

arXiv 2022年

作者： Coelho, D.F.G. Cintra, R.J. Bayer, F.M. Kulasekera, S. Madanayake, A. Martinez, P.A.C. Silveira, T.L.T. Oliveira, R.S. Dimitrov, V.S. Calgary AB Canada Signal Processing Group at Statistics Universidade Federal de Pernambuco PE Recife Brazil Departamento de Estatística LACESM Universidade Federal de Santa Maria RS Brazil Department of Electrical and Computer Engineering University of Akron OH United States Department of Electrical and Computer Engineering Florida International University FL United States Friedrich-Alexander-Universität Erlangen-Nürnberg Erlangen Germany RS Porto Alegre Brazil Programa de Pós-Graduação em Engenharia Elétrica Universidade Federal de Pernambuco Recife Brazil Department of Electrical and Computer Engineering University of Calgary CalgaryAB Canada

This paper introduced a matrix parametrization method based on the Loeffler discrete cosine transform (DCT) algorithm. As a result, a new class of eight-point DCT approximations was proposed, capable of unifying the mathematical formalism of several eight-point DCT approximations archived in the literature. Pareto-efficient DCT approximations are obtained through multicriteria optimization, where computational complexity, proximity, and coding performance are considered. Efficient approximations and their scaled 16- and 32-point versions are embedded into image and video encoders, including a JPEG-like codec and H.264/AVC and H.265/HEVC standards. Results are compared to the unmodified standard codecs. Efficient approximations are mapped and implemented on a Xilinx VLX240T FPGA and evaluated for area, speed, and power consumption. Copyright © 2022, The Authors. All rights reserved.

关键词： Discrete cosine transforms

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Reconfigurable Intelligent Surfaces Relying on Non-Diagonal Phase Shift Matrices

arXiv

引用

arXiv 2022年

作者： Li, Qingchao El-Hajjar, Mohammed Hemadeh, Ibrahim Shojaeifard, Arman Mourad, Alain A.M. Clerckx, Bruno Hanzo, Lajos The Electronics and Computer Science University of Southampton SouthamptonSO17 1BJ United Kingdom InterDigital LondonEC2A 3QR United Kingdom The Communications and Signal Processing Group Department of Electrical and Electronic Engineering Imperial College London LondonSW7 2AZ United Kingdom

Reconfigurable intelligent surfaces (RIS) have been actively researched as a potential technique for future wireless communications, which intelligently ameliorate the signal propagation environment. In the conventional design, each RIS element configures and reflects its received signal independently of all other RIS elements, which results in a diagonal phase shift matrix. By contrast, we propose a novel RIS architecture, where the incident signal impinging on one element can be reflected from another element after an appropriate phase shift adjustment, which increases the flexibility in the design of RIS phase shifts, hence, potentially improving the system performance. The resultant RIS phase shift matrix also has off-diagonal elements, as opposed to the pure diagonal structure of the conventional design. Compared to the state-of-art fully-connected/group-connected RIS structures, our proposed RIS architecture has lower complexity, while attaining a higher channel gain than the group-connected RIS structure, and approaching that of the fully-connected RIS structure. We formulate and solve the problem of maximizing the achievable rate of our proposed RIS architecture by jointly optimizing the transmit beamforming and the non-diagonal phase shift matrix based on alternating optimization and semi-define relaxation (SDR) methods. Moreover, the closed-form expressions of the channel gain, the outage probability and bit error ratio (BER) are derived. Simulation results demonstrate that our proposed RIS architecture results in an improved performance in terms of the achievable rate compared to the conventional architecture, both in single-user as well as in multi-user scenarios. © 2022, CC BY.

关键词： Bit error rate

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Low-complexity Scaling Methods for DCT-II Approximations

arXiv

引用

arXiv 2021年

作者： Coelho, D.F.G. Cintra, R.J. Madanayake, A. Perera, S. Canada The Signal Processing Group Departamento de Estatística Universidade Federal de Pernambuco Brazil The Department of Electrical and Computer Engineering Florida International University FL United States The Department of Mathematics Embry-Riddle Aeronautical University FL United States

This paper introduces a collection of scaling methods for generating 2N-point DCT-II approximations based on N-point low-complexity transformations. Such scaling is based on the Hou recursive matrix factorization of the exact 2N-point DCT-II matrix. Encompassing the widely employed Jridi-Alfalou-Meher scaling method, the proposed techniques are shown to produce DCT-II approximations that outperform the transforms resulting from the JAM scaling method according to total error energy and mean squared error. Orthogonality conditions are derived and an extensive error analysis based on statistical simulation demonstrates the good performance of the introduced scaling methods. A hardware implementation is also provided demonstrating the competitiveness of the proposed methods when compared to the JAM scaling method. Copyright © 2021, The Authors. All rights reserved.

关键词： Mean square error

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Variational Autoencoder with Embedded Student-t Mixture Model for Authorship Attribution

arXiv

引用

arXiv 2020年

作者： Boenninghoff, Benedikt Zeiler, Steffen Nickel, Robert M. Kolossa, Dorothea Cognitive Signal Processing Group Ruhr University Bochum Germany Department of Electrical and Computer Engineering Bucknell University LewisburgPA United States

Traditional computational authorship attribution describes a classification task in a closed-set scenario. Given a finite set of candidate authors and corresponding labeled texts, the objective is to determine which of the authors has written another set of anonymous or disputed texts. In this work, we propose a probabilistic autoencoding framework to deal with this supervised classification task. More precisely, we are extending a variational autoencoder (VAE) with embedded Gaussian mixture model to a Student-t mixture model. Autoencoders have had tremendous success in learning latent representations. However, existing VAEs are currently still bound by limitations imposed by the assumed Gaussianity of the underlying probability distributions in the latent space. In this work, we are extending the Gaussian model for the VAE to a Student-t model, which allows for an independent control of the "heaviness" of the respective tails of the implied probability densities. Experiments over an Amazon review dataset indicate superior performance of the proposed method. Copyright © 2020, The Authors. All rights reserved.

关键词： Students

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Unique English: An English Learning Application for Remedial Program Using Gamification Approach 2

Unique English: An English Learning Application for Remedial...

引用

2nd Joint International Conference on Emerging Computing Technology and Sports, JICETS 2019

作者： Yu, Yab Li Othman, Muhammad Fakri Bin Wahab, Mohd Helmy Abd Idrus, Syed Zulkarnain Syed Department of Multimedia in Faculty Computer Science and Information Technology Universiti Tun Hussein Onn Malaysia 86400 Batu Pahat Johor Malaysia Signal Imaging and Intelligence Focus Group Faculty of Electrical and Electronics Engineering Universiti Tun Hussein Onn Malaysia 86400 Batu Pahat Johor Malaysia School of Computer and Communication Engineering Universiti Malaysia Perlis Kubang Gajah Campus Arau Perlis02600 Malaysia Department of Multimedia in Faculty Computer Science and Information Technology Universiti Tun Hussein Onn Malaysia 86400 Batu Pahat Johor Malaysia

Literacy and Numeracy Screening (LINUS) that implemented in Malaysia as an educational program to improve literacy and numeracy among Year 1 to Year 3 pupils in all primary schools has been terminated in 2019. However, school-level remedial program still exists and its related application is limited in the market as there is no centralized syllabus for English remedial program yet. Therefore, an English learning application for remedial program called Unique English is designed with multimedia Mobile Content Development to overcome this problem by using previous LINUS centralized constructs. An application testing has been carried out in S.K. Pintas Raya, Parit Raja which involves pupils in remedial program and received satisfactory results with 83.2 % positive feedbacks obtained thus it can be concluded that Unique English is suitable to be implemented in remedial program. © Published under licence by IOP Publishing Ltd.

关键词： Software testing

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Model-based machine learning for joint digital backpropagation and PMD compensation

arXiv

引用

arXiv 2020年

作者： Bütler, Rick M. Häger, Christian Pfister, Henry D. Liga, Gabriele Alvarado, Alex Information and Communication Theory Lab Signal Processing Systems Group Department of Electrical Engineering Eindhoven University of Technology Eindhoven Netherlands Department of Electrical Engineering Chalmers University of Technology Gothenburg Sweden Department of Electrical and Computer Engineering Duke University Durham United States

In this paper, we propose a model-based machine-learning approach for dual-polarization systems by parameterizing the split-step Fourier method for the Manakov-PMD equation. The resulting method combines hardware-friendly time-domain nonlinearity mitigation via the recently proposed learned digital backpropagation (LDBP) with distributed compensation of polarization-mode dispersion (PMD). We refer to the resulting approach as LDBP-PMD. We train LDBP-PMD on multiple PMD realizations and show that it converges within 1% of its peak dB performance after 428 training iterations on average, yielding a peak effective signal-to-noise ratio of only 0.30 dB below the PMD-free case. Similar to state-of-the-art lumped PMD compensation algorithms in practical systems, our approach does not assume any knowledge about the particular PMD realization along the link, nor any knowledge about the total accumulated PMD. This is a significant improvement compared to prior work on distributed PMD compensation, where knowledge about the accumulated PMD is typically assumed. We also compare different parameterization choices in terms of performance, complexity, and convergence behavior. Lastly, we demonstrate that the learned models can be successfully retrained after an abrupt change of the PMD realization along the fiber. Copyright © 2020, The Authors. All rights reserved.

关键词： Polarization mode dispersion

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Discovering Phonetic Inventories with Crosslingual Automatic Speech Recognition

arXiv

引用

arXiv 2022年

作者： Żelasko, Piotr Feng, Siyuan Velázquez, Laureano Moro Abavisani, Ali Bhati, Saurabhchand Scharenborg, Odette Hasegawa-Johnson, Mark Dehak, Najim Center of Language and Speech Processing The Johns Hopkins University 3400 North Charles Street BaltimoreMD21218 United States Human Language Technology Center of Excellence The Johns Hopkins University 810 Wyman Park Drive BaltimoreMD21218 United States Multimedia Computing Group Delft University of Technology Van Mourik Broekmanweg 6 Delft2628 XE Netherlands Department of Electrical and Computer Engineering University of Illinois 405 N Mathews UrbanaIL61801 United States

The high cost of data acquisition makes Automatic Speech Recognition (ASR) model training problematic for most existing languages, including languages that do not even have a written script, or for which the phone inventories remain unknown. Past works explored multilingual training, transfer learning, as well as zero-shot learning in order to build ASR systems for these low-resource languages. While it has been shown that the pooling of resources from multiple languages is helpful, we have not yet seen a successful application of an ASR model to a language unseen during training. A crucial step in the adaptation of ASR from seen to unseen languages is the creation of the phone inventory of the unseen language. The ultimate goal of our work is to build the phone inventory of a language unseen during training in an unsupervised way without any knowledge about the language. In this paper, we 1) investigate the influence of different factors (i.e., model architecture, phonotactic model, type of speech representation) on phone recognition in an unknown language;2) provide an analysis of which phones transfer well across languages and which do not in order to understand the limitations of and areas for further improvement for automatic phone inventory creation;and 3) present different methods to build a phone inventory of an unseen language in an unsupervised way. To that end, we conducted mono-, multi-, and crosslingual experiments on a set of 13 phonetically diverse languages and several in-depth analyses. We found a number of universal phone tokens (IPA symbols) that are well-recognized cross-linguistically. Through a detailed analysis of results, we conclude that unique sounds, similar sounds, and tone languages remain a major challenge for phonetic inventory discovery. © 2022, CC BY-NC-ND.

关键词： Telephone sets

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