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SeaFree-GS: Reconstructing Underwater 3D Scenes With True Appearances

IEEE Signal Processing Letters 2025年 32卷 2114-2118页

作者： Liu, Shaohua Gao, Ning Fu, Shaowen Zhong, Xiaoqing Li, Hongjue Beihang University School of Astronautics Shenyuan Honors College Beijing100191 China Beihang University School of Astronautics Beijing100191 China Beijing Aerospace Automatic Control Institute Beijing100854 China National Key Laboratory of Science and Technology on Aerospace Intelligent Control Beijing100854 China China Academy of Space Technology Beijing100094 China Beijing Key Laboratory of System Design for Reusable Launch Vehicle State Key Laboratory of High- Efficiency Reusable Aerospace Transportation Technology China

Reconstructing underwater 3D scenes with accurate appearances is crucial for numerous tasks. However, existing underwater 3D reconstruction methods often fail to restore the true scene appearance due to degradation in underwater images caused by water effects. In this letter, we propose SeaFree-GS, a novel approach leveraging 3D Gaussian Splatting (3DGS) to reconstruct underwater scenes with their true appearances. Specifically, we introduce a Degradation-Aware Dual-Color Modeling strategy, where each Gaussian is assigned an intrinsic color representing the true scene appearance and a viewpoint-dependent degraded color to incorporate water effects. For a given viewpoint, this strategy physically derives the corresponding degraded colors from the intrinsic colors to render the underwater image. To improve reconstruction accuracy, we introduce a Content-Based Loss for selective enhancement of supervision over foreground and background regions, and a Coarse-Grained Depth Loss to enforce additional geometric constraints. Experiments on three datasets demonstrate that SeaFree-GS achieves state-of-the-art performance in Underwater True Appearance Reconstruction, and also performs competitively in Underwater Novel View Synthesis. © 1994-2012 IEEE.

关键词： 3D reconstruction

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The Improvement and Validation of Laser Induced Fluorescence technology on Temperature and Concentration Measurement

SSRN

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SSRN 2024年

作者： Zhang, Qi Wang, Haoyu Li, Junlong Zhou, Yi Liu, Zhenhai Qi, Feipeng Li, Dongyang Tan, Sichao Science and Technology on Reactor System Design Technology Laboratory Nuclear Power Institute of China Chengdu610213 China Fundamental Science on Nuclear Safety and Simulation Technology Laboratory Harbin Engineering University Harbin150001 China

Laser induced fluorescence (LIF) is characterized as a non-insertion and whole-field measuring technology for the thermal-hydraulic analysis. This paper presents the details of LIF, including the basic principle, the main apparatus and the data process methods. The effects of the inhomogeneous laser sheet and ambient light are eliminated by the discretization of the camera pixels. A new data process method base on the empirical fitted polynomial is developed. The additional calibration test and the empirical fitted polynomial are combined for the simplification and optimization of the data process method. The results shows that the deviation in temperature measurement is within 0.5 ℃ for the improved method, and is within 1.0 ℃ for the conventional method. The concentration measurement error is within 5.67% for the improved method, and is about 7.10% for the conventional method. The new method proposed by this work makes LIF technology more convenient and accurate. © 2024, The Authors. All rights reserved.

关键词： Fluorescence

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NASIL: Neural Network Architecture Searching for Incremental Learning in Image Classification 1

引用

11th International Symposium on Parallel Architectures, Algorithms and Programming, PAAP 2020

作者： Fu, Xianya Li, Wenrui Chen, Qiurui Zhang, Lianyi Yang, Kai Qing, Duzheng Wang, Rui Beihang University Beijing China Science and Technology on Special System Simulation Laboratory Beijing Simulation Center Beijing100854 China

ISBN: (数字)9789811600104

ISBN: (纸本)9789811600098

"Catastrophic forgetting" and scalability of tasks are two major challenges of incremental learning. Both of these issues were related to the insufficient capacity of machine learning model and the insufficiently trained weights as the increasing of tasks. In this paper, we try to figure out the impact of the neural network architecture to the performance of incremental learning in the case of image classification. During the increasing of tasks, we propose to use neural network architecture searching (NAS) to find a structure that fits the new tasks collection better. We build a NAS environment with reinforcement learning as the searching strategy and Long Short-Term Memory network as the controller network. Computation operation and connecting previous nodes are selected for each layer in the search phase. For each time a new group of tasks is added, the neural network architecture is searched and reorganized according to the training data set. To speed up the searching, we design a parameter sharing mechanism, in which the same building blocks in each layer share a group of parameters. We also introduce the quantified-parameter building blocks into the NAS, to identify the best candidate during each round of searching. We test our solution in cifar100 data set, the average accuracy outperforms the current representative solutions (LwEMC, iCaRL, GANIL) by 24.92%, 5.62%, and 3.6%, respectively, the more tasks added, the better our solution performs. © 2021, Springer Nature Singapore Pte Ltd.

关键词： Network architecture

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Architecture transformation research on joint border defense systems-of-systems 2021

Architecture transformation research on joint border defense...

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2021 5th International Conference on Management Engineering, Software Engineering and Service sciences, ICMSS 2021

作者： Zhang, Mengmeng Yi, Shuanghui Lin, Menglong Chen, Honghui Science and Technology on Information Systems Engineering Laboratory China National Key Laboratory for Complex System Simulation China

ISBN: (纸本)9781450389709

Currently, with the deepening of development and open of China's border, issues of border joint defense become increasingly arduous. Traditional means of cooperation and coordination are far from being able to align requirements;information systems of different joint defense units are difficult to interconnect and interoperate;the previous results of joint defense informatization are difficult to inherit. The main reason is the lack of border joint defense information construction with a top-level design approach. Via the lens of top-level design, this paper establishes a multi-viewpoint architecture framework and transformation process, develops the as-is and to-be joint defense architecture, and finally analyzes transformation principles from the as-is architecture to to-be architecture. This paper mainly explores the architecture transformation mechanisms under the border joint defense scenario. © 2021 ACM.

关键词： Architecture

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Multi-step Temporal Modeling for UAV Tracking

arXiv

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arXiv 2024年

作者： Yuan, Xiaoying Xu, Tingfa Liu, Xincong Wang, Ying Qin, Haolin Fang, Yuqiang Li, Jianan Beijing Institute of Technology Beijing100081 China The Science and Technology on Complex Electronic System Simulation Laboratory Space Engineering University Beijing101416 China The Key Laboratory of Photoelectronic Imaging Technology and System Ministry of Education of China Beijing100081 China Chongqing Innovation Center Beijing Institute of Technology Chongqing401135 China

In the realm of unmanned aerial vehicle (UAV) tracking, Siamese-based approaches have gained traction due to their optimal balance between efficiency and precision. However, UAV scenarios often present challenges such as insufficient sampling resolution, fast motion and small objects with limited feature information. As a result, temporal context in UAV tracking tasks plays a pivotal role in target location, overshadowing the target’s precise features. In this paper, we introduce MT-Track, a streamlined and efficient multi-step temporal modeling framework designed to harness the temporal context from historical frames for enhanced UAV tracking. This temporal integration occurs in two steps: correlation map generation and correlation map refinement. Specifically, we unveil a unique temporal correlation module that dynamically assesses the interplay between the template and search region features. This module leverages temporal information to refresh the template feature, yielding a more precise correlation map. Subsequently, we propose a mutual transformer module to refine the correlation maps of historical and current frames by modeling the temporal knowledge in the tracking sequence. This method significantly trims computational demands compared to the raw transformer. The compact yet potent nature of our tracking framework ensures commendable tracking outcomes, particularly in extended tracking scenarios. Comprehensive tests across four renowned UAV benchmarks substantiate the superior efficacy of our approach, delivering real-time performance at 84.7 FPS on a single GPU. Real-world test on the NVIDIA AGX hardware platform achieves a speed exceeding 30 FPS, validating the practicality of our method. Copyright © 2024, The Authors. All rights reserved.

关键词： Unmanned aerial vehicles (UAV)

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Method for constructing multi-dimensional feature map of malicious code 5

Method for constructing multi-dimensional feature map of mal...

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2020 5th International Seminar on Computer technology, Mechanical and Electrical Engineering, ISCME 2020

作者： Ma, Haocong Zhang, Ji Zhou, Junhua Zhai, Xiang Xue, Junjie Ji, Hang State Key Laboratory of Intelligent Manufacturing System Technology Beijing Institute of Electronic System Engineering Beijing100854 China School of Computer Science and Technology Beijing Institute of Technology Beijing100081 China Beijing Complex Product Advanced Manufacturing Engineering Research Center Beijing Simulation Center Beijing100854 China Science and Technology on Space System Simulation Laboratory Beijing Simulation Center Beijing100854 China

Malicious code is characterized by a large number of types, rapid increase in number, continuous update of transmission routes, and continuous enhancement of back analysis and back detection methods. Therefore, how to effectively detect and analyze malicious code has been a problem of great concern. This paper studies the features of binary file and disassembly file of malicious code, introduces the concept of information gain, and proposes a method to construct the multi-dimensional characteristic graph of malicious code. Finally, the convolutional neural network is used to classify the multi-dimensional feature graph of malicious code, which provides a new idea for the feature extraction of malicious code. © Published under licence by IOP Publishing Ltd.

关键词： Malware

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Architecture analysis for avionics prognostics and health management system

Architecture analysis for avionics prognostics and health ma...

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2021 CAA Symposium on Fault Detection, Supervision, and Safety for Technical Processes, SAFEPROCESS 2021

作者： Chen, Runfeng Hu, Yang Hou, Yanze Beijing China Science and Technology on Complex Aviation System Simulation Laboratory 9236 Beijing China

ISBN: (纸本)9781665401159

Prognostics and Health Management (PHM) has been researched on for recent years, and extensive studies have been done on hot topics into this field, such as diagnostics, prognostics, and decision making. However, how to evaluate PHM system architecture is still lacking. This is particularly important when designing avionics system equipped with PHM functions. We propose a general, time-variant architecture model that can simulate PHM system. Performance metrics are calculated to quantitatively evaluate the system architecture. This is useful to find differences of architectures in the earlier design stage in engineering. A case study is presented of the use of architecture modelling to show the effectiveness. And future works are discussed. © 2021 IEEE.

关键词： Decision making

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Multi-objective Optimal Allocation Strategy for Distributed Energy Storage in Distribution Networks Adapted to High Penetration Distributed Photovoltaics 9

Multi-objective Optimal Allocation Strategy for Distributed ...

引用

9th Asia Conference on Power and Electrical Engineering, ACPEE 2024

作者： Li, Cuiping Wang, Yanli Chen, Yiming Qi, Xuesong Liu, Yunjing Fang, Qian Cui, Shengyuan Wang, Yuming Northeast Electric Power University Key Laboratory of Modern Power System Simulation and Control & Renewable Energy Technology Jilin China State Grid Shanghai South Power Supply Company Science and Technology Section Shanghai China Jilin Power Supply Company Power Dispatching and Control Center Jilin China Jilin Power Supply Company Science and Technology Section Jilin China Jilin Power Supply Company Ministry of Science and Technology Jilin China

ISBN: (纸本)9798350309638

High percentage of photovoltaic gain connect to the wire line, so that the electricity grid from power distribution of the receiving end of the network into a set of production, storage, distribution of multi-source complex new network, the distribution network security operation and new energy consumption pressure increases. In response to the above, this paper puts forward the distributed ES multi-objective optimization configuration strategy of distribution network adapted to the high penetration rate distributed PV. And through a county power grid practical example to certify that the ES configuration approach proposed can effectively mitigate the impact of a high proportion of PV accessed, and it can reduce the abandonment of light. © 2024 IEEE.

关键词： Electric power distribution

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A FEATURE EXTRACTION ENHANCING-BASED LSTM INTEGRATED DEEP LEARNING MODEL FOR REMAINING USEFUL LIFE PREDICTION 14

A FEATURE EXTRACTION ENHANCING-BASED LSTM INTEGRATED DEEP LE...

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14th International Conference on Quality, Reliability, Risk, Maintenance, and Safety Engineering, QR2MSE 2024

作者： Wang, Hanyue Wang, Zhihua Wu, Qiong Mao, Zelong Cao, Shihao Li, Lu National Key Laboratory of Strength and Structural Integrity School of Aeronautic Science and Engineering Beihang University Beijing China Institute of Spacecraft System Engineering China Academy of Space Technology Beijing China Navigation Instrument Research Institute Tianjin China

ISBN: (纸本)9781837242672

The prediction of Remaining Useful Life (RUL) for complex engineering systems is crucial for maintaining their safety and reliability. To address the issue of limited RUL prediction accuracy due to inadequate extraction of degradation features in these systems, this paper presents an innovative RUL prediction method that integrates residual dilated causal convolution and Long Short-Term Memory (LSTM) networks. This approach employs residual connections to stack multiple dilated causal convolutions, facilitating the deep extraction of degradation features and enhancing the feature learning process. Additionally, it incorporates LSTM structures to forge a linkage between the degradation features and RUL, thereby enabling accurate RUL prediction for complex engineering systems. To validate the efficacy of the proffered method, experimental validation was conducted using the NASA public dataset C-MAPSS, and a comparative analysis was performed against the results of existing mainstream methods. The experimental results demonstrate that the suggested approach significantly enhances the precision of RUL estimation for complex engineering systems. © The Institution of Engineering & technology 2024.

关键词： DCC DEEP LEARNING LSTM RESIDUAL NETWORK RUL

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Multiparameter sensitivity analysis of tilt-to-length coupling noise in Taiji test mass interferometer

引用

Journal of Astronomical Telescopes, Instruments, and systems 2025年第1期11卷

作者： Xie, Fei Peng, Xiaodong Tang, Wenlin Zhao, Mengyuan Ma, Xiaoshan UCAS Hangzhou Institute for Advanced Study School of Fundamental Physics and Mathematical Sciences Hangzhou China Chinese Academy of Sciences National Space Science Center Key Laboratory of Electronics and Information Technology for Space System Beijing China University of Chinese Academy of Sciences Beijing China Taiji Laboratory for Gravitational Wave Universe Hangzhou China Key Laboratory of Gravitational Wave Precision Measurement of Zhejiang Province Hangzhou China Xi'an University of Finance and Economics School of Information Xi'an China Chinese Academy of Sciences Institute of Engineering Thermophysics National Key Laboratory of Science and Technology on Advanced Light-duty Gas-turbine Beijing China

Tilt-to-length (TTL) coupling noise is a significant noise source for test mass interferometers in Laser Interferometer space Antenna or Taiji, but identifying key parameters is a challenge due to the large number of influencing factors and complex interrelationships. simulation models based on the heterodyne interference process and the signal readout of the test mass interferometer were constructed to generate a dataset containing different parameters and corresponding to the longitudinal path length noise caused by TTL coupling. The eXtreme Gradient Boosting (XGBoost) model was employed to fit the nonlinear relationships between the parameters and TTL coupling noise. Based on the fitting results of the XGBoost model, the sensitivity of single factor and multiple factors was performed using SHapley Additive exPlanation (SHAP) values and attribution value matrix, and the results were validated by the analytical models. Without reducing the fitting accuracy, the parameter dimension was decreased from ∼60 to 11 according to sensitivities, retaining those most relevant to angular misalignment. The results showed that the angle of the test mass, the angle of the beam splitters and mirrors, and the lateral offset of the test mass had a significant impact on TTL coupling noise. The introduction of machine learning methods into the study of TTL coupling contributes to a deeper understanding of noise mechanisms and provides references for optimizing the instrument design of the Taiji program. © 2025 SPIE. All rights reserved.

关键词： Laser interferometry

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