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SSA: semantic structure aware inference on CNN networks for weakly pixel-wise dense predictions without cost

Frontiers of computer science 2025年第2期19卷 1-10页

作者： Yanpeng SUN Zechao LI School of Computer Science and Engineering Nanjing University of Science and TechnologyNanjing 210014China

The pixel-wise dense prediction tasks based on weakly supervisions currently use Class Attention Maps(CAMs)to generate pseudo masks as ***,existing methods often incorporate trainable modules to expand the immature class activation maps,which can result in significant computational overhead and complicate the training *** this work,we investigate the semantic structure information concealed within the CNN network,and propose a semantic structure aware inference(SSA)method that utilizes this information to obtain high-quality CAM without any additional training ***,the semantic structure modeling module(SSM)is first proposed to generate the classagnostic semantic correlation representation,where each item denotes the affinity degree between one category of objects and all the ***,the immature CAM are refined through a dot product operation that utilizes semantic structure ***,the polished CAMs from different backbone stages are fused as the *** advantage of SSA lies in its parameter-free nature and the absence of additional training costs,which makes it suitable for various weakly supervised pixel-dense prediction *** conducted extensive experiments on weakly supervised object localization and weakly supervised semantic segmentation,and the results confirm the effectiveness of SSA.

关键词： class attention maps semantic structure weaklysupervised object localization weakly-supervised semantic segmentation

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A recover-then-discriminate framework for robust anomaly detection

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science China(Information sciences) 2025年第4期68卷 300-318页

作者： Peng XING Dong ZHANG Jinhui TANG Zechao LI School of Computer Science and Engineering Nanjing University of Science and Technology Department of Electronic and Computer Engineering The Hong Kong University of Science and Technology

Anomaly detection(AD) has been extensively studied and applied across various scenarios in recent years. However, gaps remain between the current performance and the desired recognition accuracy required for practical *** paper analyzes two fundamental failure cases in the baseline AD model and identifies key reasons that limit the recognition accuracy of existing approaches. Specifically, by Case-1, we found that the main reason detrimental to current AD methods is that the inputs to the recovery model contain a large number of detailed features to be recovered, which leads to the normal/abnormal area has not/has been recovered into its original state. By Case-2, we surprisingly found that the abnormal area that cannot be recognized in image-level representations can be easily recognized in the feature-level representation. Based on the above observations, we propose a novel recover-then-discriminate(ReDi) framework for *** takes a self-generated feature map(e.g., histogram of oriented gradients) and a selected prompted image as explicit input information to address the identified in Case-1. Additionally, a feature-level discriminative network is introduced to amplify abnormal differences between the recovered and input representations. Extensive experiments on two widely used yet challenging AD datasets demonstrate that ReDi achieves state-of-the-art recognition accuracy.

关键词： recovery network HOG prompt discriminative network self-correlation loss anomaly detection

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Enhanced Acceleration for Generalized Nonconvex Low-Rank Matrix Learning

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Chinese Journal of Electronics 2025年第1期34卷 98-113页

作者： Hengmin Zhang Jian Yang Wenli Du Bob Zhang Zhiyuan Zha Bihan Wen School of Electrical and Electronic Engineering Nanyang Technological University School of Computer Science and Engineering Nanjing University of Science and Technology School of Information Science and Engineering East China University of Science and Technology Department of Electrical and Computer Engineering University of Macau

Matrix minimization techniques that employ the nuclear norm have gained recognition for their applicability in tasks like image inpainting, clustering, classification, and reconstruction. However, they come with inherent biases and computational burdens, especially when used to relax the rank function, making them less effective and efficient in real-world scenarios. To address these challenges, our research focuses on generalized nonconvex rank regularization problems in robust matrix completion, low-rank representation, and robust matrix regression. We introduce innovative approaches for effective and efficient low-rank matrix learning, grounded in generalized nonconvex rank relaxations inspired by various substitutes for the ?0-norm relaxed functions. These relaxations allow us to more accurately capture low-rank structures. Our optimization strategy employs a nonconvex and multi-variable alternating direction method of multipliers, backed by rigorous theoretical analysis for complexity and *** algorithm iteratively updates blocks of variables, ensuring efficient convergence. Additionally, we incorporate the randomized singular value decomposition technique and/or other acceleration strategies to enhance the computational efficiency of our approach, particularly for large-scale constrained minimization problems. In conclusion, our experimental results across a variety of image vision-related application tasks unequivocally demonstrate the superiority of our proposed methodologies in terms of both efficacy and efficiency when compared to most other related learning methods.

关键词： Learning systems Image recognition Minimization Computational efficiency Complexity theory Matrix decomposition Optimization Image reconstruction Singular value decomposition Convergence

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Uncertainties of the standard quantum teleportation channel

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Chinese Physics B 2025年第4期34卷 273-285页

作者： Zhihua Zhang Zehao Guo Zhipeng Qiu School of Cyber Science and Engineering Nanjing University of Science and TechnologyJiangyin 214443China School of Mathematics and Statistics Nanjing University of Science and TechnologyNanjing 210094China

From the perspective of state-channel interaction,standard quantum teleportation can be viewed as a communication process characterized by both input and output,functioning as a quantum depolarizing *** achieve a precise quantification of the quantumness introduced by this channel,we examine its uncertainties,which encompass both statedependent and state-independent ***,for qudit systems,we provide general formulas for these *** analyze the uncertainties associated with standard quantum teleportation when induced by isotropic states,Werner states,and X-states,and we elucidate the correlation between these uncertainties and the parameters of the specific mixed *** findings demonstrate the validity of quantifying these uncertainties.

关键词： uncertainty standard quantum teleportation channel state-channel interaction

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A blockchain-based privacy-preserving and collusion-resistant scheme(PPCR)for double auctions

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Digital Communications and Networks 2025年第1期11卷 116-125页

作者： Xuedan Jia Liangmin Wang Ke Cheng Pujie Jing Xiangmei Song School of Computer Science and Communication Engineering Jiangsu UniversityZhenjiang 212013China School of Cyber Science and Engineering Southeast UniversityNanjing 211102China School of Computer Science and Technology Xidian UniversityXi’an 710071China

Electronic auctions(e-auctions)remove the physical limitations of traditional auctions and bring this mechanism to the general ***,most e-auction schemes involve a trusted auctioneer,which is not always credible in *** studies have applied cryptography tools to solve this problem by distributing trust,but they ignore the existence of *** this paper,a blockchain-based Privacy-Preserving and Collusion-Resistant scheme(PPCR)for double auctions is proposed by employing both cryptography and blockchain technology,which is the first decentralized and collusion-resistant double auction scheme that guarantees bidder anonymity and bid privacy.A two-server-based auction framework is designed to support off-chain allocation with privacy preservation and on-chain dispute resolution for collusion resistance.A Dispute Resolution agreement(DR)is provided to the auctioneer to prove that they have conducted the auction correctly and the result is fair and *** addition,a Concise Dispute Resolution protocol(CDR)is designed to handle situations where the number of accused winners is small,significantly reducing the computation cost of dispute *** experimental results confirm that PPCR can indeed achieve efficient collusion resistance and verifiability of auction results with low on-chain and off-chain computational overhead.

关键词： Privacy protection Collusion resistance Secure protocol Blockchain-based double auction Dispute resolution

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PriChain: Efficient Privacy-Preserving Fine-Grained Redactable Blockchains in Decentralized Settings

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Chinese Journal of Electronics 2025年第1期34卷 82-97页

作者： Hongchen Guo Weilin Gan Mingyang Zhao Chuan Zhang Tong Wu Liehuang Zhu Jingfeng Xue School of Computer Science and Technology Beijing Institute of Technology School of Cyberspace Science and Technology Beijing Institute of Technology School of Computer and Communication Engineering University of Science and Technology Beijing

Recently, redactable blockchain has been proposed and leveraged in a wide range of real systems for its unique properties of decentralization, traceability, and transparency while ensuring controllable on-chain data redaction. However, the development of redactable blockchain is now obstructed by three limitations, which are data privacy breaches, high communication overhead, and low searching efficiency, respectively. In this paper, we propose PriChain, the first efficient privacy-preserving fine-grained redactable blockchain in decentralized settings. PriChain provides data owners with rights to control who can read and redact on-chain data while maintaining downward compatibility, ensuring the one who can redact will be able to read. Specifically, inspired by the concept of multi-authority attribute-based encryption, we utilize the isomorphism of the access control tree, realizing fine-grained redaction mechanism, downward compatibility, and collusion resistance. With the newly designed structure, PriChain can realize O（n） communication and storage overhead compared to prior O（n2） schemes. Furthermore, we integrate multiple access trees into a tree-based dictionary, optimizing searching efficiency. Theoretical analysis proves that PriChain is secure against the chosen-plaintext attack and has competitive complexity. The experimental evaluations show that PriChain realizes 10× efficiency improvement of searching and 100× lower communication and storage overhead on average compared with existing schemes.

关键词： Resistance Access control Data privacy Dictionaries Blockchains Encryption Complexity theory Usability Protection

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One-dimensional wave theory analysis of factors and characteristics influencing errors in two-wave method data processing in SHPB

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Acta Mechanica Sinica 2025年第1期41卷 128-140页

作者： Minghui Ma Guangfa Gao School of Mechanical Engineering Nanjing University of Science and TechnologyNanjing 210094China

A simplified calculation of the specimen’s stress-strain curve is generally conducted using the two-wave method by the split Hopkinson pressure bar(SHPB),which aligns the onset of the transmitted and reflected ***,this approach neglects the travel time of elastic waves within the *** the travel time of elastic waves,this study quantitatively investigates the error characteristics and patterns of stress,strain,and strain rate in the specimen under different conditions using the theoretical two-wave method,and compares the results with those obtained using the onset-aligned twowave *** study reveals that the stress-time curves derived from the theoretical two-wave method are lower than the actual stress curves,whereas those obtained from the onset-aligned two-wave method are consistently higher than the actual stress curves,with the stress deviation approximating a constant value when the dimensionless time exceeds *** starting point of the stress-strain curves obtained by the theoretical two-wave method is not zero but a point on the strain axis,whereas the onset-aligned two-wave method always starts at ***,the slopes of the stress-strain curves obtained by both methods differ from the actual Young’s modulus of the material,and functional relationships between the slopes and the actual Young’s modulus are *** research offers theoretical guidance for the refined design of SHPB experiments and the accurate processing of data.

关键词： SHPB Stress wave effect Assumption of stress uniformity Dynamic stress-strain curve

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Output feedback active disturbance rejection control of an electro-hydraulic servo system based on command filter

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Chinese Journal of Aeronautics 2025年第2期38卷 214-225页

作者： Yanchun BAI Jianyong YAO Jian HU Guangbin FENG School of Mechanical Engineering Nanjing University of Science and TechnologyNanjing 210094China

The output feedback active disturbance rejection control of a valve-controlled cylinder electro-hydraulic servo system is investigated in this ***,a comprehensive nonlinear mathematical model that encompasses both matched and mismatched disturbances is *** to the fact that only position information can be measured,a linear Extended State Observer(ESO)is introduced to estimate unknown states and matched disturbances,while a dedicated disturbance observer is constructed to estimate mismatched *** from the traditional observer results,the design of the disturbance observer used in this study is carried out under the constraint of output ***,an output feedback nonlinear controller is proposed leveraging the aforementioned observers to achieve accurate trajectory *** mitigate the inherent differential explosion problem of the traditional backstepping framework,a finite-time stable command filter is ***,considering transient filtering errors,a set of error compensation signals are designed to counter their negative impact *** analysis affirms that the proposed control strategy ensures the boundedness of all signals within the closed-loop ***,under the specific condition of only time-invariant disturbances in the system,the conclusion of asymptotic stability is ***,the algorithm’s efficacy is validated through comparative experiments.

关键词： Active disturbance rejection control Extended state observer Output feedback Disturbance observer Command filter

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TDNN:A novel transfer discriminant neural network for gear fault diagnosis of ammunition loading system manipulator

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Defence technology(防务技术) 2025年第3期45卷 84-98页

作者： Ming Li Longmiao Chen Manyi Wang Liuxuan Wei Yilin Jiang Tianming Chen School of Mechanical Engineering Nanjing University of Science and TechnologyNanjing 210094China

The ammunition loading system manipulator is susceptible to gear failure due to high-frequency,heavyload reciprocating motions and the absence of protective gear *** a fault occurs,the distribution of fault characteristics under different loads is markedly inconsistent,and data is hard to label,which makes it difficult for the traditional diagnosis method based on single-condition training to generalize to different *** address these issues,the paper proposes a novel transfer discriminant neural network(TDNN)for gear fault ***,an optimized joint distribution adaptive mechanism(OJDA)is designed to solve the distribution alignment problem between two *** improve the classification effect within the domain and the feature recognition capability for a few labeled data,metric learning is introduced to distinguish features from different fault *** addition,TDNN adopts a new pseudo-label training strategy to achieve label replacement by comparing the maximum probability of the pseudo-label with the test *** proposed TDNN is verified in the experimental data set of the artillery manipulator device,and the diagnosis can achieve 99.5%,significantly outperforming other traditional adaptation methods.

关键词： Manipulator gear fault diagnosis Reciprocating machine Domain adaptation Pseudo-label training strategy Transfer discriminant neural network

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Enhanced Multi-Scale Object Detection Algorithm for Foggy Traffic Scenarios

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computers, Materials & Continua 2025年第2期82卷 2451-2474页

作者： Honglin Wang Zitong Shi Cheng Zhu School of Artificial Intelligence Nanjing University of Information Science and TechnologyNanjing210044China School of Computer Science Nanjing University of Information Science and TechnologyNanjing210044China School of Electrical&Computer Engineering University of Illinois at Urbana ChampaignUrbanaIL 61801USA

In foggy traffic scenarios, existing object detection algorithms face challenges such as low detection accuracy, poor robustness, occlusion, missed detections, and false detections. To address this issue, a multi-scale object detection algorithm based on an improved YOLOv8 has been proposed. Firstly, a lightweight attention mechanism, Triplet Attention, is introduced to enhance the algorithm’s ability to extract multi-dimensional and multi-scale features, thereby improving the receptive capability of the feature maps. Secondly, the Diverse Branch Block (DBB) is integrated into the CSP Bottleneck with two Convolutions (C2F) module to strengthen the fusion of semantic information across different layers. Thirdly, a new decoupled detection head is proposed by redesigning the original network head based on the Diverse Branch Block module to improve detection accuracy and reduce missed and false detections. Finally, the Minimum Point Distance based Intersection-over-Union (MPDIoU) is used to replace the original YOLOv8 Complete Intersection-over-Union (CIoU) to accelerate the network’s training convergence. Comparative experiments and dehazing pre-processing tests were conducted on the RTTS and VOC-Fog datasets. Compared to the baseline YOLOv8 model, the improved algorithm achieved mean Average Precision (mAP) improvements of 4.6% and 3.8%, respectively. After defogging pre-processing, the mAP increased by 5.3% and 4.4%, respectively. The experimental results demonstrate that the improved algorithm exhibits high practicality and effectiveness in foggy traffic scenarios.

关键词： Deep learning object detection foggy scenes traffic detection YOLOv8

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