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Mediterranean Conference on control and Automation (MED)

作者： R. Bustan R. Boriceanu D. Popescu L. Ichim Faculty of Automatic Control and Computer Science National University of Science and Technology POLITEHNICA Bucharest Bucharest Romania

ISBN: (数字)9798350395440

ISBN: (纸本)9798350395457

Face emotion recognition is an important subject in fields such as psychology and cognitive sciences, as well as in applications that use machine learning methods to create intelligent models capable of understanding human behavior. This paper addresses the challenge of negative facial emotion recognition by employing a comprehensive framework. Our approach leverages 68 facial landmarks and integrates three pre-trained convolutional neural network models (VGG19, DenseNet201, Inception V3) into a unified weighted voting system. The efficacy of our system is evaluated using the Extended Cohn-Kanade (CK+) and Karolinska Directed Emotional Faces (KDEF) databases. The results showcase the effectiveness of our approach in accurately identifying negative facial emotions. This research contributes to the advancement of emotion recognition systems., offering a promising methodology with implications for fields such as psychology., cognitive sciences., and the broader spectrum of intelligent systems reliant on facial expression analysis.

关键词： Human computer interaction Deep learning Emotion recognition Face recognition Neural networks Mental health Robustness

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Tobacco Plant Detection Using a Performant Neural Network

Tobacco Plant Detection Using a Performant Neural Network

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International Conference on System Theory, control, and Computing (ICSTCC)

作者： Andrei Vicol Dan Popescu Loretta Ichim Faculty of Automatic Control and Computer Science National University of Science and Technology Politehnica Bucharest Bucharest Romania

ISBN: (数字)9798350364293

ISBN: (纸本)9798350364309

Accurate plant detection is an important task in modern precision agriculture, enabling growers to quantify their plant numbers and estimate crop yields accurately. This paper looks at an example tobacco crop with a small dataset and aims to augment it to produce reliable object detection and counting. To obtain a trainable dataset, the source masks are separated into base classes, noise is removed from the masks, and images are augmented. The newly obtained clean dataset is then split into patches and used to obtain a JSON file describing all the labels present in the image. The model used for this job is YOLOv8 and it is trained on a COCO-formatted augmented dataset. Choosing the proper set of weights is done by evaluating and studying the performance metrics over the whole training phase, picking the one that offers the greatest balance between performance, training duration, and risk of induced overfitting due to over-learning.

关键词： Training Measurement Precision agriculture Plants (biology) Noise Neural networks Object detection Reliability Crop yield Overfitting

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Healing IoT Data for Indoor Air Quality Using Artificial Intelligence

Healing IoT Data for Indoor Air Quality Using Artificial Int...

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E-Health and Bioengineering Conference (EHB)

作者： Radu Nicolae Pietraru Adriana Olteanu Alexandru Ştefan Velicu Robert-Alexandru Craciun Faculty of Automatic Control and Computer Science National University of Science and Technology Politehnica Bucharest Bucharest Romania

ISBN: (数字)9798331532147

ISBN: (纸本)9798331532154

This paper reviews the problems encountered with data sets recorded by IoT monitoring networks and proposes five data healing methods. The five proposed methods include classic approaches but also methods based on artificial intelligence algorithms for predicting values. Using a case study based on indoor air quality research, the performances of the five methods of filling the gaps in the recorded data are explored both from the point of view of the ease of evaluation and visualization of the data and from the point of view of the statistical properties of the series of values.

关键词： Visualization Reviews Multiprocessor interconnection Data visualization Prediction algorithms Filling Artificial intelligence Monitoring Indoor air quality Biomedical engineering

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Person Recognition and Authenticity Through Facial Analysis Combining LSTM and Siamese Networks

Person Recognition and Authenticity Through Facial Analysis ...

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International Conference on control, Automation, Robotics and Vision (ICARCV)

作者： Ionel Gabriel Zahia Loretta Ichim Dan Popescu Faculty of Automatic Control and Computer Science National University of Science and Technology POLITEHNICA Bucharest Bucharest Romania

ISBN: (数字)9798331518493

ISBN: (纸本)9798331518509

The automatic recognition of real people is particularly important in many fields of activity. The article proposes a complex system for recognizing people taking into account possible fraud attacks. A Long Short-Term Memory neural network was used to detect possible frauds in the video sequences, and to recognize the person in the case after validation as a real person, two Siamese neural networks implemented with VGG 16 and ResNet 50 were tested. The obtained results were compared for Euclidean distance, Cosine distance, and for two training methods: Contrastive Loss and Triple Loss. The best results were obtained for VGG 16, Cosine distance, and Triple Loss.

关键词： Training Convolution Neural networks Video sequences Euclidean distance Fraud Convolutional neural networks Long short term memory Robots Identification of persons

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(POSTER) Visual Transformer Models on UAV-Captured Images for Person Detection

(POSTER) Visual Transformer Models on UAV-Captured Images fo...

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International Conference on Distributed Computing in Sensor Systems (DCOSS)

作者： Ionel - Gabriel Zahia Dan Popescu Loretta Ichim Faculty of Automatic Control and Computer Science National University of Science and Technology POLITEHNICA Bucharest Bucharest Romania

ISBN: (数字)9798350369441

ISBN: (纸本)9798350369458

One of the most important applications of UAVs is person detection for security or rescue tasks. The goal of the proposed paper is to develop, experiment, and compare the performance of two new neural networks based on the transformer architecture, Detection Transformer and Vision Transformer. Two datasets were used, an own one for testing and COCO for learning. The results are promising to take into account the difficulties of person detection at a distance.

关键词： Measurement computer vision Visualization Neural networks computer architecture Object detection Transformers

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Assessment of Machine Learning Techniques used for EEG based Pain Monitoring 23

Assessment of Machine Learning Techniques used for EEG based...

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23rd International Conference on control Systems and computer science Technologies, CSCS 2021

作者： Mirela, Riciu Ionela Hossu, Daniela Hossu, Andrei Faculty of Automatic Control and Computer Science Bucharest Romania

ISBN: (纸本)9781665439398

The purpose of this article is to provide an overview of research on the analysis and interpretation of electroencephalographic (EEG) signals, using automated artificial intelligence (AI) applications based on data mining and machine learning (ML) algorithms for detecting and diagnosing neurological disorders. In this study, we assessed the sensitivity of different algorithms and datasets classifying pain syndromes. Based on this evaluation, the SVM classification algorithm, considered the most suitable for EEG analysis, was applied in an experimental study that certifies its performance. © 2021 IEEE.

关键词： Data mining

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Network Management devices in an SDN environment 24

Network Management devices in an SDN environment

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24th International Conference on control Systems and computer science, CSCS 2023

作者： Hamad, Diyar Jamal Yalda, Khirota Gorgees Tapus, Nicolae Okumus, Ibrahim Taner Politehnica University of Bucharest Faculty of Automatic Control and Computer Science Bucharest Romania Erbil Polytechnic University Soran Technical College Erbil Iraq Computer Engineering Kahramanmaras Sutcu Imam University Kahramanmaras Turkey

ISBN: (纸本)9798350313390

Network optimization and continued availability depend on a number of capabilities that are part of network management. The Maintenance, operating and also offering a safeguarded interaction network is very complicated. It calls for the network operators to grapple with low-level vendor particular arrangements to execute the high degree network policies which are complicated. A method for monitoring networks with OpenFlow controller is presented in this paper in two separate functions for the same networks. Bandwidth utilization, Meter values, charts and statistics are provided by the method to extend controller monitoring capabilities. The method architecture and implementation will be introduced in order to present the feature set. Additionally, softswitches are used as a switch and Mininet to evaluate a virtualized network. This analysis shows whether Meters or ports value is better for network management. © 2023 IEEE.

关键词： Network management

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A Survey on Security Issues in Cloud Systems 22

A Survey on Security Issues in Cloud Systems

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22nd RoEduNet Conference: Networking in Education and Research, RoEduNet 2023

作者： Hamad, Diyar Jamal Yalda, Khirota Gorgees Tapus, Nicolae Okumus, Ibrahim Taner Politehnica University of Bucharest Faculty of Automatic Control and Computer Science Bucharest Romania Erbil Polytechnic University Soran Technical college Erbil Iraq Sutcu Imam University Computer Engineering Kahramanmaras Kahramanmaras Turkey

ISBN: (纸本)9798350393651

'The cloud' points out to servers, the databases and software that run on those servers. The Internet has always been constructed of infrastructure, servers and clients. Clients send their requests to servers, and servers reply, but cloud computing is distinct in the form that cloud servers are not just replying to requests with on-demand processing but they are saving data and running programs instead of the client. Cloud computing is a technology that is crossing a great expansion today. In cloud computing you can dynamically expand resources without knowledge of a new infrastructure, without developing new software or preparing new staff and to access such great technology the only things that are asked for are an Internet connection and an Internet browser. The goal of this survey is to present the different cloud security threats and recognize the proper security mechanism used to reduce them. © 2023 IEEE.

关键词： Cloud security

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MTP-GO: Graph-Based Probabilistic Multi-Agent Trajectory Prediction with Neural ODEs

IEEE Transactions on Intelligent Vehicles

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IEEE Transactions on Intelligent Vehicles 2023年第9期8卷 4223-4236页

作者： Westny, Theodor Oskarsson, Joel Olofsson, Bjorn Frisk, Erik Linköping University Department of Computer and Information Science Linköping581 83 Sweden Lund University Department of Automatic Control Lund221 00 Sweden Linköping University Department of Electrical Engineering Linköping581 83 Sweden

Enabling resilient autonomous motion planning requires robust predictions of surrounding road users' future behavior. In response to this need and the associated challenges, we introduce our model titled MTP-GO. The model encodes the scene using temporal graph neural networks to produce the inputs to an underlying motion model. The motion model is implemented using neural ordinary differential equations where the state-transition functions are learned with the rest of the model. Multimodal probabilistic predictions are obtained by combining the concept of mixture density networks and Kalman filtering. The results illustrate the predictive capabilities of the proposed model across various data sets, outperforming several state-of-the-art methods on a number of metrics. © 2016 IEEE.

关键词： Trajectories

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Decentralized Blockchain-based Platform for Managing and Issuing Academic Certificates

Decentralized Blockchain-based Platform for Managing and Iss...

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International Conference on System Theory, control, and Computing (ICSTCC)

作者： Ciocan Stefan-Robert Cristian Nicolae Butincu Department of Computer Science Faculty of Automatic Control and Computer Engineering "Gheorghe Asachi" Technical University of Iasi Romania

ISBN: (数字)9798350364293

ISBN: (纸本)9798350364309

This paper presents a blockchain-based platform for managing and issuing academic certificates that features security, transparency, non-repudiation and traceability. Relying on the security provided by Ethereum blockchain and using asymmetrical cryptography in certificate generation, combined with certificate revocation mechanisms, the proposed platform offers a reliable, decentralized and secure solution that can be used by academic institutions to streamline the management of academic certificates and reduce bureaucracy.

关键词： Smart contracts Non-repudiation Information age control systems Fraud Reliability Certification

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