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Evaluating Generative Models: A Review of Challenges and Opportunities in Assessment of Generative Adversarial Networks

Evaluating Generative Models: A Review of Challenges and Opp...

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Computational Intelligence, Communication Technology and Networking (CICTN), international conference on

作者： Akash Shah Nitin Rakesh Monali Gulhane Pratik Agrawal Mandeep Kaur Saurav Dixit Department of CSE Symbiosis Institute of Technology Nagpur Campus Symbiosis International (Deemed University) Pune India Nagpur India School of Computer Science Engineering and Technology Bennett University Greater Noida Uttar Pradesh India Centre of Research Impact and Outcome Chitkara University Rajpura Punjab India

ISBN: (数字)9798331530389

ISBN: (纸本)9798331530396

Generative adversarial networks (GANs) have achieved remarkable success in image synthesis but evaluating their quality remains an open challenge. Existing automated metrics like FID are unable to fully capture generation performance across both objective fidelity and subjective aesthetic attributes important to human perception. This paper conducts an extensive review of literature on GAN evaluation methodology. Key limitations of current approaches are analyzed through a discussion of popular metrics and their inability to predict human judgment comprehensively. To address this, a novel hybrid evaluation model is proposed that combines automated scores with human ratings to provide a more balanced assessment. A pilot study demonstrates the hybrid metric can predict human response more accurately. However, additional validation is required. The review emphasizes the need for evaluation systems integrating richer human input to better optimize models according to user priorities. Interactive frameworks and techniques from computational creativity may help advance assessment towards comprehensively benchmarking generative capacity and artistic exploration.

关键词： measurement Training Reviews Image synthesis Computational modeling Instruments Benchmark testing Generative adversarial networks Hybrid power systems Creativity

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BIOSIGNALS 2021 - 14th international conference on Bio-Inspired systems and Signal Processing;Part of the 14th international joint conference on Biomedical Engineering systems and Technologies, BIOSTEC 2021

BIOSIGNALS 2021 - 14th International Conference on Bio-Inspi...

引用

14th international conference on Bio-Inspired systems and Signal Processing, BIOSIGNALS 2021 - Part of the 14th international joint conference on Biomedical Engineering systems and Technologies, BIOSTEC 2021

ISBN: (纸本)9789897584909

The proceedings contain 45 papers. The topics discussed include: evaluation of stair climbing as an approach for estimating heart rate recovery in daily activities;detection of error correlates in the motor cortex in a long term clinical trial of ECoG based brain computer interface;chaotic changes in fingertip pulse waves during autobiographical memory retrieval;elliptical fitting as an alternative approach to complex nonlinear least squares regression for modeling electrochemical impedance spectroscopy;characterization of upper limb functionality caused by neuromuscular disorders using novel motion features from a specialized gaming platform;self-similarity matrix of morphological features for motion data analysis in manufacturing scenarios;robust anomaly detection in time series through variational autoencoders and a local similarity score;machine learning based voice analysis in spasmodic dysphonia: an investigation of most relevant features from specific vocal tasks;and cross-phase emotion recognition using multiple source domain adaptation.

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Analysis of Attitude, Trust, and Subjective Norm Impact on Intention to Use Profile Verification in Dating Applications in Indonesia

Analysis of Attitude, Trust, and Subjective Norm Impact on I...

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computer Science, Information Technology and Engineering (ICCoSITE), international conference on

作者： Kenny Prasetyo Xenia Dharmawan Erwin Halim Marylise Hebrard Information Systems Department School of Information Systems Bina Nusantara University Jakarta Indonesia Enterprise Law Program Study Institut Des Usages Montpellier France

Despite the popularity of online dating Application, there are increasing security issues and challenges with them, such as the creation of fake accounts and phishing, which are commonly called romance scams, one of which is fake user data or even completely fake profiles. This research will discuss the profile verification technology that has been developed in several online dating applications to verify the authenticity of user profiles using an algorithm capable of detecting fake profiles. This study used Sequential Equation modeling (SEM) method and SMART PLS as a statistical tool. A total of 561 data from online dating application users in Indonesia were collected in October 2022. The purpose of this study was to determine the impact of Attitude, Trust, and Subjective Norm to intention to use profile verification in Dating Application in Indonesia. Attitude, Trust, and Subjective Norms will be special variables that affect the user's intention to use Profile Verification on Dating Applications in Indonesia. The results of the study found that all research hypotheses had a significant effect on each variable relationship in the research model.

关键词： computer science Numerical analysis Phishing Position measurement Social factors Mathematical models Mobile applications

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Fruit Quality Detection:A Comparative Study of the YOLO Series

Fruit Quality Detection:A Comparative Study of the YOLO Seri...

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Innovative Computing, Intelligent Communication and Smart Electrical systems (ICSES), international conference on

作者： Saranya G Kumaran K Angad Rehsi Anand Misra Mayank Mishra School of Computer Science and Engineering (SCOPE) Vellore Institute of Technology Chennai India

ISBN: (数字)9798331543624

ISBN: (纸本)9798331543631

Fruit Quality detection is an important aspect in the agricultural and food supply chain, it is necessary to ensure that only fruits that meet a certain standard of quality reach consumers. Generally, this process is done manually by workers carrying out visual inspection based on the fruit's appearance, texture, and color; this can be time-consuming and is subject to human errors. This may cause inefficiencies in large-scale production and possibly compromise the quality of fruits reaching the market. A fruit quality detection system is designed in this study using computer vision techniques, and a comparative analysis of YOLO series models is conducted for fruit quality detection. The analysis focuses on various performance metrics, including speed, accuracy, and robustness, while considering the benefits of each architecture. Each model is assessed to highlight its key strengths and ability to accurately classify fruit quality, with the goal of selecting the most suitable model to address the shortcomings of traditional methods. The performances of YOLOv8, YOLOv9, YOLOv10, and YOLOv11 are analyzed in terms of precision, recall, and mean Average Precision (mAP). YOLOv9 had the highest mAP50 and mAP50-95 with the score of 0.981 for both. Furthermore, the model has a very high recall of about 0.936, which makes it ideal for detection tasks needed in precision-demanding areas.

关键词： YOLO measurement computer vision Visualization Computational modeling Supply chains Production Inspection Robustness Standards

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Gradient-YOLO: Exploring the integration of gradient architecture into the YOLO network

Gradient-YOLO: Exploring the integration of gradient archite...

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international joint conference on Neural Networks (IJCNN)

作者： Gang Li Cheng Zhang Delong Han Letian Gao Mingle Zhou Key Laboratory of Computing Power Network and Information Security Ministry of Education Shandong Computer Science Center (National Supercomputer Center in Jinan) Qilu University of Technology (Shandong Academy of Sciences) Jinan China Shandong Provincial Key Laboratory of Computer Networks Shandong Fundamental Research Center for Computer Science Jinan China SHANDONG SCICOM Information and Economy Research Institute Co. Ltd Jinan China

ISBN: (数字)9798350359312

ISBN: (纸本)9798350359329

Object detection is an essential task in the field of computer vision. The one-stage object detection model directly completes object detection through a single forward propagation and has fast real-time object detection capabilities, making it widely used—especially the model of the You Only Look Once (YOLO) series. Improving the detection accuracy of the YOLO model has always been a research topic. The gradient architecture cascades feature information extraction and aggregates all features at the end, which can improve the feature fusion ability of the network. Combining the idea of gradient architecture, this paper proposes a YOLO based on gradient architecture: Gradient-YOLO. Specifically, this paper integrates gradient architecture into the backbone, neck, and bottleneck structures in the YOLO network, obtaining gradient backbone, gradient neck, and gradient bottleneck, respectively. By combining gradient architecture, various network parts in Gradient-YOLO can fully aggregate multi-layer features, reduce feature loss, and thus improve detection accuracy. This paper takes the mature YOLOv5 model and the latest YOLOv8 model as the baseline and combines gradient thinking to obtain Gradient-YOLOv5 and GradientYOLOv8. Moreover, conduct experimental testing on the MS COCO dataset. Regarding the mAP@.5 detection indicator, compared to YOLOv5s, Gradient-YOLOv5s increased by 5.07%. Compared to YOLOv8n, Gradient-YOLOv8n has increased by 4.63%. Therefore, the combination of gradient architecture can improve the detection accuracy of YOLO networks.

关键词： YOLO Accuracy Aggregates Computational modeling computer architecture Feature extraction Real-time systems

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11th international joint conference on Rough Sets, IJCRS 2025

11th International Joint Conference on Rough Sets, IJCRS 202...

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11th international joint conference on Rough Sets, IJCRS 2025

ISBN: (纸本)9783031927461

The proceedings contain 90 papers. The special focus in this conference is on Rough Sets. The topics include: Rough Shadowed Set: Hybridization of Rough Set and Shadowed Set;an Analysis of the Efficacy of Rough Set Models Within the Framework of Binary Information Tables;a Novel Weighted k-Nearest Neighborhood Rough Set Approach for Interval-Valued Decision Information System;a Class-Specific Attribute Reduction Acceleration Algorithm Based on Neighborhood Rough Set;optimal Scale Selections of Inconsistent Generalized Multi-scale Ordered Decision Information systems with Multi-scale Decision Attributes Based on the Set-Valued Dominance Matrix;new Insights Into Reduction Theory: Building on Concept Reduction;fuzzy Clustering Ensemble Method Based on Dempster-Shafer Theory;attribute Reduction Method of Fuzzy Rough Sets Based on Improved Overlap Degree;intuitionistic Fuzzy Clustering Indices Based on Generalized Fuzzy Orthopartitions;Virtual Exposure Bracketing for HDR Imaging Using Fuzzy Membership;attribute Reduction in Multi-scale Fuzzy Decision systems;tri-Training with Granular-Ball in Weighted Fuzzy Rough Sets;on q-Rung Orthopair Fuzzy Rough Generalized Dombi Aggregation Operators;optimising the Attribute Order in Fuzzy Rough Rule Induction;multi-criteria Attribute Ranking Based on Rough Sets and Interval-Valued Fuzzy Sets;MGSMCAN: MultiGranularity Semantic Margin Cross-Annotation Network;hierarchical Multi-label Attribute Reduction Based on Granular-Ball;similarity measurement and Application of Normal Clouds Based on Bhattacharyya Distance;the Description of Isomorphism Between Concept Lattices Based on the Special Datas;multi-view Graph Convolutional Network via Granular-Ball Computing;fuzzy Rough Outlier Detection Method in Two-Layer Granular Ball Space;Unsupervised Granular-Ball Partitioning Algorithm Based on KL Divergence;MOGBC: Multi-objective Driven Granular Ball Clustering;fast Minimum Spanning Tree Clustering Algorithm Based on Granular-Ball Computing;

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11th international joint conference on Rough Sets, IJCRS 2025

11th International Joint Conference on Rough Sets, IJCRS 202...

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11th international joint conference on Rough Sets, IJCRS 2025

ISBN: (纸本)9783031927430

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11th international joint conference on Rough Sets, IJCRS 2025

11th International Joint Conference on Rough Sets, IJCRS 202...

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11th international joint conference on Rough Sets, IJCRS 2025

ISBN: (纸本)9783031927409

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Detection and Suppression of Epileptiform Seizures via Model-Free Control and Derivatives in a Noisy Environment

Detection and Suppression of Epileptiform Seizures via Model...

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international conference on systems and Control (ICSC)

作者： Cédric Join D. Blair Jovellar Emmanuel Delaleau Michel Fliess CRAN (CNRS UMR 7039)) Université de Lorraine Vandœuvre-lés-Nancy France AL.I.E.N. Vézelise France Department of Neurology & Stroke University of Tübingen Tübingen Germany Hertie-Institute for Clinical Brain Research University of Tübingen Tübingen Germany ENI Brest IRDL (CNRS UMR 6027) Brest France LIX (CNRS UMR 7161) École polytechnique Palaiseau France

ISBN: (数字)9798331531812

ISBN: (纸本)9798331531829

Recent advances in control theory yield closed-loop neurostimulations for suppressing epileptiform seizures. These advances are illustrated by computer experiments which are easy to implement and to tune. The feedback synthesis is provided by an intelligent proportional-derivative (iPD) regulator associated to model-free control. This approach has already been successfully exploited in many concrete situations in engineering, since no precise computational modeling is needed. iPDs permit tracking a large variety of signals including high-amplitude epileptic activity. Those unpredictable pathological brain oscillations should be detected in order to avoid continuous stimulation, which might induce detrimental side effects. This is achieved by introducing a data mining method based on the maxima of the recorded signals. The real-time derivative estimation in a particularly noisy epileptiform environment is made possible due to a newly developed algebraic differentiator. The virtual patient is the Wendling model, i.e., a set of ordinary differential equations adapted from the Jansen-Rit neural mass model in order to generate epileptiform activity via appropriate values of excitation- and inhibition-related parameters. Several simulations, which lead to a large variety of possible scenarios, are discussed. They show the robustness of our control synthesis with respect to different virtual patients and external disturbances.

关键词： Adaptation models Regulators Computational modeling Neurostimulation Brain modeling Mathematical models Robustness Real-time systems Noise measurement Data mining

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IOTToe: A Smart System for In/Out-Toeing Foot Identification

IOTToe: A Smart System for In/Out-Toeing Foot Identification

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international conference on Communications, Information System and computer Engineering (CISCE)

作者： Ata Jahangir Moshayedi Izhar Lskar Shuxin Yang Shashikant Kisanrao Shinde Abolfazl Razi Mehran Emadi Andani School of Information Engineering Jiangxi University of Science and Technology Ganzhou Jiangxi China Yashavantrao Chavan Institute of Science Satara Maharashtra India School of Computer Science Clemson University Clemson SC USA Department of Neurosciences Biomedicine and Movement Sciences University of Verona Verona Italy

ISBN: (数字)9798350353174

ISBN: (纸本)9798350353181

Toe-in and toe-out angles show difficulties in assessing and addressing gait abnormalities, posture issues, and joint stress, requiring sophisticated monitoring and treatment strategies in musculoskeletal health. Diagnostic and Detecting toe-in/out angles is important because of its rules and index into gait abnormalities, posture imbalances, and potential joint stress, enabling early intervention and personalized treatment to improve musculoskeletal health and prevent long-term complications. While various diagnostic methods have been developed, the diagnosis of this disease continues to rely heavily on the expertise of healthcare professionals. Researchers are actively seeking more dependable and convenient approaches to assist patients in achieving earlier diagnoses and monitoring treatment progress effectively. With the importance of this measurement, the proposed design system named IOTToe based on the Internet of Things (IOT) aims to create an effective and user-friendly tool for measuring toe-in and toe-out angles accurately and easily. A web-based interface enables real-time remote tracking of foot alignment, reducing the need for physical tests and making reports. The telemetric capabilities facilitate efficient data transmission, empowering medical professionals with valuable insights for personalized treatment and enhancing healthcare efficiency. Integration with hospital systems supports advanced research in musculoskeletal health. The obtained results show the ability of the system to help the diagnosis and treatment process.

关键词： Legged locomotion Musculoskeletal system Hospitals Sensors Telemetry Internet of Things Monitoring

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