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38th Conference on Neural Information Processing systems, NeurIPS 2024

作者： Zeng, Yu Zhang, Yang Liu, Jiachen Shen, Linlin Deng, Kaijun He, Weizhao Wang, Jinbao Computer Vision Institute School of Computer Science & Software Engineering Shenzhen University China Shenzhen Institute of Artificial Intelligence and Robotics for Society China National Engineering Laboratory for Big Data System Computing Technology Shenzhen University China Guangdong Provincial Key Laboratory of Intelligent Information Processing China

Hair editing is a critical image synthesis task that aims to edit hair color and hairstyle using text descriptions or reference images, while preserving irrelevant attributes (e.g., identity, background, cloth). Many existing methods are based on StyleGAN to address this task. However, due to the limited spatial distribution of StyleGAN, it struggles with multiple hair color editing and facial preservation. Considering the advancements in diffusion models, we utilize Latent Diffusion Models (LDMs) for hairstyle editing. Our approach introduces Multi-stage Hairstyle Blend (MHB), effectively separating control of hair color and hairstyle in diffusion latent space. Additionally, we train a warping module to align the hair color with the target region. To further enhance multi-color hairstyle editing, we fine-tuned a CLIP model using a multi-color hairstyle dataset. Our method not only tackles the complexity of multi-color hairstyles but also addresses the challenge of preserving original colors during diffusion editing. Extensive experiments showcase the superiority of our method in editing multi-color hairstyles while preserving facial attributes given textual descriptions and reference images. © 2024 Neural information processing systems foundation. All rights reserved.

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An optimized Parkinson’s disorder identification through evolutionary fast learning network

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International Journal of Intelligent Computing and Cybernetics 2022年第3期15卷 383-400页

作者： Bouslah Ayoub Taleb Nora LRI Laboratory Computer Science DepartmentUniversity of BadjiMokhtar AnnabaAnnabaAlgeria Complex System Engineering Laboratory Computer Science DepartmentUniversity of Badji Mokhtar AnnabaAnnabaAlgeria

Purpose-Parkinson’s disease(PD)is a well-known complex neurodegenerative ***,its identification is based on motor disorders,while the computer estimation of its main symptoms with computational machine learning(ML)has a high exposure which is supported by researches ***,ML approaches required first to refine their parameters and then to work with the best model *** process often requires an expert user to oversee the performance of the ***,an attention is required towards new approaches for better forecasting ***/methodology/approach-To provide an available identification model for Parkinson disease as an auxiliary function for clinicians,the authors suggest a new evolutionary classification *** core of the prediction model is a fast learning network(FLN)optimized by a genetic algorithm(GA).To get a better subset of features and parameters,a new coding architecture is introduced to improve GA for obtaining an optimal FLN ***-The proposed model is intensively evaluated through a series of experiments based on Speech and HandPD benchmark *** very popular wrappers induction models such as support vector machine(SVM),K-nearest neighbors(KNN)have been tested in the same *** results support that the proposed model can achieve the best performances in terms of accuracy and ***/value-A novel efficient PD detectionmodel is proposed,which is called *** A-W-FLN utilizes FLN as the base classifier;in order to take its higher generalization ability,and identification capability is alsoembedded to discover themost suitable featuremodel in the detection ***,the proposedmethod automatically optimizes the FLN’s architecture to a smaller number of hidden nodes and solid connecting *** helps the network to train on complex PD datasets with non-linear features and yields superior result.

关键词： Parkinson’s disease(PD) Fast learning network(FLN) Genetic algorithm(GA) Speech and handwriting patterns PD identification system

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Games for Artificial Intelligence Research: A Review and Perspectives

IEEE Transactions on Artificial Intelligence

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IEEE Transactions on Artificial Intelligence 2024年第12期5卷 5949-5968页

作者： Hu, Chengpeng Zhao, Yunlong Wang, Ziqi Du, Haocheng Liu, Jialin Research Institute of Trustworthy Autonomous System Guangdong Provincial Key Laboratory of Brain-Inspired Intelligent Computation Department of Computer Science and Engineering Shenzhen518055 China LightSpeed Studios Tencent Shenzhen518057 China

Games have been the perfect test beds for artificial intelligence (AI) research for the characteristics that widely exist in real-world scenarios. Learning and optimization, decision-making in dynamic and uncertain environments, game theory, planning and scheduling, design, and education are common research areas shared between games and real-world problems. Numerous open-source games or game-based environments have been implemented to study AI. In addition to single- or multiplayer, collaborative, and adversarial games, there has also been growing interest in implementing platforms for creative design in recent years. Those platforms provide ideal benchmarks for exploring and comparing AI ideas and techniques. This article reviews the games and game-based platforms for AI research, provides guidance on matching particular types of AI with suitable games for testing and matching particular needs in games with suitable AI techniques, discusses the research trend induced by the evolution of those games and platforms, and gives an outlook. © 2024 IEEE.

关键词： Reinforcement learning

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Operational Reliability Modeling and Assessment of Battery Energy Storage Based on Lithium-ion Battery Lifetime Degradation

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Journal of Modern Power systems and Clean Energy 2022年第6期10卷 1738-1749页

作者： Lin Cheng Yuxiang Wan Yanglin Zhou David Wenzhong Gao State Key Laboratory of Control and Simulation of Power System and Generation Equipment Department of Electrical EngineeringTsinghua UniversityBeijingChina Department of Electrical and Computer Engineering University of DenverDenverUSA IEEE

Battery energy storage(BES)systems can effectively meet the diversified needs of power system dispatching and assist in renewable energy *** reliability of energy storage is essential to ensure the operational safety of the power ***,BES systems are composed of battery *** suggests that BES performance depends not only on the configuration but also on the operating state over different lifetime *** lack of safety and reliability is the main bottleneck preventing widespread applications of BES ***,a reliability assessment algorithm and a weak-link analytical method for BES systems are proposed while considering battery lifetime ***,a novel lithium-ion battery model is proposed to identify the degradation rate of solid electrolyte interphase film formation and capacity *** impacts of different operating conditions are considered in stress factor ***,a reliability assessment algorithm for a BES system is introduced based on a universal generating *** innovative weak-link analytical method based on the reliability importance index is proposed that combines the evaluation results of state-oriented and state-change-oriented indexes through an entropy weight *** model,algorithm,indexes,and the usefulness are demonstrated in case studies based on aging test data and actual bus operating *** results demonstrate the effects of the battery status and working conditions on BES ***-link analysis is also used to assist BES systems in avoiding short-board batteries to achieve long lifetimes and efficient operation.

关键词： Battery energy storage lifetime degradation operational reliability capacity plummeting weak-link analysis

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Re-identification of Saimaa Ringed Seals from Image Sequences 23rd

Re-identification of Saimaa Ringed Seals from Image Sequen...

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22nd Scandinavian Conference on Image Analysis, SCIA 2023

作者： Nepovinnykh, Ekaterina Vilkman, Antti Eerola, Tuomas Kälviäinen, Heikki Computer Vision and Pattern Recognition Laboratory Department of Computational Engineering Lappeenranta-Lahti University of Technology LUT Lappeenranta Finland

ISBN: (纸本)9783031314346

Automatic game cameras are commonly used for monitoring wildlife as they allow to document of the activity of animals in a non-invasive manner. By utilizing a large number of cameras and identifying individual animals from the images, it is possible to, for example, estimate the population size and study the migration patterns of the animals. Large image volumes produced by the cameras call for automated methods for the analysis. Re-identification of animals has commonly been implemented through one-to-one matching, where images are processed individually and the best match is searched from the database of known individuals one by one. Game cameras can be configured to produce a sequence of images that allows capturing the animal from multiple angles potentially improving the re-identification accuracy. In this work, the re-identification of the endangered Saimaa ringed seal (pusa hispida saimensis) from image sequences is studied. The individual identification is realized through Saimaa ringed seal’s unique pelage pattern. The proposed one-to-many and many-to-many matching methods aggregate the pelage pattern features over the whole sequence providing better embeddings for the re-identification tasks. We show that the proposed aggregation method outperforms traditional one-to-one matching based re-identification by a large margin. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Animals

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Enhancing Ocean Scene Video Captioning with Multimodal Pre-Training and Video-Swin-Transformer 49

Enhancing Ocean Scene Video Captioning with Multimodal Pre-T...

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49th Annual Conference of the IEEE Industrial Electronics Society, IECON 2023

作者： Chen, Xinyu Zhao, Meng Shi, Fan Zhang, Meng'en He, Yu Chen, Shengyong School of Computer Science and Engineering Tianjin University of Technology Laboratory of Computer Vision and System of Ministry of Education Tianjin300384 China Technology and Engineering Center for Space Utilization Chinese Academy of Sciences Key Laboratory of Space Utilization Beijing100190 China

ISBN: (纸本)9798350331820

With the success of multimodal pre-training models in the video-language field and various downstream tasks, previous multimodal models used 3DCNN networks as video feature extractors, which have limitations in interacting and fusing with text features. This paper proposes a multimodal pre-training model that utilizes a Video-Swin-Transformer-based network to encode both video and text data, to achieve better performance in video understanding. The model consists of four modules: video encoder, text encoder, interact encoder, and caption decoder to accomplish the task of ocean scene video captioning. A dataset of ocean scene videos, including various content types such as sea surfaces and shores, is also constructed. The training process is divided into two stages: pre-training and fine-tuning. Pre-training is performed on the Howto100m dataset to allow the model to learn video captions in natural scenes and complete video-language matching tasks. The fine-tuning stage is then performed on the ocean1000 dataset to better understand the events and content in ocean scene videos and generate captions that conform to ocean scene video descriptions. The model achieves satisfying results on both the public dataset YouCook2 and the proprietary dataset Ocean1000, demonstrating its ability in video-text information fusion and interaction. © 2023 IEEE.

关键词： Signal encoding

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Preventive Power Outage Estimation Based on A Novel Scenario Clustering Strategy

Preventive Power Outage Estimation Based on A Novel Scenario...

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2024 IEEE Power and Energy Society General Meeting, PESGM 2024

作者： Wang, Xiaofei Liu, Weijia Ding, Fei Yao, Yiyun Zhao, Junbo Power System Engineering Center National Renewable Energy Laboratory Golden United States Department of Electrical and Computer Engineering University of Connecticut Storrs United States

The increasing occurrence of extreme weather events is challenging power grid operation. For extreme weather events, the system operator is responsible for estimating the power outages and scheduling the restoration resources. This paper proposes an outage evaluation framework to identify the possible unserved load profiles, vulnerable areas, and mobile energy adequacy. The outputs of an outage prediction model tool are used to generate numerous faulted line scenarios. Next, each scenario's nodal unserved load profile is obtained by solving a three-phase restoration model that considers repair crews and mobile energy resources (MERs). Then, a novel scenario clustering strategy is developed to cluster the unserved load profiles into multiple representative profiles which the system operator can focus on. Finally, case studies on a distribution system evaluate the damage caused by an extreme weather event and verify the effectiveness of the proposed scenario clustering strategy. © 2024 IEEE.

关键词： Mobile energy resources (MERs) power system resilience preventive outage evaluation scenario clustering

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A Copyright Authentication Method Balancing Watermark Robustness and Data Distortion 26

A Copyright Authentication Method Balancing Watermark Robust...

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26th International Conference on computer Supported Cooperative Work in Design, CSCWD 2023

作者： Wang, Chundong Li, Yue Tianjin University of Technology Tianjin300384 China National Engineering Laboratory for Virus Prevention and Control Technology Tianjin China Key Laboratory of Computer Vision and System Ministry of Education Tianjin China

ISBN: (纸本)9798350331684

Database watermarking plays an irreplaceable role in copyright authentication and data integrity protection, but the robustness of the watermark and the resulting data distortion are a pair of contradictory objects that cannot be ignored. To solve this problem, a reversible database watermarking method, named IGADEW, is proposed to balance the relationship between them. The biggest difference from previous research is that IGADEW synthesizes the optimization objects and obtain various parameters through genetic algorithm (GA). Second, the fitness function considers the weights of robustness and distortion, aiming to find the optimal balance between the two. IGADEW uses the Hash-based Message Authentication Code (HMAC) algorithm to encrypt the experimental parameters and uses the primary key hash algorithm for data grouping, both to ensure robustness. And the data distortion is limited with the help of threshold constraints. Finally, experiments using the UCI dataset demonstrate the effectiveness of IGADEW. Experimental results show that, compared with existing methods, IGADEW is more robust against common attacks, with lower data distortion. © 2023 IEEE.

关键词： Copyrights

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Spectral period doubling and encoding of dissipative optical solitons via gain control

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PhotoniX 2024年第1期5卷 290-305页

作者： Kangwen Yang Yi Zhou Yuqing Ling Kevin K.Tsia Heping Zeng Kenneth K.Y.Wong Shanghai Key Laboratory of Modern Optical System and Engineering Research Center of Optical Instrument and SystemMinistry of EducationSchool of Optical Electrical and Computer EngineeringUniversity of Shanghai for Science and TechnologyShanghai 200093China Department of Electrical and Electronic Engineering The University of Hong KongHong KongChina Advanced Biomedical Instrumentation Centre Hong Kong Science ParkHong KongChina State Key Laboratory of Precision Spectroscopy East China Normal UniversityShanghai 200062China

Period-doubling bifurcation,as an intermediate state between order and chaos,is ubiquitous in all disciplines of nonlinear ***,previous experimental observations of period doubling in ultrafast fiber lasers are mainly restricted to self-sustained steady state,controllable manipulation and dynamic switching between period doubling and other intriguing dynamical states are still largely ***,we propose to expand the vision of dissipative soliton periodic doubling,which we illustrate experimentally by reporting original spontaneous,collisional,and controllable spectral period doubling in a polarization-maintaining ultrafast fiber ***,the spontaneous period doubling can be observed in both single-and *** mechanism of the switchable state and periodic doubling was revealed by numerical ***,state transformation of individual solitons can be resolved during the collision of triple solitons involving stationary,oscillating,and period ***,controllable deterministic switching between period doubling and other dynamical states,as well as exemplifying the application of period-doubling-based digital encoding,is achieved under programmable pump *** results open a new window for unveiling complex Hopf bifurcation in dissipative systems and bring useful insights into nonlinear science and applications.

关键词： Period doubling Mode locking Ultrafast fiber lasers

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A Two-Step Approach for Multi-topology Identification and Parameter Estimation of Power Distribution Networks

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CSEE Journal of Power and Energy systems 2024年第6期10卷 2446-2456页

作者： Li Ma Lei Wu Nian Liu Wei Pei Institute of Electrical Engineering and Key Laboratory of Long-Duration and Large-Scale Energy StorageChinese Academy of SciencesBeijing 100190China Department of Electrical and Computer Engineering Stevens Institute of TechnologyHobokenNJ 07030USA State Key Laboratory of Alternate Electrical Power System With Renewable Energy Sources North China Electric Power UniversityBeijing 102206China

To improve observability in power distribution networks(PDN),a two-step framework of multi-topology identification and parameter estimation is proposed in this ***,in the first step,a mixed-integer linear program(MILP)model-based split method is proposed to recognize mixed topologies in a multi-record dataset without a prerequisite on the number of topology categories and values of nodal voltage phase *** the second step,line parameters and nodal voltage phase angles are estimated using the Newton-Raphson method based on nodal measurements of real and reactive power injections,as well as voltage ***,a modified estimation model is proposed to apply to the multitopology ***,case studies on an IEEE 33-bus system illustrate the effectiveness of the proposed models in identifying the PDN’s topologies,as well as estimating line parameters and voltage phase angles.

关键词： MILP Newton-Raphson method parameter estimation power distribution system topology identification

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