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arXiv 2025年

作者： Chen, Chen Wang, Zhirui Sheng, Taowei Jiang, Yi Li, Yundu Cheng, Peirui Zhang, Luning Chen, Kaiqiang Hu, Yanfeng Yang, Xue Sun, Xian Key Laboratory of Target Cognition and Application Technology Aerospace Information Research Institute Chinese Academy of Sciences China University of Chinese Academy of Sciences China Shanghai Jiao Tong University China

Existing vision-based 3D occupancy prediction methods are inherently limited in accuracy due to their exclusive reliance on street-view imagery, neglecting the potential benefits of incorporating satellite views. We propose SA-Occ, the first Satellite-Assisted 3D occupancy prediction model, which leverages GPS & IMU to integrate historical yet readily available satellite imagery into real-time applications, effectively mitigating limitations of ego-vehicle perceptions, involving occlusions and degraded performance in distant regions. To address the core challenges of cross-view perception, we propose: 1) Dynamic-Decoupling Fusion, which resolves inconsistencies in dynamic regions caused by the temporal asynchrony between satellite and street views;2) 3D-Proj Guidance, a module that enhances 3D feature extraction from inherently 2D satellite imagery;and 3) Uniform Sampling Alignment, which aligns the sampling density between street and satellite views. Evaluated on Occ3D-nuScenes, SA-Occ achieves state-of-the-art performance, especially among single-frame methods, with a 39.05% mIoU (a 6.97% improvement), while incurring only 6.93 ms of additional latency per frame. Our code and newly curated dataset are available at https://***/chenchen235/SA-Occ. Copyright © 2025, The Authors. All rights reserved.

关键词： Satellite imagery

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IsoVISoR: Towards 3D Mesoscale Brain Mapping of Large Mammals at Isotropic Sub-micron Resolution

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Neuroscience Bulletin 2025年第2期41卷 344-348页

作者： Chao-Yu Yang Yan Shen Xiaoyang Qi Lufeng Ding Yanyang Xiao Qingyuan Zhu Hao Wang Cheng Xu Pak-Ming Lau Pengcheng Zhou Fang Xu Guo-Qiang Bi Division of Life Sciences and Medicine CAS Key Laboratory of Brain Function and DiseaseUniversity of Science and Technology of ChinaHefei230026China Interdisciplinary Center for Brain Information Shenzhen-Hong Kong Institute of Brain ScienceShenzhen Institute of Advanced TechnologyChinese Academy of SciencesShenzhen518055China Center for Integrative Imaging Hefei National Research Center for Physical Sciences at the MicroscaleUniversity of Science and Technology of ChinaHefei230027China National Engineering Laboratory for Brain-Inspired Intelligence Technology and Application MoE Key Laboratory of Brain-Inspired Intelligent Perception and CognitionSchool of Information Science and TechnologyUniversity of Science and Technology of ChinaHefei230026China Anhui Province Key Laboratory of Biomedical Imaging and Intelligent Processing Institute of Artificial IntelligenceHefei Comprehensive National Science CenterHefei230088China Faculty of Life and Health Sciences Shenzhen University of Advanced TechnologyShenzhen518107China CAS Key Laboratory of Brain Connectome and Manipulation The Brain Cognition and Brain Disease InstituteShenzhen Institute of Advanced TechnologyChinese Academy of SciencesShenzhen518055China

Dear Editor,The mammalian brain exhibits cross-scale complexity in neuronal morphology and connectivity,the study of which demands high-resolution morphological reconstruction of individual neurons across the entire brain[1-4].Current commonly used approaches for such mesoscale brain mapping include two main types of three-dimensional fluorescence microscopy:the block-face methods,and the lightsheet-based methods[5,6].In general,the high imaging speed and light efficiency of light-sheet microscopy make it a suitable tool for high-throughput volumetric imaging,especially when combined with tissue-clearing ***,large brain samples pose major challenges to this approach.

关键词： brain mapping three dimensional fluorescence microscopy mesoscale brain mapping lightsheet based methods block face methods high throughput volumetric imaging tissue clearing techniques

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A SAR Deceptive Jamming Suppression Method Based on PRI Variation Design and Multi-Channel Principle

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IEEE Transactions on Geoscience and Remote Sensing 2025年

作者： Shi, Haixu Xu, Zhongqiu Li, Guangzuo Lin, Kuan Liu, Tianqu Hong, Wen Chinese Academy of Sciences Aerospace Information Research Institute Beijing100094 China Key Laboratory of Spatial Information Processing and Application System Technology Beijing100094 China Key Laboratory of Target Cognition and Application Technology Beijing100094 China University of Chinese Academy of Sciences School of Electronic Electrical and Communication Engineering Beijing101499 China

The synthetic aperture radar (SAR) can be affected by various types of jamming during operation. Among them, the deceptive jamming generated by digital radio frequency memory (DRFM) jammers poses a serious threat to SAR imaging by creating highly realistic false targets. Moreover, with advancements in deceptive jamming technology, the generation speed of deceptive jamming has increased, rendering existing methods less effective. To address this issue, an anti-deceptive jamming method based on pulse repetition interval (PRI) variation design and multi-channel principle is proposed to mitigate the effects of deceptive jamming. First, a PRI variation strategy that will not cause the loss of echo signals in the imaging area is designed. By utilizing this strategy for imaging, deceptive jamming signals are dispersed across different ranges, resulting in preliminary suppression of the jamming. Subsequently, after azimuth non-uniform sampling reconstruction and range processing, most of the jamming signals are suppressed due to the azimuth timing differences between SAR and jamming signals. However, when the jammer uses specific retransmission intervals, such as the average PRI of the PRI sequence, the jamming signals may be concentrated at certain ranges, retaining some coherence and posing a threat to SAR imaging. To overcome this challenge, a residual jamming detection and suppression algorithm based on multi-channel principle is proposed, which can detect and filter out the channels affected by jamming. Finally, an azimuth sparse reconstruction is introduced for azimuth processing. Since the anti-jamming principle of this method relies on the differences in azimuth timing between SAR and jamming, it can suppress deceptive jamming even when the generation speed of deceptive jamming is rapid, which some other anti-deceptive jamming methods cannot achieve. Simulations of SAR imaging under deceptive jamming conditions are conducted for point target scene and complex target

关键词： Synthetic aperture radar

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Renewable energy reduces domestic depression but increases depression for neighboring countries: evidence of spatial effects from 181 countries worldwide

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BMC public health 2025年第1期25卷 1676页

作者： Zheng Zhang Huijie Xu Cui Liping Yuanyuan Wang Key Laboratory of Brain Cognition and Education Sciences Ministry of Education China School of Psychology Center for Studies of Psychological Application and Guangdong Key Laboratory of Mental Health and Cognitive Science South China Normal University Guangzhou China. School of Education Huazhong University of Science and Technology Wuhan China. Human Resources Department Hebei Vocational University of Technology and Engineering Hebei China. School of Psychology Center for Studies of Psychological Application and Guangdong Key Laboratory of Mental Health and Cognitive Science South China Normal University Guangzhou China. angelayuanyuanwang@***.

BACKGROUND:Depression poses a significant global public health challenge, affecting millions of people worldwide. The utilization of renewable energy holds potential for improving mental health by reducing air pollution and promoting green spaces. PURPOSE:This study aims to investigate the impact of renewable energy use on depression, with a focus on its spatial effects and the mediating roles of air pollution reduction and green space expansion. METHODS:Data from 181 countries were analyzed using a two-way fixed effects model and the Spatial Durbin Model (SDM). Depression-related metrics, including Disability-Adjusted Life Years (DALYs), Age-Standardized Disability-Adjusted Life Years Rate (ASDR), prevalence, and Age-Standardized Prevalence Rate (ASPR), were evaluated. RESULTS:Renewable energy use significantly reduces DALYs, ASDR, prevalence, and ASPR within a country, but it also significantly increases the risk of depression in neighboring countries. The impact of renewable energy on depression varies by gender, age, and SDI level, being more pronounced for males and the 50-74 age group. The effect is significant in high and low SDI countries but not in middle SDI countries, indicating a "middle-income trap." CONCLUSION:Renewable energy can improve mental health by reducing air pollution and promoting green spaces. However, policymakers need to consider spatial effects and tailor policies accordingly to maximize health benefits.

关键词： ASDR ASPR DALYs Depression Environmental pollution Green space Renewable energy Spatial effects

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Efficient Reconstruction of Spatial Features for Remote Sensing Image-Text Retrieval

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Transactions of Nanjing University of Aeronautics and Astronautics 2025年第1期42卷 101-111页

作者： ZHANG Weihang CHEN Jialiang ZHANG Wenkai LI Xinming GAO Xin SUN Xian Aerospace Information Research Institute Chinese Academy of SciencesBeijing 100190P.R.China Key Laboratory of Target Cognition and Application Technology(TCAT) Chinese Academy of SciencesBeijing 100190P.R.China School of Electronic Electrical and Communication EngineeringUniversity of Chinese Academy of SciencesBeijing 100190P.R.China School of Computer Science and Artificial Intelligence Aerospace Information Technology UniversityJinan 250299P.R.China

Remote sensing cross-modal image-text retrieval(RSCIR)can flexibly and subjectively retrieve remote sensing images utilizing query text,which has received more researchers’attention ***,with the increasing volume of visual-language pre-training model parameters,direct transfer learning consumes a substantial amount of computational and storage ***,recently proposed parameter-efficient transfer learning methods mainly focus on the reconstruction of channel features,ignoring the spatial features which are vital for modeling key entity *** address these issues,we design an efficient transfer learning framework for RSCIR,which is based on spatial feature efficient reconstruction(SPER).A concise and efficient spatial adapter is introduced to enhance the extraction of spatial *** spatial adapter is able to spatially reconstruct the features in the backbone with few parameters while incorporating the prior information from the channel *** conduct quantitative and qualitative experiments on two different commonly used RSCIR *** with traditional methods,our approach achieves an improvement of 3%-11% in sumR *** with methods finetuning all parameters,our proposed method only trains less than 1% of the parameters,while maintaining an overall performance of about 96%.

关键词： remote sensing cross-modal image-text retrieval(RSCIR) spatial features channel features contrastive learning parameter effective transfer learning

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Multi-document reading comprehension model based on electra and document sliding window

Multi-document reading comprehension model based on electra ...

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2023 International Workshop on Signal Processing and Machine Learning, WSPML 2023

作者： Yang, Zheyu Zhang, Benkui Jiang, Nan Key Lab of Target Cognition and Application Technology Beijing China Aerospace Information Research Institute CAS Beijing China

ISBN: (纸本)9781510671928

Multi-document reading comprehension is an important and difficult task in natural language processing. To address the issue that ELECTRA pre-training model has length limitation and cannot be directly adapt to multi-document reading comprehension task, this paper proposes a novel model based on ELECTRA and document sliding windows. In the model multiple documents are split and merged through document sliding windows, new segmentation embedding is introduced, answer position in documents is modelled as a learning target, and ELECTRA is used for joint training in each window. After obtaining all prediction outcomes of each window, the results are comprehensively sorted to achieve the optimal answer. The experiments show that Rouge-L of this model reaches 51.28% on the multi-document reading comprehension dataset MS-MARCO, ranking the current best result. © 2023 SPIE. All rights reserved.

关键词： Natural language processing systems

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Hybrid bundle-adjusting 3D Gaussians for view consistent rendering with pose optimization 11

Hybrid bundle-adjusting 3D Gaussians for view consistent ren...

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Optoelectronic Imaging and Multimedia technology XI 2024

作者： Guo, Yanan Xie, Ying Chang, Ying Zhang, Benkui Jia, Bo Cao, Lin Key Laboratory of Information and Communication Systems Ministry of Information Industry Beijing Information Science and Technology University Beijing China Key Laboratory of Target Cognition and Application Technology Aerospace Information Research Institute Beijing China

ISBN: (纸本)9781510682061

Novel view synthesis has made significant progress in the field of 3D computer vision. However, the rendering of view-consistent novel views from imperfect camera poses remains challenging. In this paper, we introduce a hybrid bundle-adjusting 3D Gaussians model that enables view-consistent rendering with pose optimization. This model jointly extract image-based and neural 3D representations to simultaneously generate view-consistent images and camera poses within forward-facing scenes. The effective of our model is demonstrated through extensive experiments conducted on both real and synthetic datasets. These experiments clearly illustrate that our model can effectively optimize neural scene representations while simultaneously resolving significant camera pose misalignments. © 2024 SPIE.

关键词： Cameras

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Rotation Correction Based Neural Radiance Fields for Multi-view Satellite Images 11

Rotation Correction Based Neural Radiance Fields for Multi-v...

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Optoelectronic Imaging and Multimedia technology XI 2024

作者： Liu, Yangfan Guo, Yanan Bian, Huanyu Zhang, Benkui Du, Kangning Xie, Ying Cao, Lin Key Laboratory of Information and Communication Systems Ministry of Information Industry Beijing Information Science and Technology University Beijing China Key Laboratory of Target Cognition and Application Technology Aerospace Information Research Institute Beijing China

ISBN: (纸本)9781510682061

To address the issue of reconstruction distortions caused by using non-unified RPC models in 3D reconstruction with multi-view satellite imagery. In this paper, we propose a method termed Rotation Correction Based Neural Radiance Fields for Multi-view Satellite Images. Our method optimizes the satellite camera model and neural radiance field by integrating multi-axial rotational correction into the reconstruction task. By separately correcting the attitude angles along the X, Y, and Z axes, the geometric distortions in multi-view satellite images can be corrected. Furthermore, by setting the ray projection in the neural radiance field under the effect of variable correction rotation variables, our method allows simultaneous optimization of the correction rotation variables and the neural radiance field during back propagation. We conducted experiments using WorldView-3 images from different locations, comparing the reconstruction results of images corrected with traditional BA and our method. Our method achieved the best results. © 2024 SPIE.

关键词： Satellite imagery

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A highly selective fluorescent probe for real-time imaging of UDP-glucuronosyltransferase 1A8 in living cells and tissues

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Frontiers of Chemical Science and Engineering 2022年第1期16卷 103-111页

作者： Mingyue Zhu Zhenhao Tian Lingling Jin Xiaokui Huo Chao Wang Jingnan Cui Yan Tian Xiangge Tian Lei Feng College of Pharmacy School of MedicineKey Laboratory of Elemene Class Anti-Cancer Chinese MedicinesEngineering Laboratory of Development and Application of Traditional Chinese MedicinesHangzhou Normal UniversityHangzhou 311121China Dalian Key Laboratory of Metabolic Target Characterization and Traditional Chinese Medicine Intervention College of PharmacyCollege of Integrative MedicineDalian Medical UniversityDalian 116044China School of Life Sciences Northwestern Polytechnical UniversityXi’an 710072China State Key Laboratory of Fine Chemicals Dalian University of TechnologyDalian 116024China

Uridine diphosphate(UDP)-glucuronosyltransferases(UGTs)are enzymes involved in the biotransformation of important endogenous compounds such as steroids,bile acids,and hormones as well as exogenous substances including drugs,environmental toxicants,and ***,a novel fluorescent probe BDMP was developed based on boron-dipyrromethene(BODIPY)with high sensitivity for the detection of *** glucuronidation of BDMP not only exhibited a redemission wavelength(lex/lem=500/580 nm),but also displayed an excellent UGT1A8-dependent fluorescence signal with a good linear relationship with UGT1A8 *** on this perfect biocompatibility and cell permeability,BDMP was successfully used to image endogenous UGT1A8 in human cancer cell lines(LoVo and HCT15)in real *** addition,BDMP could also be used to visualize UGT1A8 in tumor *** results suggested that BDMP is a promising molecular tool for the investigation of UGT1A8-mediated physiological function in humans.

关键词： UDP-glucuronosyltransferase 1A8 fluorescent probe subtype selectivity fluorescence imaging

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Advancing Few-Shot Instance Segmentation of Military Aircraft in Remote Sensing Imagery with Large Vision Models

Advancing Few-Shot Instance Segmentation of Military Aircraf...

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IEEE International Symposium on Geoscience and Remote Sensing (IGARSS)

作者： Xiyu Qi Yifan Wu Wenhui Zhang Zhan Chen Yidan Zhang Lei Wang Aerospace Information Research Institute Chinese Academy of Sciences Key Laboratory of Target Cognition and Application Technology (TCAT) Key Laboratory of Network Information System Technology (NIST) Key Laboratory of Technology in Geo-Spatial Information Processing and Application System

ISBN: (数字)9798350360325

ISBN: (纸本)9798350360332

This study introduces a novel few-shot instance segmentation framework MAR FSIS for identifying and segmenting aircraft in high-resolution remote sensing imagery under stringent few-shot conditions. Utilizing large vision models in conjunction with a sophisticated detector and a novel object prompter, MAR FSIS demonstrates superior performance in discerning intricate details of aircraft with minimal training examples. The effectiveness of this approach is confirmed through experimental evaluations on the proposed MAR20IS dataset, achieving remarkable precision in both detection and segmentation tasks.

关键词： Instance segmentation Training Atmospheric modeling Detectors Military aircraft Data models Proposals

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