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Local-Global Temporal Difference Learning for Satellite Video Super-Resolution

IEEE Transactions on Circuits and systems for Video Technology 2024年第4期34卷 2789-2802页

作者： Xiao, Yi Yuan, Qiangqiang Jiang, Kui Jin, Xianyu He, Jiang Zhang, Liangpei Lin, Chia-Wen The School of Geodesy and Geomatics Wuhan University Wuhan430000 China The School of Computer Science and Technology Harbin Institute of Technology Harbin150000 China The State Key Laboratory of Information Engineering in Surveying Mapping and Remote Sensing Wuhan University Wuhan430000 China The Department of Electrical Engineering the Institute of Communications Engineering National Tsing Hua University Hsinchu30013 Taiwan

Optical-flow-based and kernel-based approaches have been extensively explored for temporal compensation in satellite Video Super-Resolution (VSR). However, these techniques are less generalized in large-scale or complex scenarios, especially in satellite videos. In this paper, we propose to exploit the well-defined temporal difference for efficient and effective temporal compensation. To fully utilize the local and global temporal information within frames, we systematically modeled the short-term and long-term temporal discrepancies since we observe that these discrepancies offer distinct and mutually complementary properties. Specifically, we devise a Short-term Temporal Difference Module (S-TDM) to extract local motion representations from RGB difference maps between adjacent frames, which yields more clues for accurate texture representation. To explore the global dependency in the entire frame sequence, a Long-term Temporal Difference Module (L-TDM) is proposed, where the differences between forward and backward segments are incorporated and activated to guide the modulation of the temporal feature, leading to a holistic global compensation. Moreover, we further propose a Difference Compensation Unit (DCU) to enrich the interaction between the spatial distribution of the target frame and temporal compensated results, which helps maintain spatial consistency while refining the features to avoid misalignment. Rigorous objective and subjective evaluations conducted across five mainstream video satellites demonstrate that our method performs favorably against state-of-the-art approaches. Code will be available at https://***/ XY-boy/LGTD. © 2023 IEEE.

关键词： Three dimensional displays

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TTST: A Top-k Token Selective Transformer for remote sensing Image Super-Resolution

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IEEE Transactions on Image Processing 2024年 33卷 738-752页

作者： Xiao, Yi Yuan, Qiangqiang Jiang, Kui He, Jiang Lin, Chia-Wen Zhang, Liangpei Wuhan University School of Geodesy and Geomatics Wuhan430079 China Harbin Institute of Technology School of Computer Science and Technology Harbin150001 China National Tsing Hua University Department of Electrical Engineering The Institute of Communications Engineering Hsinchu300 Taiwan Wuhan University State Key Laboratory of Information Engineering in Surveying Mapping and Remote Sensing Wuhan430079 China

Transformer-based method has demonstrated promising performance in image super-resolution tasks, due to its long-range and global aggregation capability. However, the existing Transformer brings two critical challenges for applying it in large-area earth observation scenes: (1) redundant token representation due to most irrelevant tokens;(2) single-scale representation which ignores scale correlation modeling of similar ground observation targets. To this end, this paper proposes to adaptively eliminate the interference of irreverent tokens for a more compact self-attention calculation. Specifically, we devise a Residual Token Selective Group (RTSG) to grasp the most crucial token by dynamically selecting the top-k keys in terms of score ranking for each query. For better feature aggregation, a Multi-scale Feed-forward Layer (MFL) is developed to generate an enriched representation of multi-scale feature mixtures during feed-forward process. Moreover, we also proposed a Global Context Attention (GCA) to fully explore the most informative components, thus introducing more inductive bias to the RTSG for an accurate reconstruction. In particular, multiple cascaded RTSGs form our final Top-k Token Selective Transformer (TTST) to achieve progressive representation. Extensive experiments on simulated and real-world remote sensing datasets demonstrate our TTST could perform favorably against state-of-the-art CNN-based and Transformer-based methods, both qualitatively and quantitatively. In brief, TTST outperforms the state-of-the-art approach (HAT-L) in terms of PSNR by 0.14 dB on average, but only accounts for 47.26% and 46.97% of its computational cost and parameters. The code and pre-trained TTST will be available at https://***/XY-boy/TTST for validation. © 1992-2012 IEEE.

关键词： remote sensing

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Latest Innovations in Intelligent Network-on-Chip Architectures: A Systematic Review 17

Latest Innovations in Intelligent Network-on-Chip Architectu...

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17th IEEE/ACM International Workshop on Network on Chip Architectures, NoCArc 2024

作者： Kakoulli, Elena Neapolis University Pafos Intelligent Systems Laboratory Department of Computer Science Pafos Cyprus Cyprus University of Technology Electrical Engineering and Computer Engineering and Informatics Limassol Cyprus

ISBN: (纸本)9798331506421

This review investigates the latest advancements in intelligent Network-on-Chip (NoC) architectures, focusing on innovations from 2022 to 2024. The integration of Artificial Intelligence (AI) and Machine Learning (ML) into NoC designs has driven significant improvements in performance, scalability, energy efficiency, and security. Key contributions include AI/ML-driven techniques to optimize routing, reduce latency, manage power consumption, and enhancing security against emerging threats. Despite these advancements, challenges such as computational overhead and integration complexities remain. This review consolidates these findings, addresses existing challenges, and proposes future research directions to further leverage AI and ML for developing robust and adaptable NoC architectures. © 2024 IEEE.

关键词： Federated learning

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Equalizer Zero-Determinant Strategy in Discounted Repeated Stackelberg Asymmetric Game

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Journal of systems science & Complexity 2024年第1期37卷 184-203页

作者： CHENG Zhaoyang CHEN Guanpu HONG Yiguang Key Laboratory of Systems and Control Academy of Mathematics and Systems ScienceChinese Academy of SciencesBeijing 100190China School of Mathematical Sciences University of Chinese Academy of SciencesBeijing 100049China School of Electrical Engineering and Computer Science KTH Royal Institute of Technology10044 StockholmSweden. Department of Control Science and Engineering Tongji UniversityShanghai 201804China Shanghai Research Institute for Intelligent Autonomous Systems Tongji UniversityShanghai 210201China

This paper focuses on the performance of equalizer zero-determinant(ZD)strategies in discounted repeated Stackelberg asymmetric *** the leader-follower adversarial scenario,the strong Stackelberg equilibrium(SSE)deriving from the opponents’best response(BR),is technically the optimal strategy for the ***,computing an SSE strategy may be difficult since it needs to solve a mixed-integer program and has exponential complexity in the number of *** this end,the authors propose an equalizer ZD strategy,which can unilaterally restrict the opponent’s expected *** authors first study the existence of an equalizer ZD strategy with one-to-one situations,and analyze an upper bound of its performance with the baseline SSE *** the authors turn to multi-player models,where there exists one player adopting an equalizer ZD *** authors give bounds of the weighted sum of opponents’s utilities,and compare it with the SSE ***,the authors give simulations on unmanned aerial vehicles(UAVs)and the moving target defense(MTD)to verify the effectiveness of the proposed approach.

关键词： Discounted repeated Stackelberg asymmetric game equalizer zero-determinant strategy strong Stackelberg equilibrium strategy

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Enhanced Soil Property Estimations from Earth Observation Data with Differential Evolution-Based Multi-Objective TSK Model 13

Enhanced Soil Property Estimations from Earth Observation Da...

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13th IEEE Congress on Evolutionary Computation, CEC 2024

作者： Tsakiridis, Nikolaos L. Samarinas, Nikiforos Kalopesa, Eleni Theocharis, John B. Zalidis, George C. Aristotle University of Thessaloniki Spectra Lab Group Laboratory of Remote Sensing Spectroscopy and Gis Department of Agriculture Thessaloniki54124 Greece Aristotle University of Thessaloniki Automation and Robotics Laboratory Electrical and Computer Engineering Thessaloniki54124 Greece

ISBN: (纸本)9798350308365

This paper introduces a novel approach integrating Differential Evolution (DE) with multi-objective optimization techniques for enhancing Type-1 Takagi-Sugeno-Kang (TSK) fuzzy rule-based systems to attain both fair predictive performance and enhanced interpretability within the context of explainable artificial intelligence. The developed approach encodes the whole knowledge base into one chromosome and endeavors to concurrently optimize the prediction accuracy, the number of rules, and the selection of relevant input features. The methodology was tested on Earth observation data for the estimation of soil health parameters via infrared spectroscopy, and more concretely i) on the 2015 LUCAS topsoil dataset to predict three key soil properties (namely, soil organic carbon, clay content, and pH) from laboratory spectra, and ii) on a set of PRISMA hyperspectral images to predict soil organic carbon in a region of northern Greece. Compared to the classical Random Forest (RF) algorithm, our proposed learning algorithm attains a fair balance between accuracy and interpretability, and is statistically equivalent to RF in terms of accuracy. The findings underscore the potential of the proposed methodology in refining TSK models and its applicability in Earth observation-driven predictions, paving the way for both enhanced modeling accuracy and sparse feature selection. © 2024 IEEE.

关键词： Fuzzy rules

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Near-zero-dispersion soliton and broadband modulational instability Kerr microcombs in anomalous dispersion

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Light(science & Applications) 2023年第2期12卷 220-231页

作者： Zeyu Xiao Tieying Li Minglu Cai Hongyi Zhang Yi Huang Chao Li Baicheng Yao Kan Wu Jianping Chen State Key Laboratory of Advanced Optical Communication Systems and Networks School of Electronic Information and Electrical EngineeringDepartment of Electronic EngineeringShanghai Jiao Tong UniversityShanghai 200240China Key Laboratory of Optical Fibre Sensing and Communications(Education Ministry of China) University of Electronic Science and Technology of ChinaChengdu 611731China

The developing advances of microresonator-based Ker cavity solitons have enabled versatile applications ranging from communication,signal processing to high-precision *** dispersion is the key factor determining the Kerr comb *** the zero group-velocity-dispersion(GVD)regime,low-noise and broadband microcomb sources are achievable,which is crucial to the application of the Kerr *** the GVD is almost vanished,higher-order dispersion can significantly affect the Kerr comb *** many studies have investigated the Kerr comb dynamics near the zero-dispersion regime in microresonator or fiber ring system,limited by dispersion profles and dispersion perturbations,the near-zero-dispersion soliton structure pumped in the anomalous dispersion side is still elusive so ***,we theoretically and experimentally investigate the microcomb dynamics in fiber-based Fabry-Perot microresonator with ultra-small anomalous *** obtain 2/3-octave-spaning microcombs with~10 GHz spacing,>84 THz span,and>8400 comb lines in the modulational instability(MI)state,without any external nonlinear spectral *** widely-spanned Ml combs are also able to enter the soliton ***,we report the first observation of anomalous-dispersion based near-zero-dispersion solitons,which exhibits a local repetition rate up to 8.6 THz,an individual pulse duration<100 fs,a span>32 THz and>3200 comb *** two distinct comb states have their own *** broadband MI combs possess high conversion efficiency and wide existing range,while the near-zero-dispersion soliton exhibits relatively low phase noise and ultra-high local repetition *** work complements the dynamics of Kerr cavity soliton near the zero-dispersion regime,and may stimulate cross-disciplinary inspirations ranging from dispersion-controlled microresonators to broadband coherent comb devices.

关键词： resonator dispersion pumped

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Deep Learning-Based Estimation of Arterial Stiffness from PPG Spectrograms: A Novel Approach for Non-Invasive Cardiovascular Diagnostics 46

Deep Learning-Based Estimation of Arterial Stiffness from PP...

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46th Annual International Conference of the IEEE engineering in Medicine and Biology Society, EMBC 2024

作者： Abrisham, Kiana Pilevar Alipour, Khalil Tarvirdizadeh, Bahram Ghamari, Mohammad Laboratory Department of Mechatronics Engineering School of Intelligent Systems Engineering College of Interdisciplinary Science and Technology Tehran Iran Kettering University Department of Electrical and Computer Engineering FlintMI United States

ISBN: (纸本)9798350371499

Cardiovascular diseases (CVDs), a leading cause of global mortality, are intricately linked to arterial stiffness, a key factor in cardiovascular health. Non-invasive assessment of arterial stiffness, particularly through Carotid-to-femoral Pulse Wave Velocity (cf-PWV) - the gold standard in this field - is vital for early detection and management of CVDs. This study introduces a novel approach, utilizing photoplethysmogram (PPG) signal spectrograms as inputs for deep learning models to estimate cf-PWV, a significant advancement over traditional methods. Employing a modified ResNet-18 architecture, we analyze PPG signals from digital, radial, and brachial arteries of a simulated dataset of 4374 healthy adults. Our methodology's innovation lies in its direct use of finely tuned spectrogram images, bypassing the complex feature extraction processes. This approach achieved R2 (correlation coefficient) values of up to 0.9902 for the digital artery, 0.9898 for the radial artery, and 0.9825 for the brachial artery, coupled with significantly lower Mean Absolute Percentage Errors (MAPE) of approximately 1.61% for the digital, 1.87% for the radial, and 2.08% for the brachial artery. These findings highlight the efficacy of PPG spectrograms, especially from the digital artery, in providing an accurate, user-friendly, and non-invasive method for cf-PWV estimation, thereby enhancing the capabilities of non-invasive cardiovascular diagnostics. © 2024 IEEE.

关键词： Photoplethysmography

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A multispectral acquisition system for potential detection of Flavescence dorée 30

A multispectral acquisition system for potential detection o...

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30th Telecommunications Forum, TELFOR 2022

作者： Barjaktarovic, Marko Faralli, Michele Bertamini, Massimo Bruzzone, Lorenzo Santoni, Massimo University of Belgrade School of Electrical Engineering Serbia University of Trento Remote Sensing Laboratory Italy Italy Fondazione Edmund Mach Research and Innovation Centre Italy University of Trento Remote Sensing Laboratory Department of Information Engineering and Computer Science Italy

ISBN: (数字)9781665472739

ISBN: (纸本)9781665472739

Agriculture is under constant pressure to increase the production rate and to provide more food or resources for other industries. Without precision agriculture it is not possible to fulfil these requirements. Medium and large-size farms already adopted this technology, but small farms are far from precision agriculture due to the high initial costs. In this paper we present a bespoke and affordable multispectral camera for precision farming and illustrate its application in the detection of Flavescence dorée. This is a grapevine disease that makes a great concern to grapevine producers in the whole Mediterranean region. Flavescence dorée is the only quarantine disease in the European region. The related mandatory control procedures include uprooting every infected plant, with the obligation to uproot the vineyard when the infection exceed the 20% of threshold infection, hence resulting in a high economical loss. Thus, it is highly important to detect even a single infected plant over an entire vineyard plot, preventing the spreading of Flavescence dorée at earliest stages. We used the in-house developed multispectral camera together with a hyperspectral camera to acquire data from two vineyards near Riva del Garda, Trentino, Italy, during the summer of 2022. These data are the starting point for selecting the optimal spectral bands for the detection of Flavescence dorée using affordable multispectral approaches and developing an appropriate classification algorithm. © 2022 IEEE.

关键词： Hyperspectral imaging

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Assessing the Impact of Physical Configuration and Lead Time on WRF Forecasting of an Extreme Wind Event

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Journal of Meteorological Research 2025年第1期39卷 154-171页

作者： Rocío OTERO Matías SUAREZ Edgardo PIEROBON Leandro MATURANO Ignacio MONTAMAT Juan Ezequiel SANCHEZ Lucia SANDALIO Andrés RODRIGUEZ Denis POFFO Hydrometeorology Laboratory Department of ExactPhysical and Natural SciencesNational University of CordobaCórdobaX5016GCAArgentina Institute for Advanced Studies in Engineering and Technology National Scientific and Technical Research CouncilCordobaX5016GCAArgentina Radar and Remote Sensing Laboratory Department of MathematicsAstronomyPhysics and Computer ScienceNational University of CordobaCordobaX5016HUAArgentina

The central region of Argentina is known to be a source of some most extreme weather events in the world,which are partially associated with the passage of cold fronts accompanied often by extreme wind *** may cause severe property damage and even loss of human ***,there is a lack of studies that evaluate the performance of the numerical weather prediction(NWP)models such as weather research and forecasting(WRF)model in anticipating this type of weather in the *** study compares the performance of the operational WRF in Argentina using four combinations of various planetary boundary layer(PBL)and microphysics parameterization schemes under varied lead times in predicting an extreme wind event(gusts>30 m s^(-1))in Central *** results demonstrate that the WRF model is capable of providing an acceptable prediction of wind speed during an extreme *** is found that no single combination outperforms the others,although there is a slight tendency for Combination A,which utilizes the Mellor-Yamada-Janjic(MYJ)parameterization for the PBL and the Eta similarity parameterization for the surface layer,to more accurately capture the extreme wind *** with wind gust observations at five weather stations,the wind gust parameterization predicted the intensity and occurrence time of the peak wind,with an acceptable bias(time of peak<±1 h).Analysis of grid configurations(resolutions of 4 vs 9/3/1 km)revealed that higher resolution does not imply an improvement in the wind gust forecast for this particular *** regard to lead time,a shorter lead time does not necessarily result in more accurate ***,it is beneficial to conduct multiple sensitivity runs in order to obtain and understand the dispersion of forecasted wind speeds.

关键词： extreme wind wind event weather research and forecasting(WRF)model wind gust forecast cold front lead time

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Progressive Motion Boosting for Video Frame Interpolation

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IEEE Transactions on Multimedia 2023年 25卷 8076-8090页

作者： Xiao, Jing Xu, Kangmin Hu, Mengshun Liao, Liang Wang, Zheng Lin, Chia-Wen Wang, Mi Satoh, Shin'Ichi The School of Computer Science Wuhan University Wuhan430072 China The School of Computer Science and Engineering Nanyang Technological University Singapore639798 Singapore The Department of Electrical Engineering the Institute of Communications Engineering National Tsing Hua University Hsinchu30013 Taiwan The State Key Laboratory of Information Engineering in Surveying Mapping and Remote Sensing Wuhan University Wuhan430072 China The Digital Content and Media Sciences Research Division National Institute of Informatics Tokyo101-8430 Japan

Video frame interpolation has made great progress in estimating advanced optical flow and synthesizing in-between frames sequentially. However, frame interpolation involving various resolutions and motions remains challenging due to limited or fixed pre-trained networks. Inspired by the success of the coarse-to-fine scheme for video frame interpolation, i.e., gradually interpolating frames of different resolutions, we propose a progressive boosting network (ProBoost-Net) based on a multi-scale framework to achieve flexible recurrent scales and then gradually optimize optical flow estimation and frame interpolation. Specifically, we designed a dense motion boosting (DMB) module to transfer features close to real motion to the decoded features from the later scales, which provides complementary information to refine the motion further. Furthermore, to ensure the accuracy of the estimated motion features at each scale, we propose a motion adaptive fusion (MAF) module that adaptively deals with motions with different receptive fields according to the motion conditions. Thanks to the framework’s flexible recurrent scales, we can customize the number of scales and make trade-offs between computation and quality depending on the application scenario. Extensive experiments with various datasets demonstrated the superiority of our proposed method over state-of-the-art approaches in various scenarios. © 2023 Institute of electrical and Electronics Engineers Inc.. All rights reserved.

关键词： Motion estimation

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