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Cognitive, Green and Ubiquitous Computing (IC-CGU), International conference on

作者： Peddi Shyam Ganesh B. Srilekha Vukanti Sravanthi Department of ECE Siddhartha Institute of Technology & Sciences Telangana India

ISBN: (数字)9798350361780

ISBN: (纸本)9798350361797

The recent exponential surge in the number of vehicles on our roadways has made congestion and violations important problems. By automating traffic management using an ALPR system, we can improve access control systems, streamline traffic flow, and save time. Here, we look at how well algorithms for edge processing and morphological processing perform. The parameters of the neural network, including the regularisation parameter, the count of hidden layer units, and the count of iterations, are optimised with great care. With a focus on real-time implementation and control via a graphical user interface, this case presents a parking security system suitable for usage in office buildings, institutions, malls, etc. Operating on Raspberry Pi 2B and Matlab, the system accomplishes a 97% efficiency rate through the use of image processing techniques and machine learning algorithms.

关键词： Location awareness Machine learning algorithms image edge detection Neural networks Ubiquitous computing Real-time systems Character recognition

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Offline Reinforcement Learning via Sequence Modeling for Vision-Based Robotic Grasping 13

Offline Reinforcement Learning via Sequence Modeling for Vis...

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13th IEEE International conference on CYBER Technology in Automation, Control, and Intelligent systems, CYBER 2023

作者： Zeng, Sheng Sun, Xiao Chen, Kang Huang, Weibing Chen, Yi Chen, Dan Xu, Zhezhuang College of Electrical Engineering and Automation Key Laboratory of Industrial Automation Control Technology and Information Processing Fuzhou University Education Department of Fujian Province Fuzhou350000 China Evomotion Co. Ltd. Guangdong Shenzhen518000 China

ISBN: (纸本)9798350315196

High cost of environmental interaction and low data efficiency limit the development of reinforcement learning in robotic grasping. This paper proposes an end-to-end robotic grasping method based on offline reinforcement learning via sequence modeling. It considers the most recent n-step history to assist the agent in making decisions, where a predictive model learns to directly predict actions from raw image inputs. The experimental results show that our method can achieve higher grasping success rate with less training data than traditional reinforcement learning algorithms in offline setting. © 2023 IEEE.

关键词： Reinforcement learning

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An Effective image Encryption Algorithm Based on a Novel Chaotic Map 13

An Effective Image Encryption Algorithm Based on a Novel Cha...

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13th International conference on Graphics and image processing (ICGIP)

作者： Ding, Weikang Yang, Qinglian Zhao, Dongdong Yan, Shi Lanzhou Univ Sch Informat Sci & Engn Lanzhou 730000 Peoples R China

ISBN: (数字)9781510650435

ISBN: (纸本)9781510650435;9781510650428

Cryptography based on the properties such as unpredictability and initial state sensitivity of chaotic systems is a strategy to improve the security of image encryption algorithms. In this paper, a Logistic Coupled with Sine (LCS) chaotic map is proposed, and it turns out that the proposed map has more complex behaviors than existing chaotic maps in terms of performance analyses. Furthermore, as a potential application, an efficient and effective image encryption algorithm is proposed based on the keystreams generated by this LCS map. In the encryption algorithm, for a given plain image, it is split by the parity of indices of image rows first, and then a new confusion-diffusion strategy is proposed to scramble and diffuse thoroughly the elements of these two divided parts of the image. The security analyses indicate that the proposed encryption algorithm has excellent statistical properties, high security and efficiency for image encryption.

关键词： Information security image cryptography chaotic map security analyses

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Unrolling Alternating Direction Method of Multipliers for Visible and Infrared image Fusion 5

Unrolling Alternating Direction Method of Multipliers for Vi...

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5th IEEE International conference on image processing Applications and systems (IPAS)

作者： Bakan, Altug Erer, Isin Istanbul Tech Univ Dept Elect & Commun Engn Istanbul Turkey ASELSAN Microelect Guidance & Electroopt Business Sect Ankara Turkey

ISBN: (纸本)9781665462198

In this paper a new infrared and visible image fusion (IVIF) method which combines the advantages of optimization and deep learning based methods is proposed. This model takes the iterative solution used by the alternating direction method of the multiplier (ADMM) optimization method, and uses algorithm unrolling to obtain a high performance and efficient algorithm. Compared with traditional optimization methods, this model generates fusion with 99.6% improvement in terms of image fusion time, and compared with deep learning based algorithms, this model generates detailed fusion images with 99.1% improvement in terms of training time. Compared with the other state-of-the-art unrolling based methods, this model performs 26.7% better on average in terms of Average Gradient (AG), Cross Entropy (CE), Mutual Information (MI), Peak Signal-to-Noise Ratio (PSNR), and Structural Similarity Loss (SSIM) metrics with a minimal testing time cost.

关键词： visible and infrared image fusion algorithm unrolling model based deep network ADMM

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Data acquisition and data analysis in colorimetric sensor arrays

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CHEMOMETRICS AND INTELLIGENT LABORATORY systems 2023年 241卷

作者： Hemmateenejad, Bahram Bordbar, Mohammad Mahdi Shojaeifard, Zahra Shiraz Univ Chem Dept Shiraz Iran Shiraz Univ Med Sci Med & Nat Prod Chem Res Ctr Shiraz Iran

Responses in colorimetric sensor arrays are based on the monitoring color changes of chemical transducers by multichannel spectrophotometers or imaging recorders such as scanners, digital camera and smartphones. The images are then digitized using different image analysis algorithms. The array based methods provide a multidimensional data containing analytical, noise and outlier information. The inconsistent data can be removed or decreased by data pre-processing methods. Based on the goal of researches, the refined data can be processed by the pattern recognition methods for qualitative analysis or a by the multivariate regression models for quantitative analysis. This article explains (i) the mechanism of data collection using different types of readers, (ii) introduces the types and applications of algorithms and software for image digitalization, (iii) represents information about data preprocessing, variable selection and multivariate statistical methods and (iv) evaluates their applications in processing of colorimetric sensor array data published during the last decade.

关键词： Colorimetric sensor array Chemometrics image analysis Data acquisition Pre-processing

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Word Sense Disambiguation in the Biomedical Domain: Short Literature Review

Word Sense Disambiguation in the Biomedical Domain: Short ...

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International conference on Advanced Intelligent systems for Sustainable Development, AI2SD 2022

作者： El Hannaoui, Oumayma Nfaoui, El Habib El Haoussi, Fatima LISAC Laboratory Faculty of Sciences Dhar EL Mahraz Sidi Mohamed Ben Abdellah University Fez Morocco

ISBN: (纸本)9783031352478

Word Sense Disambiguation (WSD) is a subfield of Natural Language processing that discerns which meaning of a given term is used in a specific context. Exclusively in the biomedical domain, automatic processing of medical documents containing biomolecular entities, diseases, proteins, and genes, for instance, is summoning namely because many of the terminologies are ambiguous. Word Sense Disambiguation algorithms work mainly on identifying the correct sense of a given vague word in its specific context. This paper runs through the existing methods and datasets in WSD in the biomedical domain. Various methods were applied in this endeavour ranging from knowledge based methods to supervised and unsupervised machine learning methods, applied to different types of datasets such as PubMed and PubMed Central, MIMIC iii, Medline, etc. The main findings in our study include the following: (i)The lack of large testing datasets containing medical ambiguities available for public use limited the application of WSD in the biomedical domain. (ii)Whilst the unsupervised methods rely mainly on the UMLS Metathesaurus and can be applied widely, the restricted use of a manually annotated dataset containing both ambiguous words and their definitions, along with supervised learning methods, have given promising results in terms of providing the best definition for the given entity. (iii)Automatic analysis of massive health related corpora would be liable to err without accurate word sense disambiguation approaches. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Natural language processing systems

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3rd International conference on Innovation in Engineering, ICIE 2024

3rd International Conference on Innovation in Engineering, I...

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3rd International conference on Innovation in Engineering, ICIE 2024

ISBN: (纸本)9783031615818

The proceedings contain 108 papers. The special focus in this conference is on Innovation in Engineering. The topics include: Transmission Power Based Congestion Control Using Q-Learning Algorithm in Vehicular Ad Hoc Networks (VANET);collaborative Robot Laboratory Setup for Repeatable Force and Speed Experiments;towards Global Sustainability: Exploratory Analysis Through Unsupervised Machine Learning Techniques;structural Kinematic Analysis of a Wheelchair Mechanism Designed for Disabled Persons;application of Graph Theory in Designing the Communication System of a Robotic Production Cell;machine Learning algorithms in Scheduling Problems: An Overview and Future Paths;on the Relation Between the Smith Predictor and Algebraic Control Approach for Time Delay systems: A Case Study;image as a Way of processing Multidimensional Production Data for Product Quality Prediction Using Deep Learning;OPC-UA in Digital Twins—A Performance Comparative Analysis;design Improvements for an Inspection Rover;decoding the Effect of Descriptive Statistics on Informed Decision-Making;Simulation Control of Three-Tank-System Using 2DOF Controller;development of a Serious Game to Support Alzheimer’s Patients: First Insights;e-voting Platform Based on Blockchain;the Transformation of Maintenance with the Arise of Industry 4.0;real-World Comparison of Predictive Controllers Based on Internal and External Description of the Controlled System;the Use of Virtual Reality in Lower-Limb Robotic Rehabilitation;the Contribution of Photovoltaic systems to Sustainable Agriculture—An Analysis of Agrivoltaic systems;integration of Augmented Reality and IoT Elements in the Maintenance 4.0;A Fuzzy Logic-Based Risk Assessment Tool for IT Startups;wireless Localization System Applied to a Kitting Pick-to-light System;Posture Correction Device Based on IMU Sensors and CNN.

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3rd International conference on Innovation in Engineering, ICIE 2024

3rd International Conference on Innovation in Engineering, I...

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3rd International conference on Innovation in Engineering, ICIE 2024

ISBN: (纸本)9783031615740

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3rd International conference on Innovation in Engineering, ICIE 2024

3rd International Conference on Innovation in Engineering, I...

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3rd International conference on Innovation in Engineering, ICIE 2024

ISBN: (纸本)9783031626838

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MetaMorph: Learning Metamorphic image Transformation with Appearance Changes 28th

MetaMorph: Learning Metamorphic Image Transformation with Ap...

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28th International conference on Information processing in Medical Imaging (IPMI)

作者： Wang, Jian Xing, Jiarui Druzgal, Jason Wells, William M., iii Zhang, Miaomiao Univ Virginia Comp Sci Charlottesville VA 22908 USA Univ Virginia Elect & Comp Engn Charlottesville VA USA Univ Virginia Radiol & Med Imaging Charlottesville VA USA Harvard Med Sch Brigham & Womens Hosp Boston MA 02115 USA MIT Comp Sci & Artificial Intelligence Lab Cambridge MA USA

ISBN: (纸本)9783031340475;9783031340482

This paper presents a novel predictive model, MetaMorph, for metamorphic registration of images with appearance changes (i.e., caused by brain tumors). In contrast to previous learning-based registration methods that have little or no control over appearance-changes, our model introduces a new regularization that can effectively suppress the negative effects of appearance changing areas. In particular, we develop a piecewise regularization on the tangent space of diffeomorphic transformations (also known as initial velocity fields) via learned segmentation maps of abnormal regions. The geometric transformation and appearance changes are treated as joint tasks that are mutually beneficial. Our model MetaMorph is more robust and accurate when searching for an optimal registration solution under the guidance of segmentation, which in turn improves the segmentation performance by providing appropriately augmented training labels. We validate MetaMorph on real 3D human brain tumor magnetic resonance imaging (MRI) scans. Experimental results show that our model outperforms the state-of-the-art learning-based registration models. The proposed MetaMorph has great potential in various image-guided clinical interventions, e.g., real-time image-guided navigation systems for tumor removal surgery.

关键词： Tumors

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