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Stroke extraction of Chinese characters plays an important role in the field of character recognition and generation. The most existing character stroke extraction methods focus on image morphological features. These methods usually lead to…

Computer Vision and Pattern Recognition · Computer Science 2023-07-11 Meng Li , Yahan Yu , Yi Yang , Guanghao Ren , Jian Wang

Slope difference distribution (SDD) is computed for the one-dimensional curve. It is not only robust to calculate the partitioning point to separate the curve logically, but also robust to calculate the clustering center of each part of the…

Computer Vision and Pattern Recognition · Computer Science 2020-09-04 Zhenzhou Wang

A new method for dark field imaging is introduced which uses scanned electron diffraction (or 4DSTEM - 4-dimensional scanning transmission electron microscopy) datasets as its input. Instead of working on simple summation of intensity, it…

Materials Science · Physics 2024-09-18 Ian MacLaren , Andrew T. Fraser , Matthew R. Lipsett , Colin Ophus

We introduce a method that allows to automatically segment images into semantically meaningful regions without human supervision. Derived regions are consistent across different images and coincide with human-defined semantic classes on…

Computer Vision and Pattern Recognition · Computer Science 2021-11-22 Daniil Pakhomov , Sanchit Hira , Narayani Wagle , Kemar E. Green , Nassir Navab

In the absence of global positioning information, place recognition is a key capability for enabling localization, mapping and navigation in any environment. Most place recognition methods rely on images, point clouds, or a combination of…

Robotics · Computer Science 2018-04-26 Andrei Cramariuc , Renaud Dubé , Hannes Sommer , Roland Siegwart , Igor Gilitschenski

Mechanical properties in crystals are strongly correlated to the arrangement of 1D line defects, termed dislocations. Recently, Dark field X-ray Microscopy (DFXM) has emerged as a new tool to image and interpret dislocations within crystals…

Materials Science · Physics 2026-01-13 Pin-Hua Huang , Ryan Coffee , Leora Dresselhaus-Marais

Automating the current bridge visual inspection practices using drones and image processing techniques is a prominent way to make these inspections more effective, robust, and less expensive. In this paper, we investigate the development of…

Computer Vision and Pattern Recognition · Computer Science 2025-01-28 Andrii Kompanets , Gautam Pai , Remco Duits , Davide Leonetti , Bert Snijder

Different types of spectroscopies, such as X-ray absorption near edge structure (XANES) and Raman spectroscopy, play a very important role in analyzing the characteristics of different materials. In scientific literature, XANES/Raman data…

Computer Vision and Pattern Recognition · Computer Science 2021-07-08 Weixin Jiang , Eric Schwenker , Trevor Spreadbury , Kai Li , Maria K. Y. Chan , Oliver Cossairt

Camera localization methods based on retrieval, local feature matching, and 3D structure-based pose estimation are accurate but require high storage, are slow, and are not privacy-preserving. A method based on scene landmark detection (SLD)…

Computer Vision and Pattern Recognition · Computer Science 2024-02-01 Tien Do , Sudipta N. Sinha

Visual localization is a useful alternative to standard localization techniques. It works by utilizing cameras. In a typical scenario, features are extracted from captured images and compared with geo-referenced databases. Location…

Computer Vision and Pattern Recognition · Computer Science 2020-06-28 Li Weng , Valerie Gouet-Brunet , Bahman Soheilian

A new approach for decoding directly strains from surfaces encoded with random patterns has been developed and validated. It is based on phase analysis of small region of interest. Here we adapt to random patterns new concepts proposed by…

Medical Physics · Physics 2011-09-12 Jérôme Molimard

Many modern applications require detecting change points in complex sequential data. Most existing methods for change point detection are unsupervised and, as a consequence, lack any information regarding what kind of changes we want to…

Machine Learning · Computer Science 2022-02-11 Nauman Ahad , Eva L. Dyer , Keith B. Hengen , Yao Xie , Mark A. Davenport

Changes, planned or unexpected, are common during the execution of real-life processes. Detecting these changes is a must for optimizing the performance of organizations running such processes. Most of the algorithms present in the…

Artificial Intelligence · Computer Science 2025-10-28 Victor Gallego-Fontenla , Juan C. Vidal , Manuel Lama

Identifying travelers' transportation modes is important in transportation science and location-based services. It's appealing for researchers to leverage GPS trajectory data to infer transportation modes with the popularity of GPS-enabled…

Computer Vision and Pattern Recognition · Computer Science 2023-12-11 Rongsong Li , Xin Pei

For applications in navigation and robotics, estimating the 3D pose of objects is as important as detection. Many approaches to pose estimation rely on detecting or tracking parts or keypoints [11, 21]. In this paper we build on a recent…

Computer Vision and Pattern Recognition · Computer Science 2016-09-20 Patrick Poirson , Phil Ammirato , Cheng-Yang Fu , Wei Liu , Jana Kosecka , Alexander C. Berg

Tunnel lining crack is a crucial indicator of tunnels' safety status. Aiming to classify and segment tunnel cracks with enhanced accuracy and efficiency, this study proposes a two-step deep learning-based method. An automatic tunnel image…

Computer Vision and Pattern Recognition · Computer Science 2025-07-21 Yong Feng , Xiaolei Zhang , Shijin Feng , Yong Zhao , Yihan Chen

Staircase codes (SCCs) are typically decoded using iterative bounded-distance decoding (BDD) and hard decisions. In this paper, a novel decoding algorithm is proposed, which partially uses soft information from the channel. The proposed…

Signal Processing · Electrical Eng. & Systems 2020-06-05 Yi Lei , Alex Alvarado , Bin Chen , Xiong Deng , Zizheng Cao , Jianqiang Li , Kun Xu

The Deep Boltzmann Machines (DBM) is a state-of-the-art unsupervised learning model, which has been successfully applied to handwritten digit recognition and, as well as object recognition. However, the DBM is limited in scene recognition…

Computer Vision and Pattern Recognition · Computer Science 2015-06-25 Jinfu Yang , Jingyu Gao , Guanghui Wang , Shanshan Zhang

This paper presents a Koopman lifting linearization method that is applicable to nonlinear dynamical systems having both stable and unstable regions. It is known that DMD and other standard data-driven methods face a fundamental difficulty…

Machine Learning · Computer Science 2023-01-18 Jerry Ng , H. Harry Asada

We propose a method for detecting structural changes in a city using images captured from vehicular mounted cameras over traversals at two different times. We first generate 3D point clouds for each traversal from the images and approximate…

Computer Vision and Pattern Recognition · Computer Science 2021-03-29 Zi Jian Yew , Gim Hee Lee
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