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Record High Temperatures in the Ocean in 2024

Advances in Atmospheric sciences 2025年第6期 1092-1109页

作者： Lijing CHENG John ABRAHAM Kevin E.TRENBERTH James REAGAN Huai-Min ZHANG Andrea STORTO Karina VON SCHUCKMANN Yuying PAN Yujing ZHU Michael E.MANN Jiang ZHU Fan WANG Fujiang YU Ricardo LOCARNINI John FASULLO Boyin HUANG Garrett GRAHAM Xungang YIN Viktor GOURETSKI Fei ZHENG Yuanlong LI Bin ZHANG Liying WAN Xingrong CHEN Dakui WANG Licheng FENG Xiangzhou SONG Yulong LIU Franco RESEGHETTI Simona SIMONCELLI Gengxin CHEN Rongwang ZHANG Alexey MISHONOV Zhetao TAN Wangxu WEI Huifeng YUAN Guancheng LI Qiuping REN Lijuan CAO Yayang LU Juan DU Kewei LYU Albertus SULAIMAN Michael MAYER Huizan WANG Zhanhong MA Senliang BAO Henqian YAN Zenghong LIU Chunxue YANG Xu LIU Zeke HAUSFATHER Tanguy SZEKELY Flora GUES National Key Laboratory of Earth System Numerical Modeling and Application Institute of Atmospheric PhysicsChinese Academy of Sciences University of St. Thomas School of Engineering NSF National Center for Atmospheric Research University of Auckland National Oceanic and Atmospheric Administration National Centers for Environmental Information National Research Council (CNR) Institute of Marine Sciences (ISMAR) Mercator Ocean International Department of Earth and Environmental Science University of Pennsylvania Institute of Oceanology Chinese Academy of Sciences National Marine Environmental Forecasting Center Ministry of Natural Resources of China North Carolina Institute for Climate Studies (NCICS) North Carolina State University Oceanographic Data Center Chinese Academy of Sciences College of Oceanography Hohai University National Marine Data and Information Service Istituto Nazionale di Geofisica eVulcanologia Sede di Bologna South China Sea Institute of Oceanology Chinese Academy of Sciences ESSIC/CISESS-MD University of Maryland Computer Network Information Center Chinese Academy of Sciences Eco-Environmental Monitoring and Research Center Pearl River Valley and South China Sea Ecology and Environment Administration Ministry of Ecology and Environment National Meteorological Information Center China Meteorological Administration International Research Center of Big Data for Sustainable Development Goals Xiamen University Research Center for Climate and Atmosphere National Research and Innovation Agency (BRIN) Research Department European Centre for Medium-Range Weather Forecasts Department of Meteorology and Geophysics University of Vienna College of Meteorology and Oceanography National University of Defense Technology State Key Laboratory of Satellite Ocean Environment Dynamics Second Institute of OceanographyMinistry of Natural Resources Stripe Inc. South San Francisco Ocean Scope CELAD

Heating in the ocean has continued in 2024 in response to increased greenhouse gas concentrations in the atmosphere,despite the transition from an El Ni?o to neutral conditions. In 2024, both global sea surface temperature(SST) and upper2000 m ocean heat content(OHC) reached unprecedented highs in the historical record. The 0–2000 m OHC in 2024exceeded that of 2023 by 16 ± 8 ZJ(1 Zetta Joules = 1021 Joules, with a 95% confidence interval)(IAP/CAS data), which is confirmed by two other data products: 18 ± 7 ZJ(CIGAR-RT reanalysis data) and 40 ± 31 ZJ(Copernicus Marine data,updated to November 2024). The Indian Ocean, tropical Atlantic, Mediterranean Sea, North Atlantic, North Pacific, and Southern Ocean also experienced record-high OHC values in 2024. The global SST continued its record-high values from2023 into the first half of 2024, and declined slightly in the second half of 2024, resulting in an annual mean of 0.61°C ±0.02°C(IAP/CAS data) above the 1981–2010 baseline, slightly higher than the 2023 annual-mean value(by 0.07°C ±0.02°C for IAP/CAS, 0.05°C ± 0.02°C for NOAA/NCEI, and 0.06°C ± 0.11°C for Copernicus Marine). The record-high values of 2024 SST and OHC continue to indicate unabated trends of global heating.

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Annular pupil in optical scanning holography

Annular pupil in optical scanning holography

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2019 Conference on Digital Holography and Three-Dimensional Imaging, DH 2019

作者： Zhang, Yaping Wang, Rende Wang, Lin Tsang, Peter Poon, T.-C. Key Lab of Laser Information Processing Technology and Application Kunming University of Science and Technology Kunming650500 China School of Electronic and Optical Engineering Nanjing University of Science and Technology Nanjing Jiangsu210094 China Department of Electronic Engineering City University of Hong Kong 83 Tat Chee Avenue Kowloon Hong Kong Bradley Department of Electrical and Computer Engineering Virginia Tech BlacksburgVA24061 United States

Optical scanning holography (OSH) is a variant of two-pupil heterodyning image processing. We investigate the use of one pupil as a delta function and the other being an annulus as an extended application of OSH. ... 详细信息

ISBN: (纸本)9781943580590

关键词： Holography

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Attend to the Difference: Cross-Modality Person Re-identification via Contrastive Correlation

arXiv

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arXiv 2019年

作者： Zhang, Shizhou Yang, Yifei Wang, Peng Liang, Guoqiang Zhang, Xiuwei Zhang, Yanning National Engineering Laboratory for Integrated Aero-Space-Ground-Ocean Big Data Application Technology School of Computer Science and Engineering Northwestern Polytechnical University Xi'an710071 China

The problem of cross-modality person reidentification has been receiving increasing attention recently, due to its practical significance. Motivated by the fact that human usually attend to the difference when they compare two similar objects, we propose a dual-path cross-modality feature learning framework which preserves intrinsic spatial structures and attends to the difference of input cross-modality image pairs. Our framework is composed by two main components: a Dual-path Spatial-structure-preserving Common Space Network (DSCSN) and a Contrastive Correlation Network (CCN). The former embeds cross-modality images into a common 3D tensor space without losing spatial structures, while the latter extracts contrastive features by dynamically comparing input image pairs. Note that the representations generated for the input RGB and Infrared images are mutually dependant to each other. We conduct extensive experiments on two public available RGB-IR ReID datasets, SYSU-MM01 and RegDB, and our proposed method outperforms state-of-the-art algorithms by a large margin with both full and simplified evaluation modes. Copyright © 2019, The Authors. All rights reserved.

关键词： Infrared imaging

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Vehicle Re-Identification in Aerial Imagery: Dataset and Approach

Vehicle Re-Identification in Aerial Imagery: Dataset and App...

引用

International Conference on computer Vision (ICCV)

作者： Peng Wang Bingliang Jiao Lu Yang Yifei Yang Shizhou Zhang Wei Wei Yanning Zhang School of Computer Science and Engineering Northwestern Polytechnical University Xi’an China National Engineering Laboratory for Integrated Aero-Space-Ground-Ocean Big Data Application Technology China

ISBN: (数字)9781728148038

ISBN: (纸本)9781728148045

In this work, we construct a large-scale dataset for vehicle re-identification (ReID), which contains 137k images of 13k vehicle instances captured by UAV-mounted cameras. To our knowledge, it is the largest UAV-based vehicle ReID dataset. To increase intra-class variation, each vehicle is captured by at least two UAVs at different locations, with diverse view-angles and flight-altitudes. We manually label a variety of vehicle attributes, including vehicle type, color, skylight, bumper, spare tire and luggage rack. Furthermore, for each vehicle image, the annotator is also required to mark the discriminative parts that helps them to distinguish this particular vehicle from others. Besides the dataset, we also design a specific vehicle ReID algorithm to make full use of the rich annotation information. It is capable of explicitly detecting discriminative parts for each specific vehicle and significantly outperforming the evaluated baselines and state-of-the-art vehicle ReID approaches.

关键词： Image color analysis Cameras Feature extraction Task analysis Image resolution Tires Visualization

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Solder joint image adaptive block compressive sensing with convex optimisation and Gini index

Solder joint image adaptive block compressive sensing with c...

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7th International Symposium on Test Automation and Instrumentation, ISTAI 2018

作者： Zhao, Huihuang Wang, Yaonan Zheng, Jinhua Qiao, Zhijun Zhang, Yun Department of Computer Science and Technology College of Computer Science and Technology Hengyang Normal University Hengyang Hunan China Hunan Provincial Key Laboratory of Intelligent Information Processing and Application Hengyang China Department of Electrical and Engineering College of Electrical and Information Engineering Hunan University Changsha China School of Mathematical and Statistical Sciences University of Texas Rio Grande ValleyTX United States Institute of Radio and TV Technology Communication University of Zhejiang Hangzhou310018 China

This study aims to improve the performance in solder joint image compression and reconstruction. A novel adaptive block compressive sensing with convex optimisation and Gini index (Ad_BCSGB_Gini) methodology for solder joint image compression and reconstruction is proposed. At first, the image is split into square blocks and each block is resized into a row which consists of a new image. Then, the new image is transformed into a sparse signal by an orthogonal basis matrix, and the image reconstruction is handled as a convex optimisation problem. Moreover, a gradient-based method which has fast computational speed is used to reconstruct image. There is a control factor which controls a norm l1 in the optimisation problem. To achieve the best performance, at last, the proposed method adaptively selects the best result by comparing Gini index of the reconstruction results based on different control factor values. Experimental results with different methods indicate that the Ad_BCSGB_Gini method is able to achieve the best performance in quantisation comparison than several classical algorithms, and Ad_BCSGB_Gini has a good robustness. © 2019 Institution of engineering and Technology. All rights reserved.

关键词： Convex optimization

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Reverse-engineering bar charts using neural networks

arXiv

引用

arXiv 2020年

作者： Zhou, Fangfang Zhao, Yong Chen, Wenjiang Tan, Yijing Xu, Yaqi Chen, Yi Liu, Chao Zhao, Ying School of Computer Science and Engineer Central South University Changsha China Beijing Key Laboratory of Big Data Technology for Food Safety Beijing Technology and Business University Beijing China Institute of Systems Engineering Academy of Military Sciences Beijing China Rail Data Research and Application Key Laboratory of Hunan Province Changsha China

Reverse-engineering bar charts extracts textual and numeric information from the visual representations of bar charts to support application scenarios that require the underlying information. In this paper, we propose a neural network-based method for reverse-engineering bar charts. We adopt a neural network-based object detection model to simultaneously localize and classify textual information. This approach improves the efficiency of textual information extraction. We design an encoder–decoder framework that integrates convolutional and recurrent neural networks to extract numeric information. We further introduce an attention mechanism into the framework to achieve high accuracy and robustness. Synthetic and real-world datasets are used to evaluate the effectiveness of the method. To the best of our knowledge, this work takes the lead in constructing a complete neural network-based method of reverse-engineering bar charts. Copyright © 2020, The Authors. All rights reserved.

关键词： Reverse engineering

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An Ultra-compact Broadband TE-pass Nanofocusing Structure

An Ultra-compact Broadband TE-pass Nanofocusing Structure

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Asia Communications and Photonics Conference and Exhibition (ACP)

作者： Kejian Zhu Xu Pengfei Pengfei Sun Xingpeng Liu Haiou Li Zhiping Zhou Nano-optoelectronics Frontier Center of Ministry of Education Peking University Beijing China State Key Laboratory of Advanced Optical Communication Systems and Networks School of Electronics Engineering and Computer Science Peking University Beijing China Guangxi Key Laboratory of Precision Navigation Technology and Application Guilin University of Electronic Technology Guilin China

We propose a broadband structure which integrates polarization and nanofocusing functions into a single device with 3.8x4 μm 2 footprint. The bandwidth is over 200 nm with insert loss (IL) smaller than 1.68 dB. ... 详细信息

ISBN: (数字)9781943580828

ISBN: (纸本)9781728176567

关键词： Bandwidth Nanoscale devices Optical fiber communication Broadband communication System-on-chip Photonics Periodic structures

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Traffic Management using Logistic Regression with Fuzzy Logic

Traffic Management using Logistic Regression with Fuzzy Logi...

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2018 International Conference on Computational Intelligence and Data science, ICCIDS 2018

作者： Tomar, Anurag Singh Singh, Mridula Sharma, Girish Arya, K.V. School of Computer Science University of Petroleum and Energy Studies Dehradun India Department of Computer Science Engineering Uttarakhand Technical University Dehradun India Department of Electronics and Telecommunication College of Engineering Roorkee India Department of Master of Computer Application Bhai Parmanand Institute of Business Studies Shakarpur New Delhi India Department of Computer Science Engineering Institute of Engineering and Technology Lucknow India

Traffic congestion is one of the major problems in most of the cities across the globe and it leads to several other problems like pollution, time wastage, long traffic queues on roads and may cause accidents. Improvement of Road infrastructure is not always the feasible solution to resolve the problem. In real life scenario shorter distance route towards the destination attracts majority of people and at times it may aggravate traffic jam conditions. Therefore, a real time traffic information for intelligent decision making to decide the route preference is required. Moreover, a system which considers the factor of distance towards the destination along with real time traffic situation on that route will add to the solution to the congestion problem. certain parameters such as distance, weather condition, road location, day of week and time are considered to formulate the problem and to find solutions to these problems This paper outlines a combination of logistic regression with fuzzy logic such that a smart decision to preferred path can be taken. It is used to compute the probability of each possible path by considering the real time traffic information, distance and road condition and later is used to take decisions in an uncertain scenario. Proposed Method considers the number of parameters like distance, weather condition, road location, day of week and time. © 2018 The Authors. Published by Elsevier Ltd.

关键词： Fuzzy logic

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A robust non-linear and feature-selection image fusion theory

arXiv

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arXiv 2019年

作者： Fang, Aiqing Zhao, Xinbo Zhang, Yanning Natl. Engineering Laboratory for Integrated Aero-Space-Ground-Ocean Big Data Application Technology School of Computer Science and Engineering Northwestern Polytechnical University Xian710072 China

The human visual perception system has strong robustness in image fusion. This robustness is based on human visual perception system's characteristics of feature selection and non-linear fusion of different features. In order to simulate the human visual perception mechanism in image fusion tasks, we propose a multi-source image fusion framework that combines illuminance factors and attention mechanisms. The framework effectively combines traditional image features and modern deep learning features. First, we perform multi-scale decomposition of multi-source images. Then, the visual saliency map and the deep feature map are combined with the illuminance fusion factor to perform high-low frequency nonlinear fusion. Secondly, the characteristics of high and low frequency fusion are selected through the channel attention network to obtain the final fusion map. By simulating the nonlinear characteristics and selection characteristics of the human visual perception system in image fusion, the fused image is more in line with the human visual perception mechanism. Finally, we validate our fusion framework on public datasets of infrared and visible images, medical images and multi-focus images. The experimental results demonstrate the superiority of our fusion framework over state-of-arts in visual quality, objective fusion metrics and robustness. Copyright © 2019, The Authors. All rights reserved.

关键词： Image fusion

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A cross-modal image fusion theory guided by human visual characteristics

arXiv

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arXiv 2019年

The characteristics of feature selection, nonlinear combination and multi-task auxiliary learning mechanism of the human visual perception system play an important role in real-world scenarios, but the research of image fusion theory based on the characteristics of human visual perception is less. Inspired by the characteristics of human visual perception, we propose a robust multi-task auxiliary learning optimization image fusion theory. Firstly, we combine channel attention model with nonlinear convolutional neural network to select features and fuse nonlinear features. Then, we analyze the impact of the existing image fusion loss on the image fusion quality, and establish the multi-loss function model of unsupervised learning network. Secondly, aiming at the multi-task auxiliary learning mechanism of human visual perception system, we study the influence of multi-task auxiliary learning mechanism on image fusion task on the basis of single task multi-loss network model. By simulating the three characteristics of human visual perception system, the fused image is more consistent with the mechanism of human brain image fusion. Finally, in order to verify the superiority of our algorithm, we carried out experiments on the combined vision system image data set, and extended our algorithm to the infrared and visible image and the multi-focus image public data set for experimental verification. The experimental results demonstrate the superiority of our fusion theory over state-of-arts in generality and robustness. Copyright © 2019, The Authors. All rights reserved.

关键词： Feature extraction

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