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39th Annual AAAI Conference on Artificial Intelligence, AAAI 2025

作者： Li, Hao Wan, Fanggao Su, Yue Wu, Yue Zhang, Mingyang Gong, Maoguo School of Electronic Engineering Xidian University Xi'an 710071 China School of Artificial Intelligence Xidian University Xi'an 710071 China School of Computer Science and Technology Xidian University Xi'an 710071 China Key Laboratory of Collaborative Intelligence Systems Ministry of Education Xi'an 710071 China

ISBN: (纸本)157735897X

When the current physical adversarial patches cannot deceive thermal infrared detectors, the existing techniques implement adversarial attacks from scratch, such as digital patch generation, material production, and physical deployment. Besides, it is difficult to finely regulate infrared radiation. To address these issues, this paper designs an adversarial thermal display (AdvDisplay ) by assembling thermoelectric coolers (TECs) as an array. Specifically, to reduce the gap between patches in the physical and digital worlds and decrease the power of AdvDisplay device, heat transfer loss and electric power loss are designed to guide the patch optimization. In addition, a precise temperature control scheme for AdvDisplay is proposed based on proportional-integral-derivative (PID) control. Due to the accurate temperature regulation and the reusability of AdvDisplay, our method is able to improve the attack success rate and the efficiency of physical deployments. Extensive experimental results indicate that the proposed method possesses superior adversarial effectiveness compared to other methods and demonstrates strong robustness in physical attacks. Copyright © 2025, Association for the Advancement of Artificial Intelligence (***). All rights reserved.

关键词： Thermoelectric refrigeration

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Separating Content and Style for Unsupervised Image-to-Image Translation 32

Separating Content and Style for Unsupervised Image-to-Image...

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32nd British Machine Vision Conference, BMVC 2021

作者： Liu, Yunfei Wang, Haofei Yue, Yang Lu, Feng State Key Laboratory of Virtual Reality Technology and Systems School of Computer Science and Engineering Beihang University Beijing China Peng Cheng Laboratory Shenzhen China Beihang University Beijing China

Unsupervised image-to-image translation aims to learn the mapping between two visual domains with unpaired samples. Existing works focus on disentangling domain-invariant content code and domain-specific style code individually for multimodal purposes. However, less attention has been paid to interpreting and manipulating the translated image. In this paper, we propose to separate the content code and style code simultaneously in a unified framework. Based on the correlation between the latent features and the high-level domain-invariant tasks, the proposed framework demonstrates superior performance in multimodal translation, interpretability and manipulation of the translated image. Experimental results show that the proposed approach outperforms the existing unsupervised image translation methods in terms of visual quality and diversity. Code and data have been released at https://***/DreamtaleCore/SCS-UIT. © 2021. The copyright of this document resides with its authors.

关键词： computer vision

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Decoupled Doubly Contrastive Learning for Cross Domain Facial Action Unit Detection

arXiv

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arXiv 2025年

作者： Li, Yong Liu, Menglin Cui, Zhen Ding, Yi Zong, Yuan Zheng, Wenming Shan, Shiguang Guan, Cuntai School of Computer Science and Engineering The Key Laboratory of New Generation Artificial Intelligence Technology and Its Interdisciplinary Applications Southeast University Nanjing210096 China Key Laboratory of Intelligent Perception and Systems for High-Dimensional Information Ministry of Education School of Computer Science and Engineering Nanjing University of Science and Technology Nanjing210094 China School of Artificial Intelligence Beijing Normal University Beijing100875 China Key Laboratory of AI Safety Institute of Computing Technology Chinese Academy of Sciences Beijing100190 China University of Chinese Academy of Sciences Beijing100049 China School of Computer Science and Engineering Nanyang Technological University 50 Nanyang Avenue Singapore639798 Singapore Key Laboratory of Child Development and Learning Science of Ministry of Education School of Biological Science and Medical Engineering Nanjing210096 China

Despite the impressive performance of current vision-based facial action unit (AU) detection approaches, they are heavily susceptible to the variations across different domains and the cross-domain AU detection methods are under-explored. In response to this challenge, we propose a decoupled doubly contrastive adaptation (D2CA) approach to learn a purified AU representation that is semantically aligned for the source and target domains. Specifically, we decompose latent representations into AU-relevant and AU-irrelevant components, with the objective of exclusively facilitating adaptation within the AU-relevant subspace. To achieve the feature decoupling, D2CA is trained to disentangle AU and domain factors by assessing the quality of synthesized faces in cross-domain scenarios when either AU or domain attributes are modified. To further strengthen feature decoupling, particularly in scenarios with limited AU data diversity, D2CA employs a doubly contrastive learning mechanism comprising image and feature-level contrastive learning to ensure the quality of synthesized faces and mitigate feature ambiguities. This new framework leads to an automatically learned, dedicated separation of AU-relevant and domain-relevant factors, and it enables intuitive, scale-specific control of the cross-domain facial image synthesis. Extensive experiments demonstrate the efficacy of D2CA in successfully decoupling AU and domain factors, yielding visually pleasing cross-domain synthesized facial images. Meanwhile, D2CA consistently outperforms state-of-the-art cross-domain AU detection approaches, achieving an average F1 score improvement of 6%-14% across various cross-domain scenarios. © 2025, CC BY-NC-SA.

关键词： Contrastive Learning

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A Multi-Layer Software Architecture for Aerial Cognitive Multi-Robot systems in Power Line Inspection Tasks

A Multi-Layer Software Architecture for Aerial Cognitive Mul...

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2021 International Conference on Unmanned Aircraft systems, ICUAS 2021

作者： Silano, Giuseppe Bednar, Jan Nascimento, Tiago Capitan, Jesus Saska, Martin Ollero, Anibal Czech Technical University Faculty of Electrical Engineering Prague Czech Republic Universidade Federal da Paraiba Department of Computer Systems Brazil Grvc Robotics Laboratory University of Seville Spain

ISBN: (纸本)9780738131153

This paper presents a multi-layer software architecture to perform cooperative missions with a fleet of quad-rotors providing support in electrical power line inspection operations. The proposed software framework guarantees the compliance with safety requirements between drones and human workers while ensuring that the mission is carried out successfully. Besides, cognitive capabilities are integrated in the multi-vehicle system in order to reply to unforeseen events and external disturbances. The feasibility and effectiveness of the proposed architecture are demonstrated by means of realistic simulations. © 2021 IEEE.

关键词： Inspection

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Four-dimensional conserved topological charge vectors in plasmonic quasicrystals

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Science (New York, N.Y.) 2025年第6734期387卷 644-648页

作者： Tsesses, Shai Dreher, Pascal Janoschka, David Neuhaus, Alexander Cohen, Kobi Meiler, Tim C. Bucher, Tomer Sapir, Shay Frank, Bettina Davis, Timothy J. Meyer Zu Heringdorf, Frank Giessen, Harald Bartal, Guy rew and Erna Viterbi Department of Electrical and Computer Engineering Technion - Israel Institute of Technology Haifa Israel Department of Physics MIT-Harvard Center for Ultracold Atoms and Research Laboratory of Electronics Massachusetts Institute of Technology Cambridge MA United States Faculty of Physics and Center for Nanointegration University of Duisburg-Essen Duisburg-Essen (CENIDE) Duisburg Germany 4th Physics Institute Research Center SCoPE Integrated Quantum Science and Technology Center University of Stuttgart Stuttgart Germany Centre for Disruptive Photonic Technologies and School of Physical and Mathematical Sciences Nanyang Technological University Singapore Faculty of Mathematics and Computer Science Weitzmann Institute of Science Rehovot Israel School of Physics University of Melbourne Parkville VIC Australia

According to Noether's theorem, symmetries in a physical system are intertwined with conserved quantities. These symmetries often determine the system topology, which is made ever more complex with increased dimensionality. Quasicrystals have neither translational nor global rotational symmetry, yet they intrinsically inhabit a higher-dimensional space in which symmetry resurfaces. Here, we discovered topological charge vectors in four dimensions (4D) that govern the real-space topology of 2D quasicrystals and reveal their inherent conservation laws. We demonstrate control over the topology in pentagonal plasmonic quasilattices, mapped by both phase-resolved and time-domain near-field microscopy, showing that their temporal evolution continuously tunes the 2D projections of their distinct 4D topologies. Our work provides a route to experimentally probe the thermodynamic properties of quasicrystals and topological physics in 4D and above.

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Diagnosis of Liver Disease Induced by Hepatitis Virus Using Machine Learning Methods 8

Diagnosis of Liver Disease Induced by Hepatitis Virus Using ...

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8th International Conference on Information Technology Trends, ITT 2022

作者： Hafeez, Muhammad Ahmad Imran, Azhar Khan, Muhammad Imran Khan, Ali Haider Nawaz, Asif Ahmed, Sheeraz Air University Department of Creative Technologies Islamabad Pakistan Air University Faculty of Computing and A.I Department of Creative Technologies Islamabad Pakistan School of Systems and Technology University of Management and Technology Department of Computer Science Lahore Pakistan Faculty of Electrical Engineering Higher Colleges of Technology Dubai United Arab Emirates Iqra National University Department of Computer Sciences Peshawar Pakistan

ISBN: (数字)9781665487429

ISBN: (纸本)9781665487412

Liver, the largest vital organ in the human body, helps in digestion, energy storage, and toxic removal processes. Hepatitis A, B, C, fatty liver, cirrhosis, and liver cancer all cause swelling of the belly and legs, changes in the color of urine, and jaundice. Early identification is necessary to save the lives of those infected with the Hepatitis virus. Although clinical tests such as Abdominal Ultrasound, Chloride Blood Test, Liver Biopsy, Liver Function Tests (LFT), Magnetic Resonance Cholangio Pancreatography (MRCP), Total Protein and Albumin/Globulin (A/G) Ratio, and others are used in the diagnosis of Hepatitis virus, but high-level expertise of the doctors are also required. With continual advancements in Artificial Intelligence (AI) and Machine Learning algorithms, medically intelligent systems for early detection of fatal liver disease can be developed for prediction of deadly liver disease in the early stage. The goal of this paper is to examine the accuracies of several Machine Learning algorithms such as Linear Regression, Decision Tree, Random Forest, KNN, and SVM. For this work, author used the data set accessible at the UCI database and proved that the Support Vector Machine perform better than all other methods with.91.84% accuracy. © 2022 IEEE.

关键词： Decision trees

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Organic–inorganic hybrid perovskite scintillators for mixed field radiation detection

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InfoMat 2022年第9期4卷 97-108页

作者： Mengling Xia Guangda Niu Linyue Liu Runlong Gao Tong Jin Pengying Wan Weicheng Pan Xianpeng Zhang Zuoxiang Xie Sam Teale Zenghua Cai Jiajun Luo Shan Zhao Haodi Wu Shiyou Chen Zhiping Zheng Qingguo Xie Xiaoping Ouyang Edward HSargent Jiang Tang Wuhan National Laboratory for Optoelectronics(WNLO) WuhanChina School of Optical and Electronic Information Huazhong University of Science and Technology(HUST)WuhanChina State Key Laboratory of Intense Pulsed Radiation Simulation and Effect Northwest Institute of Nuclear TechnologyXi'anChina School of Nuclear Science and Technology Xi'an Jiaotong UniversityXi'anChina Department of Electrical and Computer Engineering University of TorontoTorontoOntarioCanada School of Microelectronics Fudan UniversityShanghaiChina College of Life Science and Technology Huazhong University of Science and TechnologyWuhanChina

Sensitive and fast detection of neutrons and gamma rays is vital for homeland security,high-energy physics,and proton ***-neutron detectors rely on light organic scintillators,andγ-ray detectors use heavy inorganic scintillators and *** mixed-field detection using a single material is highly challenging due to their contradictory *** we report hybrid perovskites(C_(8)H_(12)N)_(2)Pb(Br_(0.95)Cl_(0.05))_(4)that combine light organic cations and heavy inorganic skeletons at a molecular level to achieve unprecedented performance for mixed-field radiation *** neutron absorption due to a high density of hydrogen,strong radiative recombination within the highly confined[PbX_(6)]^(4-)layer,and sub-nanometer distance between absorption sites and radiative centers,enable a light yield of 41000 photons/MeV,detection pulse width of 2.97 ns and extraordinary linearity response toward both fast neutrons andγ-rays,outperforming commonly used fast-neutron *** energy spectrum,time-of-flight based fast-neutron/γ-ray discrimination and neutron yield monitoring were all successfully achieved using(C_(8)H_(12)N)_(2)Pb(Br_(0.95)Cl_(0.05))_(4)*** further demonstrate the monitoring of reaction kinetics and total power of a nuclear fusion *** envision that molecular hybridized scintillators open a new avenue for mixed-field radiation detection and imaging.

关键词： fast neutron mixed-field radiation detection organic-inorganic hybrid perovskite

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Backdoor-Empowered Regulable Privilege Authorization for Edge-Level Graph Learning in 6G Vehicular Networks

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IEEE Transactions on Consumer Electronics 2025年

作者： Yang, Xiao Li, Gaolei Wu, Jun Zhou, Kai Li, Jianhua Yang, Wu Shanghai Jiao Tong University School of Electronic Information and Electrical Engineering Shanghai China Shanghai Key Laboratory of Integrated Administration Technologies for Information Security Shanghai China The Hong Kong Polytechnic University Department of Computing Hong Kong Harbin Engineering University College of Computer Science and Technology Harbin China

Edge-Level Graph Learning System (EGLS) exhibits diverse applicability in flow prediction, route planning, and accident forecasting. Existing EGLS studies extremely stress absolute fairness and impartiality for all users, resultantly depriving its flexibility and humanity in addressing special circumstances and rendering the privilege authorization for exceptional responses challenging to achieve. To address this limitation, we present BackPriv, the first privilege authorization methodology enabling regulable privilege assignment or revocation in EGLS. Specifically, it is achieved through a creative edge backdoor mechanism, wherein the edge training samples are poisoned via user-specific privilege tokens to induce privilege outputs from the well-trained EGLS for authorized users. Moreover, related EGLS regulating strategies were proposed to dynamically realize the addition and revocation of user privileges by system retraining to guarantee privilege control in EGLS. Additionally, a Graph Mutual Information-based adaptive privilege token generation method is introduced to reduce the impact of privilege authorization on normal inputs and augment authorization functionality. Based on experiments with multiple real-world datasets, BackPriv demonstrates high success rates of privilege authorization under various scenarios ( 100%) and exerts minimal impact on normal task performance for regular inputs (mean accuracy drop 0.32%). © 1975-2011 IEEE.

关键词： Adversarial machine learning

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A Study of Gender Discussions in Mobile Apps

A Study of Gender Discussions in Mobile Apps

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International Mining Software Repositories, MSR

作者： Mojtaba Shahin Mansooreh Zahedi Hourieh Khalajzadeh Ali Rezaei Nasab School of Computing Technologies RMIT University Melbourne Australia School of Computing and Information Systems University of Melbourne Melbourne Australia School of Information Technology Deakin University Melbourne Australia School of Electrical and Computer Engineering Shiraz University Shiraz Iran

Mobile software apps ("apps") are one of the prevailing digital technologies that our modern life heavily depends on. A key issue in the development of apps is how to design gender-inclusive apps. Apps that do not consider gender inclusion, diversity, and equality in their design can create barriers (e.g., excluding some of the users because of their gender) for their diverse users. While there have been some efforts to develop gender-inclusive apps, a lack of deep understanding regarding user perspectives on gender may prevent app developers and owners from identifying issues related to gender and proposing solutions for improvement. Users express many different opinions about apps in their reviews, from sharing their experiences, and reporting bugs, to requesting new features. In this study, we aim at unpacking gender discussions about apps from the user perspective by analysing app reviews. We first develop and evaluate several Machine Learning (ML) and Deep Learning (DL) classifiers that automatically detect gender reviews (i.e., reviews that contain discussions about gender). We apply our ML and DL classifiers on a manually constructed dataset of 1,440 app reviews from the Google App Store, composing 620 gender reviews and 820 non-gender reviews. Our best classifier achieves an F1-score of 90.77%. Second, our qualitative analysis of a randomly selected 388 out of 620 gender reviews shows that gender discussions in app reviews revolve around six topics: App Features, Appearance, Content, Company Policy and Censorship, Advertisement, and Community. Finally, we provide some practical implications and recommendations for developing gender-inclusive apps.

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Effective Spline-GMPPT Approach Performance for Photovoltaic systems under Uniform Irradiance and Partial Shading Conditions

Effective Spline-GMPPT Approach Performance for Photovoltaic...

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Energy Transition and Security (ICETS), International Conference on

作者： Saidi Ahmed Abdelouahed Touhami Draoui Abdelghani Meziane Mohamed Amine Harrouz Abdelkader Department of Electrical Engineering Laboratory of Sustainable Development and Computer Science Ahmed Draia University Algeria Department of Electrical Engineering Laboratory of Smart Grid and Renewable Energy University of Tahri Mohamed Bechar Algeria Laboratory of Environmental and Energy Systems (LSEE) University Center Ali Kafi Tindouf Algeria NAAMA University Center Naama Algeria

In the literature, there are several criteria techniques classified to achieve the point of maximum power tracking (MPPT) in photovoltaic (PV) power systems, such as accuracy, speed, and simplicity. These criteria are often trade-offs; in this case, the higher accuracy generally achieved at the expense of two other criteria: speed and *** contribution proposes a new technique based on the Spline-Global-MPPT approach to provide its reliability in multiple criteria as an accurate, fast, and simple technique to find the MPP of PV power generation systems under two cases, such as uniform irradiance and partial shading conditions (PSCs), in the total distorted characteristics of the PV string. A cubic spline interpolation approach has proposed in this method, which defines from a few simple points an approximate *** localize the GMPP under standard (uniform) irradiance conditions, there are a huge number of interpolation-based approaches proposed in the literature. Unfortunately, this interpolation approach became incapable of detecting the point of the global maximum power (GMPP) under PSCs. The MPP of the system predicted by this new Spline-GMPPT method using a limited sample set of current and voltage, and it maintains this position as long as the external conditions stay unchanged. In the last part, the simulation results prove the reliability and robustness of the proposed approach.

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