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Smart-Tree: Neural Medial Axis Approximation of Point Clouds for 3D Tree Skeletonization 11th

Smart-Tree: Neural Medial Axis Approximation of Point Cloud...

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11th iberian conference on pattern recognition and image analysis, IbPRIA 2023

作者： Dobbs, Harry Batchelor, Oliver Green, Richard Atlas, James UC Vision Research Lab University of Canterbury Christchurch8041 New Zealand

ISBN: (纸本)9783031366154

This paper introduces Smart-Tree, a supervised method for approximating the medial axes of branch skeletons from a tree point cloud. Smart-Tree uses a sparse voxel convolutional neural network to extract the radius and direction towards the medial axis of each input point. A greedy algorithm performs robust skeletonization using the estimated medial axis. Our proposed method provides robustness to complex tree structures and improves fidelity when dealing with self-occlusions, complex geometry, touching branches, and varying point densities. We evaluate Smart-Tree using a multi-species synthetic tree dataset and perform qualitative analysis on a real-world tree point cloud. Our experimentation with synthetic and real-world datasets demonstrates the robustness of our approach over the current state-of-the-art method. The dataset (https://***/uc-vision/synthetic-trees ) and source code (https://***/uc-vision/smart-tree ) are publicly available. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Trees (mathematics)

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Deformation Behaviour of Soil with Geocell Using image analysis Techniques 3rd

Deformation Behaviour of Soil with Geocell Using Image Analy...

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3rd International conference on Recent Trends in image Processing and pattern recognition, RTIP2R 2020

作者： Mane, Abhinav Gaikwad, Praful Shete, Shubham CSMSS Chh. Shahu College of Engineering Aurangabad Maharashtra431008 India Vatsalya Consulting Services Harsul Aurangabad Maharashtra431008 India

ISBN: (纸本)9789811604928

Geocell is being used very conveniently for soil reinforcement and slope protection in the recent times. The main advantage of this synthetic material is provision of the confinement to the soil resulting in the higher resistance to shear failure of the soil. Geocell is a three-dimensional synthetic material having the varying wall thickness and opening sizes. The use of the confining properties of the geocell is needed to be investigated in the application of bearing capacity improvement of soil below the foundations. The present work demonstrates bearing capacity improvement of the soil using geocell as the confining reinforcement. A series of experimental model tests is performed in the present study with constant soil type (sand). Parameters considered for variation was the width (W), opening size (og) and height (hg) of the geocell. The image analysis was performed mainly in imageJ which is available on free license program with Digital image Correlation and the Particle image Velocimetry approach. The observations were made mainly in terms of maximum load carried by the subsoil and the depth of Rankine’s zone obtained due to placement of geocell. Load bearing resistance of subsoil was in proportion with the width and height and in inverse proportion with the opening size of the geocell. The Rankine’s zone also observed to shift downward due to geocell inclusion providing more shear surface and thus higher bearing capacity. Thus, the geocell may successfully be utilized below shallow foundations to obtain higher Safe Bearing Capacities. © 2021, Springer Nature Singapore Pte Ltd.

关键词： Bearing capacity

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Implementation of Two-Dimensional image Result analysis Using Artificial Neural Networks with the Counter propagation Method

Implementation of Two-Dimensional Image Result Analysis Usin...

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3rd IEEE International conference on Emerging Smart Computing and Informatics (IEEE-ESCI)

作者： Paryati Lavate, Santosh H. Martin, Sagayam Salahddine, Krit Elngar, Ahmed A. UPN Vet Yogyakarta Fac Tech Engn Yogyakarta Indonesia AISSMS IOIT Dept E&TC Pune Maharashtra India Karunya Inst Technol & Sci Dept Elect Commun Engn Coimbatore Tamil Nadu India Ibn Zohr Univ Fac Quarzazate Agadir Morocco Beni Suef Univ Fac Comp & Artificial Intelligence Bani Suwayf 62511 Egypt

ISBN: (纸本)9781728185194

Two-dimensional image recognition is one of the activities to check the original image. The method counter propagation used is focused on how to extract data from the available samples. The data extraction step was dividing the sample into several research areas. Then from each region the active pixel value is taken so that numerical data can be obtained as much as the available area. The numerical result data is then normalized by fixed compare, where each numeric data comes from the same data. To prove the method, the writer made a supporting application, namely char-cognition with a basic visual programming language. The final result of the analysis shows that the pattern produced by this method can be recognized well the authenticity of the two-dimensional image. Manual examination is considered inefficient because it faces problems with the eye's eye foresight and accuracy. Two-dimensional images are generally identical but not the same in terms of shape and slope. Automatic two-dimensional image matching via a computer system is essential for better and more accurate identification of two-dimensional images. Artificial neural network method is used for extraction with various data in two-dimensional images. From the five of the simulation can be concluded that the best Learn Rates by the lowest Error Level is 0.1 and the best Learn Rates based on the highest Match Level is 0.3. Otherwise, due to successful rate from this experiment is not measured by low rate of Error Level but from the high of Match Level rate, so that Simulation 2 with Learn Rates=0.3 that will be used in the next experiment.

关键词： artificial neural network two dimensional counter propagation

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analysis of Changing Trends in Textual Data Representation 3rd

Analysis of Changing Trends in Textual Data Representation

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3rd International conference on Recent Trends in image Processing and pattern recognition, RTIP2R 2020

作者： Singh, Ksh. Nareshkumar Dorendro, A. Devi, H. Mamata Mahanta, Anjana Kakoti Department of Computer Science Manipur University Imphal India Department of Computer Science Gauhati University Guwahati India

ISBN: (纸本)9789811605062

The most efficient way to convey human knowledge is through natural language text. In order to manage the exponential growth of digital data, it is high time to build a robust text information system. The system performs various techniques such as classification, clustering, summarization, etc. to organize the huge unstructured text data into well-defined forms. Text representation is the fundamental task in text mining and text retrieval. Just like a backbone gives structure to human body, text representation lays the foundation step for various other downstream tasks of Natural Language Processing (NLP), text mining and text retrieval. This paper concentrates on the analysis of various text representation models and also discusses major changing trends in textual data representation. This paper could be beneficial to those who wish to study and work on text data in NLP domain. The challenges and drawbacks of the existing text representation models are also discussed in this paper. © 2021, Springer Nature Singapore Pte Ltd.

关键词： Machine learning

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Quantifying Uncertainty of image Labelings Using Assignment Flows 43rd

Quantifying Uncertainty of Image Labelings Using Assignment...

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43rd DAGM German conference on pattern recognition, DAGM GCPR 2021

作者： Gonzalez-Alvarado, Daniel Zeilmann, Alexander Schnörr, Christoph Image and Pattern Analysis Group Heidelberg University Heidelberg Germany Heidelberg Collaboratory for Image Processing Heidelberg University Heidelberg Germany

ISBN: (纸本)9783030926588

This paper introduces a novel approach to uncertainty quantification of image labelings determined by assignment flows. Local uncertainties caused by ambiguous data and noise are estimated by fitting Dirichlet distributions and pushed forward to the tangent space. The resulting first- and second-order moments are then propagated using a linear ODE parametrization of assignment flows. The corresponding moment evolution equations can be solved in closed form and numerically evaluated using iterative Krylov subspace techniques and low-rank approximation. This results in a faithful representation and quantification of uncertainty in the output space of image labelings, which is important in all applications where confidence in pixelwise decisions matters. © 2021, Springer Nature Switzerland AG.

关键词： Uncertainty analysis

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Robust image Watermarking Method in Wavelet Domain Based on SIFT Features 20

Robust Image Watermarking Method in Wavelet Domain Based on ...

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3rd International conference on Artificial Intelligence and pattern recognition (AIPR)

作者： Ahmad, Raza Muhammad Yao, Xiaoming Nawaz, Saqib Ali Bhatti, Uzair Aslam Mehmood, Anum Bhatti, Mughair Aslam Shaukat, Mohammad Usman Hainan Univ Coll Comp & Cyberspace Secur Haikou 570228 Hainan Peoples R China Hainan Univ State Key Lab Marine Resource Utilizat South Chin Haikou 570228 Hainan Peoples R China Nanjing Normal Univ Nanjing Nanlin Campus Nanjing Jiangsu Peoples R China Southeast Univ Med Sch Nanjing Jiangsu Peoples R China

ISBN: (纸本)9781450375511

To protect the ownership of the digital content, the robustness of the watermarking algorithm is the most important metric to assess its affectiveness. However few state-of-the-art watermarking algorithms can resist the combinations of the conventional attacks such as jpeg compression and geometric transformation. In this paper, an improved robust image watermarking algorithm is thus proposed to address this issue. The watermark information is embedded in the low frequency domain of the wavelet transform by a quantization modulation method. When using watermark detection, use matching the position information of the SIFT key points is used to calculate the affine transformation parameters and the edge point parameters, and then inversely transform and reposition the detected image to recover the watermark synchronization information. Theoretical analysis and experimental results show that the proposed algorithm has high correlation accuracy and stable performance, and can effectively recover the watermark synchronization of watermark images subjected to rotation, scaling and translation attacks, so that the watermark algorithm can correctly detect or extract watermarks.

关键词： SIFT features Watermarking Wavelet domain Secure image processing

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Wet and Wrinkled Finger recognition Using Voting Classification and GLCM Algorithm

Wet and Wrinkled Finger Recognition Using Voting Classificat...

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Advances in Computing, Communication Control and Networking (ICAC3N), International conference on

作者： Puneet Kumar Suarabh Sharma Chandigarh University Punjab India Chandigarh University Mohali India

ISBN: (纸本)9781665438124

The automated wrinkle fingerprint recognition techniques rely on some principles from the domain of pattern recognition. There are two prevalent techniques for wrinkle fingerprint recognition. The first method is based on the pixel intensity of the wrinkles, and the second relies upon the pattern of fingerprint orientation fields. In this research paper classification method is proposed for the wet and wrinkled image recognition. The proposed method is the combination of threshold segmentation, Grey Level C0-occurrence Matrix algorithm to extract the attributes and voting classification to recognize wet image. The proposed method is executed in python and the analysis of results is done with regard to accuracy, precision and recall. The accuracy of the proposed model is achieved up to 96 percent.

关键词： Measurement image segmentation image recognition Computational modeling Fingers Fingerprint recognition Feature extraction

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Object Localization with Multiplanar Fiducial Markers: Accurate Pose Estimation 11th

Object Localization with Multiplanar Fiducial Markers: Accu...

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11th iberian conference on pattern recognition and image analysis, IbPRIA 2023

作者： García-Ruiz, Pablo Muñoz-Salinas, Rafael Medina-Carnicer, Rafael Marín-Jiménez, Manuel J. Department of Computing and Numerical Analysis University of Córdoba Córdoba Spain Córdoba Spain

ISBN: (纸本)9783031366154

Accurate object tracking is an important task in applications such as augmented/virtual reality and tracking of surgical instruments. This paper presents a novel approach for object pose estimation using a dodecahedron with pentagonal fiducial markers. Unlike traditional ArUco markers, which are squared, we propose a pentagonal marker that fits better in the dodecahedron figure. Our proposal improves marker detectability and enhances pose estimation with a novel pose refinement algorithm. Our experiments show the system’s performance and the refinement algorithm’s efficacy under different configurations. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Augmented reality

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Resource Creation for Sentiment analysis of Under-Resourced Language: Marathi 3rd

Resource Creation for Sentiment Analysis of Under-Resourced ...

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3rd International conference on Recent Trends in image Processing and pattern recognition, RTIP2R 2020

作者： Patil, Rupali S. Kolhe, Satish R. School of Computer Sciences Kavayitri Bahinabai Chaudhari North Maharashtra University Jalgaon India

ISBN: (纸本)9789811605062

With the hike of social networking sites like Facebook, Twitter, Instagram, the Marathi web data are increasing day by day. Mining these data towards the corporate and government has become a broad area of research under Natural Language Processing. Sentiment analysis (SA), identification of the public’s attitude, using machine learning or subjective lexicon, is easier for resource-rich languages like English. Still, for Marathi being poor resource language, it’s a difficult task. In this research, the three approaches have experimented – Corpus-based, SentiWordNet3.0-based, and Hindi SentiWordNet (HSWN)-based to create the Marathi sentiment lexicon (adjective, adverb). The first two approaches use Google Translator to make use of English resource-SWN3.0. The third approach uses HSWN and Marathi WordNet, which minimizes translation errors. The word coverage of the SWN3.0-based lexicon is noteworthy. This paper attempts the Marathi subjective lexicon creation for the first time, which would aid for SA chore precise to the Marathi data. © 2021, Springer Nature Singapore Pte Ltd.

关键词： Sentiment analysis

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Optimal Wavelength Selection for Deep Learning from Hyperspectral images 11th

Optimal Wavelength Selection for Deep Learning from Hypers...

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11th iberian conference on pattern recognition and image analysis, IbPRIA 2023

作者： Dehaeck, S. Van Belleghem, R. Wouters, N. De Ketelaere, B. Liao, W. Flanders Make Oude Diestersebaan 133 Lommel3920 Belgium KU Leuven Department of Biosystems MeBioS Kasteelpark Arenberg 30 Leuven3001 Belgium

ISBN: (纸本)9783031366154

While hyperspectral images typically contain two orders of magnitude more information about the detailed colour spectrum of the object under study compared to RGB images, this inevitably leads to larger storage costs and larger bandwidth requirements. This, in consequence, typically makes it challenging to use such images for real-time industrial defect detection. A second challenge of working with images having tens to hundreds of colour channels is that most available deep-learning (DL) networks are designed for images with three colours. In this paper, we will demonstrate that training typical DL segmentation networks on the full hyperspectral colour channel stack performs differently than when training on only three channels. We will also test two different approaches (Greedy Selection and Bayesian Optimization) to select the N-best wavelengths. For a given use-case, we demonstrate how optimal 3-wavelength images can outperform baseline wavelength selection methods as RGB and PCA (principal component analysis) as well as outperform networks trained with the full colour channel stack. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Principal component analysis

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