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A Combined Method for Face Recognition

A Combined Method for Face Recognition

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international conference on Information and Computer Technologies (ICICT)

作者： Laura Mukhamadiyeva Aiman Moldagulova Information Systems International University of Information Technologies Almaty Kazakhstan Software Engineering Satbayev University Almaty Kazakhstan

Nowadays face recognition methods are in great interest of computer vision area. the development of a face recognition method that provides a high level of reliability of the solution in the absence of restrictions on the source image is a very crucial task. the paper deals with analysis of existing algorithms for recognizing the geometric characteristics of the face. As a result a combined method for identifying the face was developed. the main goal of this paper is to develop methods for recognizing and detecting faces that increase the reliability of identification of objects of analysis, reduce the level of false recognition, reduce the training time of the classifier and the time of preliminary processing and recognition of the image.

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Emotionally Intelligent Robots: Advancements in Social and Cognitive computing Towards Improving Human-Robot Interaction In Space 74

Emotionally Intelligent Robots: Advancements in Social and C...

引用

74th international Astronautical Congress, IAC 2023

作者： Tng, Faith Space Generation Advisory Council c/o ESPI Schwarzenbergplatz 6 Vienna1030 Austria

With several upcoming long-duration crewed space missions, robots that have emotional intelligence capabilities are becoming increasingly critical in supporting the well-being and performance of astronauts. Long-duration space missions subject astronauts to the effects of isolation, confinement, and exposure to extreme environments, which could take a toll on their mental health and affect crew cohesion. Emotionally-intelligent robots can mitigate these physical and psychological stresses, with social and cognitive computing (SCC) advancements providing promising avenues for achieving improved human-robot interaction (HRI) in space. For example, the social space robot Crew Interactive Mobile Companion (CIMON) uses SCC techniques to facilitate natural language communication in order to interpret voice commands, understand context, and respond appropriately to astronauts. SCC techniques already play a significant role in influencing emotionally-intelligent robots on Earth. SCC involves analyzing social behaviors and interactions to help artificial intelligence (AI) systems recognise emotional cues, and uses machine learning (ML) algorithms and natural language processing (NLP) to understand the context of emotional expressions in order to respond appropriately. When applied to space settings, emotionally-intelligent robots have the potential to provide emotional support, companionship and cognitive simulation to astronauts, as well as better support crew interactions, decision-making and assistance in carrying out missions. Emotionally-intelligent robots on Earth that use underlying SCC techniques have shown to provide comfort and companionship, mental stimulation, possess the ability to support decision-making and even reduce pain perception. However, there is not much research around emotionally-intelligent robots in space or the computing techniques behind them, with most research on HRI in space exploration covering the engineering aspects. this paper reviews exis

关键词： robotic intelligence social robotics in space space psychology space robot assistants

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8th international conference on Mathematical Aspects of Computer and Information Sciences, MACIS 2019

8th International Conference on Mathematical Aspects of Comp...

引用

8th international conference on Mathematical Aspects of Computer and Information Sciences, MACIS 2019

ISBN: (纸本)9783030431198

the proceedings contain 36 papers. the special focus in this conference is on Mathematical Aspects of Computer and Information Sciences. the topics include: Reliable Computation of the Singularities of the Projection in R3 of a Generic Surface of R4;LaserTank is NP-Complete;A Parallel GPU Implementation of SWIFFTX;new Practical Advances in Polynomial Root Clustering;certified Hermite Matrices from Approximate Roots - Univariate Case;preface;Comprehensive LU Factors of Polynomial Matrices;generalized Integral Dependence Relations;evaluation of Chebyshev Polynomials on Intervals and Application to Root Finding;DD-Finite Functions Implemented in Sage;an Overview of Geometry Plus Simulation Modules;authorship Attribution by Functional Discriminant Analysis;common Vector Approach Based Image Gradients Computation for Edge Detection;optimal Transport to a Variety;a Numerical Efficiency Analysis of a Common Ancestor Condition;improved Cross-Validation for Classifiers that Make Algorithmic Choices to Minimise Runtime Without Compromising Output Correctness;a Fast Counting Method for 6-Motifs with Low Connectivity;IPO-Q: A Quantum-Inspired Approach to the IPO Strategy Used in CA Generation;second Order Balance Property on Christoffel Words;edge-Critical Equimatchable Bipartite Graphs;on a Weighted Spin of the Lebesgue Identity;on Parametric Border Bases;computing an Invariant of a Linear Code;acceleration of Spatial Correlation Based Hardware Trojan Detection Using Shared Grids Ratio;algebraic Analysis of Bifurcations and Chaos for Discrete Dynamical systems;automatic Synthesis of Merging and Inserting algorithms on Binary Trees Using Multisets in theorema;on the Chordality of Simple Decomposition in Top-Down Style;CUR LRA at Sublinear Cost Based on Volume Maximization.

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Underwater Image Enhancement Based on Shallow Underwater Neural Network

Underwater Image Enhancement Based on Shallow Underwater Neu...

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Pattern Recognition and Artificial Intelligence (PRAI), international conference on

作者： Tianyi Lv Wenhui Yu Guangchao Rui Haijie Jia Jun Jiang Xiang Zhang Sixth Research Office Zheng Zhou Electromechanical Engineering Research Institute Zhengzhou China Sixth Research Office 713th Research Institute of China State Shipbuilding Corporation Limited Zhengzhou China

In recent years, due to the importance of underwater image enhancement in underwater robot, underwater vehicle and ocean engineering, more and more extensive research has been done. It has evolved from implementing physics-based solutions to using very cutting edge cnn and GANs. However, these cutting-edge algorithms often come at the cost of high computing power and time, which reduces the efficiency and portability of underwater working equipment using these algorithms. At the same time, these models have harsh requirements on data sets, leading to high cost of training and unfriendly to many underwater operations. therefore, this paper aims to propose a lightweight neural network structure, Shallow underwater neural network. these neural networks associate the original image directly with the output of each convolutional layer, preserving the original features while enhancing the image and avoiding gradient descent. the experimental results show that the model has a good effect on image enhancement, and the structure is lightweight.

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Automated Bone Age Assessment Using Deep Learning with Attention Module 6th

Automated Bone Age Assessment Using Deep Learning with Atte...

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6th international conference on Intelligent computing and Optimization, ICO 2023

作者： Fahmida, Maisha Khaliluzzaman, Md. Hossain, Syed Md. Minhaz Deb, Kaushik Chattogram4349 Bangladesh Department of Computer Science and Engineering International Islamic University Chittagong Chattogram4318 Bangladesh Department of Computer Science and Engineering Premier University Chattogram4000 Bangladesh

ISBN: (纸本)9783031503269

Bone age assessment (BAA) based on the hand X-ray image is used by the pediatric for measuring the growth of children, predicting their final height and also diagnosing some diseases. Beside this, it may be used for forensic, sports and other legal purposes. the conventional manual approach, however, takes considerable time and is prone to obverse fluctuation. this study proposes an end-to-end BAA method based on the concept of Convolutional Neural Network (CNN). the proposed model contains three separate module: transferred InceptionV3 module, an attention module, and a regression module. Initially, pretrained InceptionV3 model is used to serve the purpose of initialization. then four different attention module: channel attention, spatial attention, squeeze and excitation attention, and channel attention with spatial attention are used separately at the end of the InceptionV3 module in order to choose the best module for bone age assessment purpose. Attention module is used to put emphasis on the most important features to escalate the performance of the proposed model. Finally, regression module is introduced to estimate the bone age. the experiment of the model with squeeze and excitation attention on Digital Hand Atlas (DHA) dataset reveals that the model overcomes baseline models performance. © 2023, the Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Deep learning

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Identifying Categories of Domain Names by Using Deep Learning Methods

Identifying Categories of Domain Names by Using Deep Learnin...

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2022 international conference on Machine Learning, Cloud computing and Intelligent Mining, MLCCIM 2022

作者： Zhang, Zhenzhong Su, Majing Bao, Zhenjing Liu, Xudong Yao, Yun Su, Shen 6th Research Institute of China Electronic Corporations School of Computer Science and Technology Xidian University Xi'an China 6th Research Institute of China Electronic Corporations Beijing China Cyberspace Institute of Advanced Technology Guangzhou University Guangzhou China

ISBN: (数字)9781665498586

ISBN: (纸本)9781665498586

In recent years, the dramatic increase in the number of domain names has made it more difficult to accurately index and search web pages. An emerging method is to classify webpages according to various features of webpages, the server can accurately locate the search items according to the classification results during retrieval, and filter irrelevant or malicious domain name recommendations. Identifying the category of a domain name by just the URL is not accurate enough because of confusing domain names used by the malicious or irrelevant web pages. In this paper, we implement the task of domain names classification based on a group of features of domain names, including URL, title, description, content, and their combinations. Different from previous work, we not only pay attention to the scene of domain names but also focus on the categories according to their industries. We take four categories of banking, government, education, and transportation as examples to eximine effects of the selected domain name features. We constructed a dataset of five categories including the rejection class. We implement and fine-tune four deep learning models(BERT, RoBERTa, BERT-CNN and BERT-RNN) for the classification tasks on the dataset, and then we experiment with each model using different feature combinations as input, and compare the accuracy of the classification results. According to the results, we observe that with the combined features of URL and content as input, each model can achieve higher classification accuracy, with the highest classification accuracy reaching 94.78% © 2022 IEEE.

关键词： Websites

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Efficient evaluation of cryptographic solutions in IoT systems 9

Efficient evaluation of cryptographic solutions in IoT syste...

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9th international conference on Digital Technologies in Education, Science and Industry, DTESI 2024

作者： Temirbekova, Zhanerke Abdiakhmetova, Zukhra Tynymbayev, Sakhybay Bekaulova, Zhansaya Al-Farabi Kazakh National University al-Farabi71/10 Astana Almaty050035 Kazakhstan International Information Technology University 34/1 Manas St. Almaty050000 Kazakhstan

Selecting cryptographic algorithms for Internet of things (IoT) devices is a critical process as it directly impacts the security, performance, and viability of these devices. When selecting cryptographic algorithms for IoT devices, many factors need to be taken into account, the central ones being computing power, memory usage, and power consumption. the optimal choice of algorithms can significantly improve the security of devices while maintaining their performance and energy efficiency. Balancing these factors is the key to successfully integrating cryptography into the IoT ecosystem. the research paper evaluates the effectiveness of cryptographic solutions, compares and analyzes their performance, power consumption, security, and other parameters. As a result, optimal algorithms are selected that meet the requirements of the IoT system and provide effective protection. © 2023 Copyright for this paper by its authors.

关键词： Energy utilization

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Drivers and Barriers for Going Paperless in Tertiary Educational Institute 6th

Drivers and Barriers for Going Paperless in Tertiary Educati...

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6th international conference on Intelligent computing and Optimization, ICO 2023

作者： Haque, Rafid Mahmud Maha, Lamyea Tasneem Rahman, Oshin Nusrat Safa, Noor Fabi Shah Tuhin, Rashedul Amin Reza, Ahmed Wasif Arein, Mohammad Shamsul Department of Computer Science and Engineering East West University Dhaka Bangladesh Department of CSE Daffodil International University Dhaka Bangladesh Department of CSE Chittagong University of Engineering and Technology Chattogram Bangladesh

ISBN: (纸本)9783031501579

Tertiary educational institutes especially universities have become one of the major consumers of paper. Since paper uses natural resources and energy, universities are being encouraged to turn processes paperless. However, there are certain barriers along with drivers which lead to turning processes paperless. Although some work has been done on similar work, most of these works are not from Bangladesh’s perspective and do not show as-is or to-be models of processes. this paper presents the current scenario of paperless initiatives, the impact of going paperless, and the driving forces and barriers to making processes paperless. Due to limitations in time and resources, only personnel working at East West University were interviewed for this qualitative study. To analyze the data from the interviews, the ‘Gap Analysis’ method. the interview data was then used to build as-is and to-be models for two processes at East West University which are not yet paperless. the drivers and barriers to these processes turning paperless were also explored. Going paperless not only reduces paper usage, but also reduces manpower, physical storage space, and time needed to maintain the processes. However, barriers specific to different processes still remain which include but are not limited to fear of data center failure and transparency maintenance. © 2023, the Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Digital storage

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6th IEEE international conference on "Smart Structures and systems", ICSSS 2019

6th IEEE International Conference on "Smart Structures and S...

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6th IEEE international conference on "Smart Structures and systems", ICSSS 2019

ISBN: (纸本)9781728100272

the proceedings contain 32 papers. the topics discussed include: a comparative study of inverters for three phase induction motor drives to mitigate voltage sag;novel scheme for wide area oscillation control with signal latency compensation;octagonal N-antenna for space research applications;an optimistic approach to interpret the DDoS attacks by wielding deterministic packet marking;sequencing of modules and prioritization of test cases using dependency structure matrix: survey;house resale price prediction using classification algorithms;an automatic localization of microaneurysms in retinal fundus images;energy conservative mobile sink path routing for wireless sensor networks;automatic electricity bill calculation using Arduino;a novel hidden camera destroyer to avoid un-lawful activity;and identification of autism in MR brain images using deep learning networks.

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Fun with FUN 11

Fun with FUN

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11th international conference on Fun with algorithms, FUN 2022

作者： Mathieu, Fabien Tixeuil, Sébastien Swapcard Paris France Sorbonne Université CNRS LIP6 Paris France

ISBN: (纸本)9783959772327

the notions of scientific community and research field are central elements for researchers and the articles they publish. We propose to explore the evolution of the FUN conference community since its creation from the articles listed in DBLP, authors, program committees, and advertised themes, by means of a novel symmetric embedding, and carefully crafted software tools. Our results make it possible on the one hand to better understand the evolution of the community, and on the other hand to easily integrate new themes or researchers during future editions. © Fabien Mathieu and Sébastien Tixeuil.

关键词： Natural language processing systems

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