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Automated object recognition in high-resolution optical remote sensing imagery

National science Review 2023年第6期10卷 38-41页

作者： Yazhou Yao Tao Chen Hanbo Bi Xinhao Cai Gensheng Pei Guoye Yang Zhiyuan Yan Xian Sun Xing Xu Hai Zhang School of Computer Science and Engineering Nanjing University of Science and Technology Aerospace Information Research Institute Chinese Academy of Sciences School of Electronic Electrical and Communication Engineering University of Chinese Academy of Sciences Key Laboratory of Network Information System Technology (NIST) Aerospace Information Research Institute Chinese Academy of Sciences Department of Computer Science and Technology Tsinghua University School of Computer Science and Engineering University of Electronic Science and Technology of China Pazhou Laboratory (Huangpu) School of Mathematics Northwest University

INTRODUCTION With the rapid development of remote sensing technology,high-quality remote sensing images have become widely *** automated object detection and recognition of these images,which aims to automatically locate objects of interest in remote sensing images and distinguish their specific categories,is an important fundamental task in the *** provides an effective means for geospatial object monitoring in many social applications,such as intelligent transportation,urban planning,environmental monitoring and homeland security.

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Jointly Estimation of Microstructure Maps Across Acquisition Protocols

Jointly Estimation of Microstructure Maps Across Acquisition...

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2024 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2024

作者： Wang, Tenglong Yu, Jiahao Pan, Yiang He, Jianzhong He, Yifei Wu, Ye Nanjing University of Science and Technology School of Computer Science and Engineering Nanjing China Zhejiang University of Technology College of Information Engineering Hangzhou China

ISBN: (纸本)9798350386226

Diffusion MRI (dMRI) allows for examining microarchitecture profiles and tissue changes using specific microstructure modeling but depends on advanced acquisition protocol and well-established biological model assumptions. It is also limited in clinical applications due to lengthy acquisition time and dense q-space sampling requirements. In this study, we present a method that aims to estimate multiple functional microstructural parameters robustly, thereby enhancing clinical applications with different acquisition protocols. Instead of learning the mapping between dMRI and microstructure maps directly, our approach learns a set of explainable over-completed tissue-compartment kernels between parameterized spherical mean signal and widely-used microstructure maps and apply into the joint characterization of multiple biological models. We validate the effectiveness of our method using an in vivo dataset across different health conditions collected by a clinical scanner. This work sets the foundation for future techniques that integrate clinical data acquisition protocols and enhance sensitivity to microstructure measures. The code is provided at https://***/1nlandempire/JEMAP. © 2024 IEEE.

关键词： Tissue

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Unknown Category Malicious Traffic Detection Based on Contrastive Learning 6th

Unknown Category Malicious Traffic Detection Based on Contra...

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6th International Conference on Machine Learning for Cyber Security, ML4CS 2024

作者： Yan, Leiming Zhou, Tao Chen, Xianyi Engineering Research Center of Digital Forensics Ministry of Education Nanjing University of Information Science and Technology Nanjing210044 China School of Computer Science and Cyber Science and Engineering Nanjing University of Information Science and Technology Nanjing210044 China

ISBN: (纸本)9789819645657

In response to the continuous emergence of novel unknown malicious traffic and the limitations of traditional detection methods, this paper presents an unknown-category malicious traffic detection approach based on contrastive learning. The proposed method utilizes contrastive learning to train an encoder for distinguishing normal traffic and multiple types of known malicious traffic, thereby enhancing inter-class separability. Subsequently, the model is fine-tuned to optimize the representations of malicious traffic categories with limited samples, amplifying the separation between different classes in the feature space. This ensures that the distance between unknown malicious traffic and other categories exceeds a predefined threshold, thereby achieving effective detection. Experimental results on the CICIoT2023 and UNSW-NB15 datasets demonstrate the superior performance of the proposed method, achieving multi-class F1-scores of 93.23 and 89.93, respectively, outperforming traditional approaches. Additionally, the method achieves an accuracy of over 83% in simulated scenarios involving unknown-category malicious traffic detection. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Contrastive Learning

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Advanced synaptic devices and their applications in biomimetic sensory neural system

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Chip 2023年第1期2卷 1-22页

作者： Yiqi Sun Jiean Li Sheng Li Yongchang Jiang Enze Wan Jiahan Zhang Yi Shi Lijia Pan School of Electronic Science and Engineering Nanjing University210093NanjingChina School of Microelectronics and Control Engineering Changzhou University213164ChangzhouChina School of Computer Sci-ence and Engineering Macao University of Science and Technology

Human nervous system,which is composed of neuron and synapse networks,is capable of processing information in a plastic,dataparallel,fault-tolerant,and energy-efficient *** by the ingenious working mechanism of this miraculous biological data processing system,scientists have been devoting great efforts to ar-tificial neural systems based on synaptic devices in recent *** continuous development of bioinspired sensors and synaptic devices in recent years have made it possible that artificial sensory neural systems are capable of capturing and processing stimuli informa-tion in real *** progress of biomimetic sensory neural systems could provide new methods for next-generation humanoid robotics,human-machine interfaces,and other frontier ***,this review summarized the recent progress of synaptic devices and biomimetic sensory neural ***,the opportunities and remaining challenges in the further development of biomimetic sensory neural systems were also outlined.

关键词： Artificial synapse Biomimetic sensory neural system Memristor Synaptic transistor

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Knowledge Graph Driven Inference Testing for Question Answering Software 24

Knowledge Graph Driven Inference Testing for Question Answer...

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44th ACM/IEEE International Conference on Software engineering, ICSE 2024

作者： Wang, Jun Li, Yanhui Chen, Zhifei Chen, Lin Zhang, Xiaofang Zhou, Yuming Nanjing University State Key Laboratory for Novel Software Technology China School of Computer Science and Engineering Nanjing University of Science and Technology China School of Computer Science and Technology Soochow University China

ISBN: (纸本)9798400702174

In the wake of developments in the field of Natural Language Processing, Question Answering (QA) software has penetrated our daily lives. Due to the data-driven programming paradigm, QA software inevitably contains bugs, i.e., misbehaving in real-world applications. Current testing techniques for testing QA software include two folds, reference-based testing and metamorphic testing. This paper adopts a different angle to achieve testing for QA software: we notice that answers to questions would have inference relations, i.e., the answers to some questions could be logically inferred from the answers to other questions. If these answers on QA software do not satisfy the inference relations, an inference bug is detected. To generate the questions with the inference relations automatically, we propose a novel testing method Knowledge Graph driven Inference Testing (KGIT), which employs facts in the Knowledge Graph (KG) as the seeds to logically construct test cases containing questions and contexts with inference relations. To evaluate the effectiveness of KGIT, we conduct an extensive empirical study with more than 2.8 million test cases generated from the large-scale KG YAGO4 and three QA models based on the state-of-the-art QA model structure. The experimental results show that our method (a) could detect a considerable number of inference bugs in all three studied QA models and (b) is helpful in retraining QA models to improve their inference ability. © 2024 ACM.

关键词： Knowledge graph

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SeBROP:blind ROP attacks without returns

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Frontiers of computer science 2022年第4期16卷 185-202页

作者： Tianning Zhang Miao Cai Diming Zhang Hao Huang Department of Computer Science and Technology Nanjing UniversityNanjing210023China School of Computer and Information Hohai UniversityNanjing211106China College of Computer Engineering Jiangsu University of Science and TechnologyZhenjiang212008China

Currently,security-critical server programs are well protected by various defense techniques,such as Address Space Layout Randomization(ASLR),eXecute Only Memory(XOM),and Data Execution Prevention(DEP),against modern code-reuse attacks like Return-oriented Programming(ROP)***,in these victim programs,most syscall instructions lack the following ret instructions,which prevents attacks to stitch multiple system calls to implement advanced behaviors like launching a remote *** this kind of gadget greatly constrains the capability of code-reuse *** paper proposes a novel code-reuse attack method called Signal Enhanced Blind Return Oriented Programming(SeBROP)to address these *** SeBROP can initiate a successful exploit to server-side programs using only a stack overflow *** leveraging a side-channel that exists in the victim program,we show how to find a variety of gadgets blindly without any pre-knowledges or reading/disassembling the code ***,we propose a technique that exploits the current vulnerable signal checking mechanism to realize the execution flow control even when ret instructions are *** technique can stitch a number of system calls without returns,which is more superior to conventional ROP ***,the SeBROP attack precisely identifies many useful gadgets to constitute a Turing-complete *** attack can defeat almost all state-of-the-art defense *** SeBROP attack is compatible with both modern 64-bit and 32-bit *** validate its effectiveness,We craft three exploits of the SeBROP attack for three real-world applications,i.e.,32-bit Apache 1.3.49,32-bit ProFTPD 1.3.0,and 64-bit Nginx *** results demonstrate that the SeBROP attack can successfully spawn a remote shell on Nginx,ProFTPD,and Apache with less than 8500/4300/2100 requests,respectively.

关键词： code-reuse atack ROP signal

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Spark workflow task scheduling with deadline and privacy constraints in hybrid cloud networks

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Soft Computing 2025年第2期29卷 783-801页

作者： Rajput, Kamran Yaseen Xiaoping, Li Lakhan, Abdullah School of Computer Science and Engineering Southeast University Nanjing China School of Economics Innovations and Technology Kristiania University College Oslo Norway Department of Cybersecurity Dawood University of Engineering and Technology Karachi Pakistan

The increasing adoption of hybrid clouds in organizations stems from their ability to bolster private cloud resources with additional public cloud capacity when required. However, scheduling distributed applications, such as workflow tasks, on hybrid cloud resources presents new and intricate challenges. A significant concern revolves around the potential exposure of private data and tasks within third-party, public cloud infrastructures, especially within sensitive domains like healthcare applications. The complexity escalates when considering the selection of resources from multiple cloud providers due to the fluctuating resource computation prices and data transmission costs. This paper presents the Spark Workflow Task Scheduling to Hybrid Cloud (SWSHC) framework, designed to schedule Spark workflows precisely while adhering to deadline and task privacy constraints within a hybrid cloud setting. Our innovative approach encompasses developing and implementing three pivotal components: deadline division, stage order optimization, and task scheduling mechanisms. We segregate the workflow deadline for each stage to bridge the gaps between stages effectively. Additionally, job prioritization is achieved using the maximum rank rule. The proposed solution considers diverse factors, including interval pricing variations, utilization of heterogeneous VM instances, intra- and inter-bandwidth considerations, and the efficient utilization of private cloud resources. Through meticulous calibration of our algorithm and comprehensive experimentation with various realistic workflows, our findings unequivocally demonstrate that SWSHC surpasses existing solutions in the current literature the cost by up to 40–70% in terms of cost efficiency and resource utilization. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2025.

关键词： Differential privacy

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Interpretation Mode of Spaceborne SAR Based on Analysis of Cognitive Needs 11th

Interpretation Mode of Spaceborne SAR Based on Analysis of C...

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11th China Conference on Command and Control, C2 2023

作者： Lanyu, Li Shouwei, Yang Nanjing Research Institute of Electronic Technology Nanjing210049 China School of Computer Science and Engineering Nanjing University of Science and Technology Nanjing210004 China

ISBN: (纸本)9789819990207

The intelligent interpretation of spaceborne SAR images is an important technical field for future remote sensing applications. However, due to the imaging defects of SAR itself, it is very difficult to divide the image interpretation samples. Command and control, as an important application field of image interpretation, has many cognitive scenarios. Based on the analysis of image usage requirements, this article calculates the information value of corresponding target samples under different application purposes through text analysis of relevant SAR image scientific literature, technical reports, etc., and uses this as the selection threshold for image interpretation to improve the efficiency of image interpretation. At the same time, this paper also designed a SAR image interpretation mode based on graph neural network, replacing the attention mechanism module with knowledge calibration, and providing technical support for the in-depth application of satellite-borne SAR. © Chinese Institute of Command and Control 2024.

关键词： Synthetic aperture radar

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Iterative Segmentation and Propagation Based Interactive Video Object Segmentation

Iterative Segmentation and Propagation Based Interactive Vid...

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2023 International Conference on Algorithm, Imaging Processing, and Machine Vision, AIPMV 2023

作者： Luo, Sihan Yang, Sizhe Yuan, Xia School of Computer Science and Engineering Nanjing University of Science and Technology Jiangsu Nanjing China School of Information and Software Engineering University of Electronic Science and Technology of China Sichuan Chengdu China

ISBN: (纸本)9781510672444

Interactive video object segmentation (iVOS), which aims to efficiently produce high-quality segmentation masks of the target object in a video with user interactions. Recently, numerous works are proposed to advance the task of iVOS. However, their usages on user intent are limited. First, typical modules usually try to direct generate the segmentation without any further exploration on the input interaction, which misses valuable information. Second, recent iVOS approaches also do not consider the raw interactive information. As a result, the final segmentation results will be poisoned by the erroneous information given by the previous round’s segmentation masks. To solve the aforementioned weaknesses, in this paper, an Iterative Segmentation and Propagation based iVOS method is proposed to conduct better user intent exploration, namely ISP. ISP directly models user intent into the PGI2M module and TP module. Specifically, ISP first extracts a coarse-grained segmentation mask by analyzing the user’s input. Subsequently, this mask is used as a prior to aid the PGI2M module. Secondly, ISP presents a new interaction-driven self-attention module to recall the user’s intent in the TP module. Extensive experiments on two public datasets show the superiority of ISP over existing methods. © 2024 SPIE.

关键词： Iterative methods

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Learning cross-modal interaction for RGB-T tracking

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science China(Information sciences) 2023年第1期66卷 320-321页

作者： Chunyan XU Zhen CUI Chaoqun WANG Chuanwei ZHOU Jian YANG Key Laboratory of Intelligent Perception and Systems for High-Dimensional Information of Ministry of Education School of Computer Science and Engineering Nanjing University of Science and Technology

Dear editor,Visual object tracking, which has attracted increasing attention in the field of general visual understanding, aims to track each temporally changing object in a video sequence, with the target specified only in the first *** most tracking algorithms have facilitated significant advances in RGB video sequences, object tracking using only RGB information is unreliable under extreme lighting conditions(e.g., dark night, rain, and foggy).

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