Relevant bibliographies by topics / Feature detection and description

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Feature detection and description'

Author: Grafiati
Published: 3 June 2025
Last updated: 31 July 2025

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Journal articles on the topic "Feature detection and description"

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Feng, Lu, Zhuangzhi Wu, and Xiang Long. "Fast Image Diffusion for Feature Detection and Description." International Journal of Computer Theory and Engineering 8, no. 1 (2016): 58–62. http://dx.doi.org/10.7763/ijcte.2016.v8.1020.

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Yuan, Chaofeng, Yuelei Xu, Jingjing Yang, Zhaoxiang Zhang, and Qing Zhou. "A Pseudoinverse Siamese Convolutional Neural Network of Transformation Invariance Feature Detection and Description for a SLAM System." Machines 10, no. 11 (2022): 1070. http://dx.doi.org/10.3390/machines10111070.

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Simultaneous localization and mapping (SLAM) systems play an important role in the field of automated robotics and artificial intelligence. Feature detection and matching are crucial aspects affecting the overall accuracy of the SLAM system. However, the accuracy of the position and matching cannot be guaranteed when confronted with a cross-view angle, illumination, texture, etc. Moreover, deep learning methods are very sensitive to perspective change and do not have the invariance of geometric transformation. Therefore, a novel pseudo-Siamese convolutional network of a transformation invarian
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Zhang, Zhiqiang, Xin Qiu, and Yongzhou Li. "Learning Balance Feature for Object Detection." Electronics 11, no. 17 (2022): 2765. http://dx.doi.org/10.3390/electronics11172765.

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In the field of studying scale variation, the Feature Pyramid Network (FPN) replaces the image pyramid and has become one of the most popular object detection methods for detecting multi-scale objects. State-of-the-art methods have FPN inserted into a pipeline between the backbone and the detection head to enable shallow features with more semantic information. However, FPN is insufficient for object detection on various scales, especially for small-scale object detection. One of the reasons is that the features are extracted at different network depths, which introduces gaps between features.
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Hoffmann, Annika. "On the Benefits of Color Information for Feature Matching in Outdoor Environments." Robotics 9, no. 4 (2020): 85. http://dx.doi.org/10.3390/robotics9040085.

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The detection and description of features is one basic technique for many visual robot navigation systems in both indoor and outdoor environments. Matched features from two or more images are used to solve navigation problems, e.g., by establishing spatial relationships between different poses in which the robot captured the images. Feature detection and description is particularly challenging in outdoor environments, and widely used grayscale methods lead to high numbers of outliers. In this paper, we analyze the use of color information for keypoint detection and description. We consider gra
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Oliveira, António José, Bruno Miguel Ferreira, and Nuno Alexandre Cruz. "A Performance Analysis of Feature Extraction Algorithms for Acoustic Image-Based Underwater Navigation." Journal of Marine Science and Engineering 9, no. 4 (2021): 361. http://dx.doi.org/10.3390/jmse9040361.

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In underwater navigation, sonars are useful sensing devices for operation in confined or structured environments, enabling the detection and identification of underwater environmental features through the acquisition of acoustic images. Nonetheless, in these environments, several problems affect their performance, such as background noise and multiple secondary echoes. In recent years, research has been conducted regarding the application of feature extraction algorithms to underwater acoustic images, with the purpose of achieving a robust solution for the detection and matching of environment
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Wang Fangbin, 汪方斌, 储朱涛 Chu Zhutao, 朱达荣 Zhu Darong, 刘涛 Liu Tao, 徐德军 Xu Dejun, and 许露 Xu Lu. "An Improved KAZE Feature Detection and Description Algorithm." Laser & Optoelectronics Progress 55, no. 9 (2018): 091007. http://dx.doi.org/10.3788/lop55.091007.

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Pang, Yanwei, Xianbin Cao, Lei Zhang, and Amir Hussein. "Special issue on image feature detection and description." Neurocomputing 120 (November 2013): 1–3. http://dx.doi.org/10.1016/j.neucom.2013.02.036.

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Huang, Wei, Yongjie Li, Zhaonan Xu, Xinwei Yao, and Rongchun Wan. "Improved Deep Support Vector Data Description Model Using Feature Patching for Industrial Anomaly Detection." Sensors 25, no. 1 (2024): 67. https://doi.org/10.3390/s25010067.

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In industrial contexts, anomaly detection is crucial for ensuring quality control and maintaining operational efficiency in manufacturing processes. Leveraging high-level features extracted from ImageNet-trained networks and the robust capabilities of the Deep Support Vector Data Description (SVDD) model for anomaly detection, this paper proposes an improved Deep SVDD model, termed Feature-Patching SVDD (FPSVDD), designed for unsupervised anomaly detection in industrial applications. This model integrates a feature-patching technique with the Deep SVDD framework. Features are extracted from a
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Zhang, Wei, and Guoying Zhang. "Image Feature Matching Based on Semantic Fusion Description and Spatial Consistency." Symmetry 10, no. 12 (2018): 725. http://dx.doi.org/10.3390/sym10120725.

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Image feature description and matching is widely used in computer vision, such as camera pose estimation. Traditional feature descriptions lack the semantic and spatial information, and give rise to a large number of feature mismatches. In order to improve the accuracy of image feature matching, a feature description and matching method, based on local semantic information fusion and feature spatial consistency, is proposed in this paper. Once object detection is used on images, feature points are then extracted, and image patches with various sizes surrounding these points are clipped. These
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Stanciu, Stefan G., Radu Hristu, Radu Boriga, and George A. Stanciu. "On the Suitability of SIFT Technique to Deal with Image Modifications Specific to Confocal Scanning Laser Microscopy." Microscopy and Microanalysis 16, no. 5 (2010): 515–30. http://dx.doi.org/10.1017/s1431927610000371.

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AbstractComputer vision tasks such as recognition and classification of objects and structures or image registration and retrieval can provide significant information when applied to microscopy images. Recently developed techniques for the detection and description of local features make the extraction and description of local image features that are invariant to various changes possible. The invariance and robustness of feature detection and description techniques play a key role in the design and implementation of object recognition, image registration, or image mosaicing applications. The s
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Dissertations / Theses on the topic "Feature detection and description"

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Fowers, Spencer G. "Limited Resource Feature Detection, Description, and Matching." BYU ScholarsArchive, 2012. https://scholarsarchive.byu.edu/etd/3207.

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The aims of this research work are to develop a feature detection, description, and matching system for low-resource applications. This work was motivated by the need for a vision sensor to assist the flight of a quad-rotor UAV. This application presented a real-world challenge of autonomous drift stabilization using vision sensors. The initial solution implemented a basic feature detector and matching system on an FPGA. The research then pursued ways to improve the vision system. Research began with color feature detection, and the Color Difference of Gaussians feature detector was developed.
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Du, Xiaoyun. "Enhanced Contour Description for People Detection in Images." Thesis, Université d'Ottawa / University of Ottawa, 2014. http://hdl.handle.net/10393/31804.

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People detection has been an attractive technology in computer vision. There are many useful applications in our daily life, for instance, intelligent surveillance and driver assistance system. People detection is a challenging matter as people adopt a wide range of poses, wear diverse clothes, and are visible in different kind of backgrounds with significant changes in illumination. In this thesis, some advanced techniques and powerful tools are presented in order to design a robust people detection system. First a baseline model is implemented by combining the Histogram of Oriented Gradients
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Westin, Carl-Fredrik. "Feature extraction based on a tensor image description." Licentiate thesis, Linköping University, Linköping University, Computer Vision, 1991. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-54888.

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<p>Feature extraction from a tensor based local image representation introduced by Knutsson in [37] is discussed. The tensor representation keeps statements of structure, certainty of statement and energy separate. Further processing for obtaining new features also having these three entities separate is achieved by the use of a new concept, tensor field filtering. Tensor filters for smoothing and for extraction of circular symmetries are presented and discussed in particular. These methods are used for corner detection and extraction of more global features such as lines in images. A novel me
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Nilsson, Niklas. "Feature detection for geospatial referencing." Thesis, Umeå universitet, Institutionen för fysik, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-159809.

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With the drone industry's recent explosive advancement, aerial photography is becoming increasingly important for an array of applications ranging from construction to agriculture. A drone flyover can give a better overview of regions that are difficult to navigate, and is often significantly faster, cheaper and more accurate than man-made sketches and other alternatives. With this increased use comes a growing need for image processing methods to help in analyzing captured photographs. This thesis presents a method for automatic location detection in aerial photographs using databases of aeri
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Danielsson, Max, and Thomas Sievert. "Viability of Feature Detection on Sony Xperia Z3 using OpenCL." Thesis, Blekinge Tekniska Högskola, Institutionen för kreativa teknologier, 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:bth-10388.

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Context. Embedded platforms GPUs are reaching a level of perfor-mance comparable to desktop hardware. Therefore it becomes inter-esting to apply Computer Vision techniques to modern smartphones.The platform holds different challenges, as energy use and heat gen-eration can be an issue depending on load distribution on the device. Objectives. We evaluate the viability of a feature detector and de-scriptor on the Xperia Z3. Specifically we evaluate the the pair basedon real-time execution, heat generation and performance. Methods. We implement the feature detection and feature descrip-tor pair H
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Gundogdu, Erhan. "Feature Detection And Matching Towards Augmented Reality Applications On Mobile Devices." Master's thesis, METU, 2012. http://etd.lib.metu.edu.tr/upload/12614618/index.pdf.

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Local feature detection and its applications in different problems are quite popular in vision research. In order to analyze a scene, its invariant features, which are distinguishable in many views of this scene, are used in pose estimation, object detection and augmented reality. However, required performance metrics might change according to the application type<br>in general, the main metrics are accepted as accuracy and computational complexity. The contributions in this thesis provide improving these metrics and can be divided into three parts, as local feature detection, local feature de
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Huang, Chengqiang. "Featured anomaly detection methods and applications." Thesis, University of Exeter, 2018. http://hdl.handle.net/10871/34351.

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Anomaly detection is a fundamental research topic that has been widely investigated. From critical industrial systems, e.g., network intrusion detection systems, to people’s daily activities, e.g., mobile fraud detection, anomaly detection has become the very first vital resort to protect and secure public and personal properties. Although anomaly detection methods have been under consistent development over the years, the explosive growth of data volume and the continued dramatic variation of data patterns pose great challenges on the anomaly detection systems and are fuelling the great deman
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Desai, Alok. "An Efficient Feature Descriptor and Its Real-Time Applications." BYU ScholarsArchive, 2015. https://scholarsarchive.byu.edu/etd/5465.

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Finding salient features in an image, and matching them to their corresponding features in another image is an important step for many vision-based applications. Feature description plays an important role in the feature matching process. A robust feature descriptor must works with a number of image deformations and should be computationally efficient. For resource-limited systems, floating point and complex operations such as multiplication and square root are not desirable. This research first introduces a robust and efficient feature descriptor called PRObability (PRO) descriptor that meet
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Canelhas, Daniel Ricão. "Truncated Signed Distance Fields Applied To Robotics." Doctoral thesis, Örebro universitet, Institutionen för naturvetenskap och teknik, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:oru:diva-59369.

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This thesis is concerned with topics related to dense mapping of large scale three-dimensional spaces. In particular, the motivating scenario of this work is one in which a mobile robot with limited computational resources explores an unknown environment using a depth-camera. To this end, low-level topics such as sensor noise, map representation, interpolation, bit-rates, compression are investigated, and their impacts on more complex tasks, such as feature detection and description, camera-tracking, and mapping are evaluated thoroughly. A central idea of this thesis is the use of truncated si
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Mohammed, Abdulmalik. "Obstacle detection and emergency exit sign recognition for autonomous navigation using camera phone." Thesis, University of Manchester, 2017. https://www.research.manchester.ac.uk/portal/en/theses/obstacle-detection-and-emergency-exit-sign-recognition-for-autonomous-navigation-using-camera-phone(e0224d89-e743-47a4-8c68-52f718457098).html.

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In this research work, we develop an obstacle detection and emergency exit sign recognition system on a mobile phone by extending the feature from accelerated segment test detector with Harris corner filter. The first step often required for many vision based applications is the detection of objects of interest in an image. Hence, in this research work, we introduce emergency exit sign detection method using colour histogram. The hue and saturation component of an HSV colour model are processed into features to build a 2D colour histogram. We backproject a 2D colour histogram to detect emergen
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Books on the topic "Feature detection and description"

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Barbieri, Gillian Sylvia Anna-Stasia. The role of spatial derivatives in feature detection. University of Birmingham, 2000.

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Zhang, Zhifen, Guangrui Wen, and Wenjing Ren. Multiple Sensing-Driven Feature Extraction and Defect Detection. Springer Nature Singapore, 2025. https://doi.org/10.1007/978-981-96-4808-5.

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Li, Jian. Synthetic aperture radar target detection, feature extraction, and image formation techniques. National Aeronautics and Space Administration, 1994.

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United States. National Aeronautics and Space Administration., ed. Synthetic aperture radar target detection, feature extraction, and image formation techniques. National Aeronautics and Space Administration, 1994.

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Neelanarayanan, ed. Feature Analysis for Abnormality Detection in Breast Thermogram Sequences Subject to Cold Stress. Association of Scientists, Developers and Faculties, 2014.

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Levin, Boris. Seĭsmichnostʹ Tikhookeanskogo regiona: Vyi︠a︡vlenie globalʹnykh zakonomernosteĭ = Seismicity of the Pacific Region : global feature detection. "I︠A︡nus-K", 2012.

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L, Jankovsky Amy, and Lewis Research Center, eds. Real-time sensor validation, signal reconstruction, and feature detection for an RLV propulsion testbed. National Aeronautics and Space Administration, Lewis Research Center, 1998.

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L, Jankovsky Amy, and Lewis Research Center, eds. Real-time sensor validation, signal reconstruction, and feature detection for an RLV propulsion testbed. National Aeronautics and Space Administration, Lewis Research Center, 1998.

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L, Jankovsky Amy, and Lewis Research Center, eds. Real-time sensor validation, signal reconstruction, and feature detection for an RLV propulsion testbed. National Aeronautics and Space Administration, Lewis Research Center, 1998.

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L, Jankovsky Amy, and Lewis Research Center, eds. Real-time sensor validation, signal reconstruction, and feature detection for an RLV propulsion testbed. National Aeronautics and Space Administration, Lewis Research Center, 1998.

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Book chapters on the topic "Feature detection and description"

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Hassaballah, M., Aly Amin Abdelmgeid, and Hammam A. Alshazly. "Image Features Detection, Description and Matching." In Image Feature Detectors and Descriptors. Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-28854-3_2.

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Hassaballah, M., and Ali Ismail Awad. "Detection and Description of Image Features: An Introduction." In Image Feature Detectors and Descriptors. Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-28854-3_1.

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Bredereke, J., and R. Gotzhein. "Specification, Detection and Resolution of IN Feature Interactions with Estelle." In Formal Description Techniques VII. Springer US, 1995. http://dx.doi.org/10.1007/978-0-387-34878-0_30.

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Youssef, Ali, and Francisco Vasconcelos. "NeRF-Supervised Feature Point Detection and Description." In Lecture Notes in Computer Science. Springer Nature Switzerland, 2025. https://doi.org/10.1007/978-3-031-91989-3_7.

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Bagad, Piyush, Floor Eijkelboom, Mark Fokkema, Danilo de Goede, Paul Hilders, and Miltiadis Kofinas. "C-3PO: Towards Rotation Equivariant Feature Detection and Description." In Lecture Notes in Computer Science. Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-25069-9_44.

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Yíldíz, Ramazan, and Tankut Acarman. "Feature-Based Robust Description and Monocular Detection: An Application to Vehicle tracking." In Hybrid Intelligence for Image Analysis and Understanding. John Wiley & Sons, Ltd, 2017. http://dx.doi.org/10.1002/9781119242963.ch8.

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Beryl Princess, P. Joyce, Salaja Silas, and Elijah Blessing Rajsingh. "Performance Analysis of Feature Detection and Description (FDD) Methods on Accident Images." In Communications in Computer and Information Science. Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-6315-7_32.

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Gong, Lejun, Jiacheng Feng, and Ronggen Yang. "Corner Detection-Based Image Feature Extraction and Description with Application to Target Tracking." In Wireless Communications, Networking and Applications. Springer India, 2015. http://dx.doi.org/10.1007/978-81-322-2580-5_97.

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Lecron, Fabian, Mohammed Benjelloun, and Saïd Mahmoudi. "Descriptive Image Feature for Object Detection in Medical Images." In Lecture Notes in Computer Science. Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-31298-4_39.

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Wang, Changhao, Guanwen Zhang, Zhengyun Cheng, and Wei Zhou. "Rethinking Low-Level Features for Interest Point Detection and Description." In Computer Vision – ACCV 2022. Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-26284-5_7.

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Conference papers on the topic "Feature detection and description"

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Huang, Yidian, Min Xu, Yaoyao Nie, et al. "One Simple Stage learning for Feature Detection, Description and Matching." In 2025 Joint International Conference on Automation-Intelligence-Safety (ICAIS) & International Symposium on Autonomous Systems (ISAS). IEEE, 2025. https://doi.org/10.1109/icaisisas64483.2025.11051405.

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Naumov, I. I., R. R. Ibadov, and A. G. Gazaryan. "Detection and Description of Local Features of a Thermal Image." In 2025 International Conference on Industrial Engineering, Applications and Manufacturing (ICIEAM). IEEE, 2025. https://doi.org/10.1109/icieam65163.2025.11028317.

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Yang, Yifei, Zihao Wang, Zhen Li, Fang Deng, and Yidian Huang. "D2VT: Better Detection and Description of Local Features with Vision Transformers." In 2024 China Automation Congress (CAC). IEEE, 2024. https://doi.org/10.1109/cac63892.2024.10864608.

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Krauß, Franziska, Matthias Ege, Zoltan Lovasz, et al. "Simultaneous Description and Detection of Sparse Features for Deformable Intraoperative Bladder Environments*." In 2024 IEEE SENSORS. IEEE, 2024. https://doi.org/10.1109/sensors60989.2024.10785221.

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Ganesan, Annalakshmi. "Multi Feature Descriptor Based Ship Wake Detection Using AdaBoost-Weighted Extreme Learning Machine." In 2024 IEEE Space, Aerospace and Defence Conference (SPACE). IEEE, 2024. http://dx.doi.org/10.1109/space63117.2024.10667783.

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Drexler, Dominik, Simon Ståhlberg, Blai Bonet, and Hector Geffner. "Symmetries and Expressive Requirements for Learning General Policies." In 21st International Conference on Principles of Knowledge Representation and Reasoning {KR-2023}. International Joint Conferences on Artificial Intelligence Organization, 2024. http://dx.doi.org/10.24963/kr.2024/79.

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State symmetries play an important role in planning and generalized planning. In the first case, state symmetries can be used to reduce the size of the search; in the second, to reduce the size of the training set. In the case of general planning, however, it is also critical to distinguish non-symmetric states, i.e., states that represent non-isomorphic relational structures. However, while the language of first-order logic distinguishes non-symmetric states, the languages and architectures used to represent and learn general policies do not. In particular, recent approaches for learning gene
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López-López, D., A. Wong-Moreno, and L. Martínez. "Carburization in Fossil Fired Boilers: a Review." In CORROSION 2002. NACE International, 2002. https://doi.org/10.5006/c2002-02378.

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Abstract Failure of superheater tubes in fossil-fired boilers has been associated to creep and high temperature fuel ash corrosion. Oxidizing conditions are typical of boiler environments, and under such conditions it is unlikely to have the required reducing conditions to explain carburization of boilers materials. However, several cases of carburization related to failures or high corrosion rates have been reported. The purpose of this paper is, to present a critical review on carburization process in boilers, a phenomenon much more frequent that it would be expected and, whose occurrence, h
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Xue, Fei, Ignas Budvytis, and Roberto Cipolla. "SFD2: Semantic-Guided Feature Detection and Description." In 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). IEEE, 2023. http://dx.doi.org/10.1109/cvpr52729.2023.00504.

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Keskenler, Mustafa Furkan, Abdulsamet Hasiloglu, Gulsah Tumuklu Ozyer, Baris Ozyer, and Emrah Simsek. "Sperm Detection and Analysis Using Feature Description Algorithms." In 2019 27th Signal Processing and Communications Applications Conference (SIU). IEEE, 2019. http://dx.doi.org/10.1109/siu.2019.8806287.

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Sahrim, Musab, Mark S. Nixon, and Roxana O. Carare. "Blood vessel feature description for detection of Alzheimers disease." In 2014 13th International Conference on Control Automation Robotics & Vision (ICARCV). IEEE, 2014. http://dx.doi.org/10.1109/icarcv.2014.7064325.

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Reports on the topic "Feature detection and description"

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Guan, Yawen, Deborah Sulsky, J. Tucker, and Christian Sampson. Feature Detection. Office of Scientific and Technical Information (OSTI), 2021. http://dx.doi.org/10.2172/1769711.

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Dinovitzer, Aaron, Brian Leis, Ravi Krishnamurthy, Chris Alexander, and Mures Zarea. PR214-203804-R01 Systematize 20 Years of Mechanical Damage Research. Pipeline Research Council International, Inc. (PRCI), 2022. http://dx.doi.org/10.55274/r0012226.

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This research was funded in part under the Department of Transportation, Pipeline and Hazardous Materials Safety Administration's Pipeline Safety Research and Development Program. The views and conclusions contained in this document are those of the authors and should not be interpreted as representing the official policies, either expressed or implied, of the Pipeline and Hazardous Materials Safety Administration, or the U.S. Government. Research over the past 20 years has improved the pipeline industry's understanding of the behavior and failure processes for mechanical damage. This new unde
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Robinson, K. Feature detection for spatial templates. Office of Scientific and Technical Information (OSTI), 1996. http://dx.doi.org/10.2172/179294.

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Lukow, Steven, Ross Lee, Jonathan Gigax, and David Grow. Improving Non-Destructive Detection Technology Through SAVY Feature Detection. Office of Scientific and Technical Information (OSTI), 2022. http://dx.doi.org/10.2172/1884728.

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Hajjaj, Hadhoum. Feature Description for Assessing Autonomous Vehicle Performance. National Institute of Standards and Technology, 2024. http://dx.doi.org/10.6028/nist.ir.8534.

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Stevens, Mark R., and J. R. Beveridge. Optical Linear Feature Detection Based on Model Pose. Defense Technical Information Center, 1995. http://dx.doi.org/10.21236/ada308546.

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Karasaki, Kenzi, John Apps, Christine Doughty, et al. Feature Detection, Characterization and Confirmation Methodology: Final Report. Office of Scientific and Technical Information (OSTI), 2007. http://dx.doi.org/10.2172/945944.

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West, Brendan. Linear- and repetitive-feature detection within remotely sensed imagery. Cold Regions Research and Engineering Laboratory (U.S.), 2017. http://dx.doi.org/10.21079/11681/22151.

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Downs, Christine, Jason Heath, and Teeratorn Kadeethum. Persistent homology-based feature detection from remote-sensing data. Office of Scientific and Technical Information (OSTI), 2022. http://dx.doi.org/10.2172/1887492.

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Sherlock, Barry G. Wavelet Based Feature Extraction for Target Recognition and Minefield Detection. Defense Technical Information Center, 2002. http://dx.doi.org/10.21236/ada401966.

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