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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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Towards Reliable Configuration Management in Clouds: A Lightweight Consistency Validation Mechanism for Virtual Private Clouds

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Chinese Journal of Electronics 2025年第1期34卷 49-63页

作者： Yuhang Qiu Gongming Zhao Hongli Xu Long Li He Huang Liusheng Huang School of Computer Science and Technology University of Science and Technology of China Suzhou Institute for Advanced Research University of Science and Technology of China School of Computer Science and Technology Soochow University

The virtual private cloud service currently lacks a real-time end-to-end consistency validation mechanism, which prevents tenants from receiving immediate feedback on their requests. Existing solutions consume excessive communication and computational resources in such large-scale cloud environments, and suffer from poor timeliness. To address these issues, we propose a lightweight consistency validation mechanism that includes real-time incremental validation and periodic full-scale validation. The former leverages message layer aggregation to enable tenants to swiftly determine the success of their requests on hosts with minimal communication overhead. The latter utilizes lightweight validation checksums to compare the expected and actual states of hosts locally, while efficiently managing the checksums of various host entries using inverted indexing. This approach enables us to efficiently validate the complete local configurations within the limited memory of hosts. In summary, our proposed mechanism achieves closed-loop implementation for new requests and ensures their long-term effectiveness.

关键词： Cloud computing Memory management Configuration management Reliability engineering Real-time systems Indexing

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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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Hierarchical Motion-Enhanced Matching Framework for Few-Shot Action Recognition

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IEEE Transactions on Multimedia 2025年 27卷 2450-2462页

作者： Gao, Hailiang Xie, Guo-Sen Yan, Rui Cui, Qiongjie Qu, Hongyu Shu, Xiangbo Nanjing University of Science and Technology School of Computer Science and Engineering Nanjing210094 China Nanjing University Department of Computer Science and Technology Nanjing210023 China

Few-Shot Action Recognition (FSAR) aims to recognize novel class action with limited annotated training data from the same class. Most FSAR methods subconsciously follow the few-shot image classification solutions by solely focusing on appearance-level matching between support and query videos, such as part-level matching, frame-level matching, and segment-level matching. However, these methods, almost always, have two main limitations: 1) generally ignore the relationship among these part-, frame- and segment-level features and 2) may mismatch the same class actions under fast-term and slow-term dynamics. To this end, we present a novel Hierarchical Motion-enhanced Matching (HM{^{2}}) framework to hierarchically learn the relation-aware multi-modal features, and jointly promote the multi-modal matching, including appearance-level matching on segments, frames, and parts, as well as the motion-level matching on dynamics. Specifically, we first propose a new Hierarchical Tokenizer (HT) to learn multi-modal features, namely utilizing a hierarchical Transformer to learn appearance-level features, along with a Slow-Fast Aware Motion (SFAM) strategy to learn motion-level features covering fast- and slow-term dynamics. Next, we propose a new Relation-aware Matcher (RM) to match the multi-modal features, by leveraging a Hierarchical Relational Graph Convolutional Network (H-RGCN) to capture the relationship among these appearance-level features. Further, a Dual Sample-to-Class Matching (DSCM) strategy is proposed to measure the bidirectional similarities among appearance- and motion-modal features by sample-to-class matching and class-to-sample matching. Extensive experiments on four golden FSAR datasets demonstrate significant performance improvements of HM2 compared with the state-of-the-art methods. © 1999-2012 IEEE.

关键词： Motion capture

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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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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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Witness encryption with updatable ciphertexts

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science China(Information sciences) 2025年第3期68卷 181-196页

作者： Yuzhu WANG Mingwu ZHANG School of Computer Science and Information Security Guilin University of Electronic Technology School of Computer Science Hubei University of Technology

Witness encryption(WE) is a novel type of cryptographic primitive that enables a message to be encrypted via an NP instance. Anyone who possesses a solution to this instance(i.e., a witness) can then recover the message from the *** introduce a variant of WE that allows ciphertext updates, referred to as ciphertext updateable WE(CUWE). With CUWE,a user can encrypt a message using an instance x and a tag t, and those who possess a valid witness w for x and match the access policy defined by tag t can decrypt the message. Furthermore, CUWE allows for the use of an update token to change the tag t of ciphertext to a different tag. This feature enables fine-grained access control, even after the ciphertext has been created, thereby significantly increasing the usefulness of the WE scheme. We demonstrate that such a WE framework with an updatable ciphertext scheme can be constructed using our puncturable instance-based deterministic encryption(PIDE) and indistinguishability obfuscation(iO). We also propose an instantiation of PIDE utilizing puncturable pseudorandom functions(PRFs) that provide(selectively) indistinguishable security. Finally, we expand our CUWE to ciphertext-updatable functional WE(CUFWE), which offers enhanced data access control.

关键词： witness encryption NP relation updatable ciphertext access control indistinguishable obfuscation

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Measuring discrete sensing capability for ISAC via task mutual information

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science China(Information sciences) 2025年第5期68卷 287-288页

作者： Fei SHANG Haohua DU Panlong YANG Xin HE Jingjing WANG Xiang-Yang LI School of Computer Science and Technology University of Science and Technology of China School of Cyber Science and Technology Beihang University School of Computer Science Nanjing University of Information Science and Technology School of Computer and Information Anhui Normal University

Thanks to its ubiquity,using radio frequency (RF) signals for sensing has found widespread *** traditional integrated sensing and communication systems,such as joint radar-communication systems,common sensing tasks include target localization and ***,increasingly intelligent systems,such as smart agriculture,lowaltitude economy,and smart healthcare,have demanded more comprehensive and continuous information sensing capabilities to support higher-level *** sensing has the potential to offer both spatial and temporal continuity,meeting the multi-dimensional sensing needs of these intelligent ***,numerous advanced systems have been proposed,expanding the application scope of RF sensing to be more pervasive,including discrete state ubiquitous sensing tasks (such as material identification [1]),and continuous state ubiquitous sensing tasks (such as health monitoring [2]).With the advent of the 6G era,it is anticipated that the sensing potential of RF systems will be further unleashed.

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Efficient Quantum Secure Vector Dominance and Its Applications in Computational Geometry

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IEEE Transactions on computers 2025年第6期74卷 2129-2143页

作者： Liu, Wenjie Su, Bingmei Sun, Feiyang Nanjing University of Information Science and Technology School of Software Nanjing210044 China Nanjing University of Information Science and Technology School of Computer Science Nanjing210044 China

Secure vector dominance is a key cryptographic primitive in secure computational geometry (SCG), determining the dominance relationship of vectors between two participants without revealing their private information. However, the security of traditional SVD protocols is compromised by the formidable computational power of quantum computing, and their efficiency needs further improvement. To address these challenges, an efficient quantum secure vector dominance (QSVD) protocol is proposed. Specifically, we first introduce a quantum private permutation (QPP) subprotocol to shuffle the elements of each participant's private input vector. To further facilitate secure data comparison, we propose an enhanced quantum millionaire subprotocol with equality determination functionality, building upon Jia's original protocol. Based on the above two subprotocols, we propose a QSVD protocol with polynomial complexity, deriving vector dominance in a single interaction with a semi-honest third party. Performance analyses confirm that QSVD protocol is correct, resilient against malicious attacks, and retains polynomial computational complexity, ensuring both security and efficiency. To demonstrate the scalability of the QSVD protocol, we illustrate its applications in several geometric computation problems, such as point-line inclusion determination, line-line intersect determination, and point-in-polygon determination. Finally, we validate the feasibility of our protocol by conducting comprehensive simulations on IBM's Qiskit platform, demonstrating its practical applicability and effectiveness in real quantum computing environments. © 1968-2012 IEEE.

关键词： Vectors

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