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27th International Conference on Pattern Recognition, ICPR 2024

作者： Su, Yang Tan, ShunQuan Huang, Jiwu College of Information Engineering Shenzhen University Shenzhen China Shenzhen Institute of Artificial Intelligence and Robotics for Society Shenzhen China College of Computer Science and Software Engineering Shenzhen University Shenzhen China

ISBN: (纸本)9783031783111

Surveillance videos play a crucial role in providing evidences. However, the deletion of even a few frames can significantly impact the interpretation of events, while the deletion can be performed easily using video editing softwares without leaving visual traces. This paper introduces a novel method to detect video frame deletion based on velocity field characteristics. The main idea is to convert long videos into a feature sequence, which appears as a sequence containing outlier values for videos with frame deletions, and as a sequence without outlier values for original videos. The proposed approach employs a siamese network to distinguish frame deletions between adjacent frames. A video can be transformed into a feature sequence through the siamese network, and the resulting sequence is fed into a binary classifier for final classification. Experimental results demonstrate the effectiveness of our proposed approach, even for longer videos (e.g., 2000 frames) with minimal frame deletions (e.g., 1 frame). © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Digital forensics

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Recognition of the emotional state of energy facilities operators based on artificial immune systems 4

Recognition of the emotional state of energy facilities oper...

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4th International Conference on Applied Physics, Information Technologies and Engineering 2022, APITECH 2022

作者： Nuriakhmetov, A.I. Bogdanova, D.R. Yusupova, N.I. Faculty of Computer Science and Robotics Ufa State Aviation Technical University Ufa450077 Russia

This research paper presents results on the construction of a system for recognizing emotional state of energy facilities operators by the expression of their faces in the images. The model uses one of the algorithms of artificial immune systems as a classifier. An artificial immune system is a concept that contains methods and algorithms that try to apply the basic mechanisms of biological immune system to solve various practical problems. In accordance with the main aim of the research, the article deals with existing concepts of emotion classification as well as current methods for recognizing emotions from facial expressions in images. Also, a brief review of the literature is given in accordance with the questions posed. The proposed model uses a feature extraction approach based on marking the human face with 68 points, followed by extraction of their coordinates. For the obtained coordinates, a new special technique for their processing for subsequent classification is proposed. The built model is able to classify the 7 basic Ekman emotions both on images and in the video stream, with an accuracy of about 80%. © Published under licence by IOP Publishing Ltd.

关键词： Extraction

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Text-Guided Image Generation for Railway Intrusion Anomaly Detection

Text-Guided Image Generation for Railway Intrusion Anomaly D...

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2023 IEEE International Conference on Unmanned Systems, ICUS 2023

作者： Chen, Jinghang Zhang, Chi Feng, Xiaodan Liu, Yuehu Institute of Artificial Intelligence and Robotics Xi'an Jiaotong University Xi'an China School of Computer Science and Technology Xi'an Jiaotong University Xi'an China

ISBN: (纸本)9798350316308

Railway intrusion are characterized by strong suddenness, high unpredictability and many disturbing factors, which are key factors affecting railway safety. Currently, the deep neural network-based intrusion object detection algorithm relies on the diversity of training data. However, the data of railway intrusion image is scarce and difficult to obtain. Existing image generation methods face the problem of insufficient realism in the generated images and difficulty in generating large amounts of data. We aim to explore a text-guided image data generation framework for specific visual tasks by using an existing large language model combined with a text-to-image diffusion model. In this paper, we construct a framework for railway intrusion image generation guided by textual prompts and build a dataset of railway intrusion images based on this framework. The dataset generated in this paper contains a wide range of intrusion images and includes a variety of environmental factors such as weather and time, which provides better diversity than existing datasets. The evaluation results show that the intrusion images generated in this paper have high quality and realism. © 2023 IEEE.

关键词： Deep neural networks

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Uncertainty propagation in the internet of things

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Discover Internet of Things 2024年第1期4卷 1-20页

作者： Pal, Shantanu Khalifa, Sara Miller, Dimity Dedeoglu, Volkan Dorri, Ali Ramachandran, Gowri Moghadam, Peyman Kusy, Brano Jurdak, Raja The School of Information Technology Faculty of Science Engineering and Built Environment Deakin University MelbourneVIC 3125 Australia The School of Information Systems Faculty of Science Queensland University of Technology BrisbaneQLD4000 Australia The School of Electrical Engineering and Robotics Faculty of Engineering Queensland University of Technology BrisbaneQLD4000 Australia The Distributed Sensing Systems Group Data61 CSIRO PullenvaleQLD 4069 Australia The School of Computer Science Faculty of Science Queensland University of Technology BrisbaneQLD 4000 Australia The CSIRO Robotics Data61 CSIRO PullenvaleQLD 4069 Australia

The Internet of Things (IoT) detects context through sensors capturing data from dynamic physical environments, in order to inform automation decisions within cyber physical systems (CPS). Diverse types of uncertainty in the IoT pipeline can propagate within and across nodes, involving complex interactions with security, privacy, and trust that remain largely unexplored. This paper conducts an in-depth analysis of the types of uncertainties in IoT and how they propagate within IoT nodes and networks. We consider adversarial uncertainty in the context of distributed IoT networks to capture perturbations due to malicious actors in the network that can influence IoT security, privacy and trust. We examine the propagation of adversarial uncertainty and well-known uncertainty types, namely aleatoric and epistemic uncertainty, within the five distinct stages of sensing, communication, storage, processing and decision-making in an IoT pipeline, across network layer boundaries, and across nodes within an IoT network. Using this mapping, we analyse the interactions between the uncertainty types and their propagation, and security, privacy, and trust in IoT. Based on this analysis, we discuss guidelines and considerations for mitigating uncertainty in IoT through a smart grid use case study. © The Author(s) 2024.

关键词： Differential privacy

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Lighting the Smart Way: A Technological Odyssey in Urban Street Illumination 10

Lighting the Smart Way: A Technological Odyssey in Urban Str...

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10th International Conference on Advanced Computing and Communication Systems, ICACCS 2024

作者： Vinu, M.S. Priya, P Kanaga Thilakaveni, P. Hermina, J. M. Ashforn Prashanthini, K. Misba, M. Nehru Institute of Engineering and Technology Department of Computer Science and Engineering Coimbatore India Kpr Institute of Engineering and Technology Department of Computer Science and Engineering Coimbatore India Psg Polytechnic College Department of Computer Engineering Coimbatore India Bannari Amman Institute of Technology Department of Artificial Intelligence and Data Science Erode India Sri Ramakrishna Engineering College Department of Robotics and Automation Coimbatore India Bethlahem Institute of Engineering Department of Computer Science and Engineering Nagercoil Karungal India

ISBN: (纸本)9798350384369

The development of intelligent street light systems has ushered in a new era of efficiency and sustainability in urban infrastructure. The proposed work studies the integration of modern sensors and Internet of Things (IoT) technologies to increase the functionality of street lights. The major components include Light Dependent Resistors (LDR) for automatic light management, an MQ135 sensor for air quality monitoring, and a fog detection system employing a laser module and LDR. These sensors are integrated with the ESP8266, providing cloud integration for real-time data visualization and monitoring. Additionally, solar panels are employed to enhance energy efficiency. The proposed methodology digs into the precise implementation, data analysis, and the potential of this system to alter urban lighting infrastructure © 2024 IEEE.

关键词： Air quality

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Optimization of the Storage Location Assignment Problem Using Nested Annealing 12th

Optimization of the Storage Location Assignment Problem Us...

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11th and 12th International Conferences on Operations Research and Enterprise Systems, ICORES 2022 and 2023

作者： Oxenstierna, Johan van Rensburg, Louis Janse Stuckey, Peter J. Krueger, Volker Department of Computer Science Lund University Lund Sweden Faculty of Information Technology Monash University Melbourne Australia Flux Robotics Caltowie Australia Kairos Logic AB Lund Sweden

ISBN: (纸本)9783031496615

The Storage Location Assignment Problem (SLAP) has a significant impact on the efficiency of warehouse operations. We propose a multi-phase optimizer for the SLAP, where the quality of an assignment is based on distance estimates of future-forecasted order-picking. Candidate assignments are first sampled using a Markov Chain accept/reject method. Order-picking Traveling Salesman Problems (TSPs) are then modified according to the assignments and solved. The model is graph-based and generalizes to any obstacle layout in two dimensions. We investigate whether optimization speed-ups are possible using methods such as cost approximation, rejection of samples with low approximate cost and restarts from local minima. Results demonstrate that these methods improve performance, with total travel-cost reductions of up to 30% within 8 h of CPU-time. We share a public repository with SLAP instances and corresponding benchmark results on the generalizable TSPLIB format. © 2024, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Hamming distance

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Towards Single Point Incremental Forming Accuracy: An Approach for the Springback Effect Compensation 19

Towards Single Point Incremental Forming Accuracy: An Approa...

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19th IEEE International Conference on Automation science and Engineering, CASE 2023

作者： Shaker, Walid K. Klimchik, Alexandr Institute of Robotics and Computer Vision Innopolis University Republic of Tatarstan 420500 Russia School of Computer Science University of Lincoln LincolnLN6 7TS United Kingdom

ISBN: (纸本)9798350320695

The springback effect is a common occurrence in incremental forming, where the formed workpiece elastically deforms and slightly shifts from the desired shape after the tool is released. This phenomenon causes an error between the target and obtained shape, leading to reduced geometric accuracy. It is is a significant challenge in incremental forming and it is a reason why the process has lower accuracy compared to conventional forming methods. This paper presents an off-line springback effect compensation model aiming to generate an optimized toolpath that accounts for the material springback effect. The model is based on an off-line numerical simulation conducted on Abaqus/CAE software. The results demonstrated that the proposed model can effectively reduce the error between the desired and obtained shape by 31.8% for aluminum, 63.2% for copper, and 63.1 % for magnesium. © 2023 IEEE.

关键词： ABAQUS

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A Vision-Based Autonomous AI Tic-Tac-Toe Manipulation System 12

A Vision-Based Autonomous AI Tic-Tac-Toe Manipulation System

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12th International Electrical Engineering Congress, iEECON 2024

作者： Rakprayoon, Panjawee Ounsiri, Akechai Chongyoa, Ratchanon Bangkok University Faculty Of Engineering Dept. Ai Engineering And Data Science Pathum Thani Thailand Dna Robotics And Automation System Company Limited Pathum Thani Thailand Bangkok University Faculty Of Engineering Dept. Computer And Robotics Engineering Pathum Thani Thailand

ISBN: (纸本)9798350383591

For an AI tic-tac-toe manipulator application, a real-time vision-based approach is proposed. The technique employs the RealSense camera to capture color and depth images. Combining object detection and image processing techniques to identify X's and O's positions on the game board. However, we recognize that errors can occur during object movement when using only 2D images. To solve this problem, a calibration method between RealSense and the manipulator based on the point-to-plane ICP algorithm is presented. This method provides the 3D object position in the robot coordinate, resulting in increasing the accuracy from 86.25% to 97.25%. Our experiment shows that this technique is highly effective and can accurately identify position objects. © 2024 IEEE.

关键词： Object detection

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Deep Compliant Control for Legged Robots

Deep Compliant Control for Legged Robots

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IEEE International Conference on robotics and Automation (ICRA)

作者： Adrian Hartmann Dongho Kang Fatemeh Zargarbashi Miguel Zamora Stelian Coros Computational Robotics Lab in the Department of Computer Science ETH Zurich Switzerland

ISBN: (数字)9798350384574

ISBN: (纸本)9798350384581

Control policies trained using deep reinforcement learning often generate stiff, high-frequency motions in response to unexpected disturbances. To promote more natural and compliant balance recovery strategies, we propose a simple modification to the typical reinforcement learning training process. Our key insight is that stiff responses to perturbations are due to an agent’s incentive to maximize task rewards at all times, even as perturbations are being applied. As an alternative, we introduce an explicit recovery stage where tracking rewards are given irrespective of the motions generated by the control policy. This allows agents a chance to gradually recover from disturbances before attempting to carry out their main tasks. Through an in-depth analysis, we highlight both the compliant nature of the resulting control policies, as well as the benefits that compliance brings to legged locomotion. In our simulation and hardware experiments, the compliant policy achieves more robust, energy-efficient, and safe interactions with the environment.

关键词： Training Legged locomotion Uncertainty Tracking Perturbation methods Process control Energy efficiency

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Retrospective of Kazakh-Russian Sign Language Corpus Formation 11

Retrospective of Kazakh-Russian Sign Language Corpus Formati...

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11th Workshop on the Representation and Processing of Sign Languages: Evaluation of Sign Language Resources, sign-lang@LREC-COLING 2024

作者： Imashev, Alfarabi Kydyrbekova, Aigerim Mukushev, Medet Sandygulova, Anara Islam, Shynggys Israilov, Khassan Makazhanov, Aibek Yessenbayev, Zhandos Department of Robotics Engineering Nazarbayev University Kazakhstan Computer Science Lab National Laboratory Astana Nazarbayev University Kazakhstan Public Association "Kazakh Deaf Society" Astana Branch Kazakhstan

ISBN: (纸本)9782493814302

Sign language (SL) is a mode of communication that, in most cases, relies on visual perception exclusively and uses the visual-gestural modality. The advent of machine learning techniques has expanded the range of potential applications, not only in industry but also in addressing societal needs. Previous research has already demonstrated encouraging outcomes in developing sign language recognition systems that are both quite accurate and resilient. Nevertheless, the effectiveness and use of algorithms are impacted not only by their accessibility but also, at times to a greater extent, by the presence of substantial quantities of pertinent data. At the start of the local sign language corpus collection in 2015, there was a notable deficit of local Kazakh-Russian Sign Language data available for computer vision and machine-learning tasks. There were already corpora of another lexically close language, Russian Sign Language, but they were aimed at and tailored for lingustic research. We initiated the procedure by collecting data appropriate for machine-learning purposes. The subsets have been incorporated into the principal corpus and will be subject to future enhancements and refinements. This paper provides an overview of the collected components of the Kazakh-Russian Sign Language Corpus and the resulting outcomes derived from them. © 2024 ELRA Language Resources Association: CC BY-NC 4.0.

关键词： Machine learning

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