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Directional dark-field imaging is an emerging x-ray modality that is sensitive to unresolved anisotropic scattering from sub-pixel sample microstructures. A single-grid imaging set-up can be used to capture dark-field images by looking at…

Image and Video Processing · Electrical Eng. & Systems 2023-04-07 Michelle K Croughan , Ying Ying How , Allan Pennings , Kaye S Morgan

We consider the task of semi-supervised video object segmentation (VOS). Our approach mitigates shortcomings in previous VOS work by addressing detail preservation and temporal consistency using visual warping. In contrast to prior work…

Computer Vision and Pattern Recognition · Computer Science 2021-11-23 Julia Gong , F. Christopher Holsinger , Serena Yeung

Emerging single-photon-sensitive sensors combined with advanced inverse methods to process picosecond-accurate time-stamped photon counts have given rise to unprecedented imaging capabilities. Rather than imaging photons that travel along…

Optics · Physics 2020-05-19 D. Faccio , A. Velten , G. Wetzstein

Variational Auto-Encoders have often been used for unsupervised pretraining, feature extraction and out-of-distribution and anomaly detection in the medical field. However, VAEs often lack the ability to produce sharp images and learn…

Machine Learning · Computer Science 2019-11-28 David Zimmerer , Jens Petersen , Klaus Maier-Hein

Edge-enhanced imaging is critical for visualizing weakly absorbing and transparent objects. Extending this functionality into the mid-infrared (MIR) region enables chemical sensitivity and improved imaging performance for biomedical,…

Quantum techniques can be used to enhance the signal-to-noise ratio in optical imaging. Leveraging the latest advances in single photon avalanche diode array cameras and multi-photon detection techniques, here we introduce a super-sensitive…

In this paper, we propose an x-ray fluorescence imaging system for elemental analysis. The key idea is what we call "x-ray fluorescence sectioning". Specifically, a slit collimator in front of an x-ray tube is used to shape x-rays into a…

Medical Physics · Physics 2012-10-29 Wenxiang Cong , Ge Wang

Image segmentation is the process of partitioning an image into meaningful segments. The meaning of the segments is subjective due to the definition of homogeneity is varied based on the users perspective hence the automation of the…

Computer Vision and Pattern Recognition · Computer Science 2018-10-12 Ravimal Bandara

Wavefront sensing and reconstruction are widely used for adaptive optics, aberration correction, and high-resolution optical phase imaging. Traditionally, interference and/or microlens arrays are used to convert the optical phase into…

Edge detection, a basic task in the field of computer vision, is an important preprocessing operation for the recognition and understanding of a visual scene. In conventional models, the edge image generated is ambiguous, and the edge lines…

Computer Vision and Pattern Recognition · Computer Science 2022-03-18 Dawei Dai , Chunjie Wang , Shuyin Xia , Yingge Liu , Guoyin Wang

Benefiting from its single-photon sensitivity, single-photon avalanche diode (SPAD) array has been widely applied in various fields such as fluorescence lifetime imaging and quantum computing. However, large-scale high-fidelity…

The segmentation of transparent objects can be very useful in computer vision applications. However, because they borrow texture from their background and have a similar appearance to their surroundings, transparent objects are not handled…

Computer Vision and Pattern Recognition · Computer Science 2015-11-24 Yichao Xu , Hajime Nagahara , Atsushi Shimada , Rin-ichiro Taniguchi

Ground-based astronomical observations at thermal infrared wavelengths face the problem of extracting the weak astronomical signal from the large and rapidly variable background flux. The observing strategy most commonly used, the so-called…

Astrophysics · Physics 2009-10-31 M. Bertero , P. Boccacci , M. Robberto

The paper presents a new model for single channel images low-level interpretation. The image is decomposed into a graph which captures a complete set of structural features. The description allows to accurately identify every edge location…

Computer Vision and Pattern Recognition · Computer Science 2019-04-23 Alessandro Dal Palu'

Recent work has shown that label-efficient few-shot learning through self-supervision can achieve promising medical image segmentation results. However, few-shot segmentation models typically rely on prototype representations of the…

Image and Video Processing · Electrical Eng. & Systems 2022-03-07 Stine Hansen , Srishti Gautam , Robert Jenssen , Michael Kampffmeyer

Single-pixel imaging, originally developed in light optics, facilitates fast three-dimensional sample reconstruction, as well as probing with light wavelengths undetectable by conventional multi-pixel detectors. However, the spatial…

This paper presents a state-of-the-art approach in object detection for being applied in future SLAM problems. Although, many SLAM methods are proposed to create suitable autonomy for mobile robots namely ground vehicles, they still face…

Robotics · Computer Science 2018-10-05 Seyed Amir Tafrishi , Vahid E. Kandjani

The possibility to obtain a three-dimensional representation of a single object with sub-$\mu$m resolution is crucial in many fields, from material science to clinical diagnostics. This is typically achieved through tomography, which…

We introduce optical polarization-insensitive high pass filters based on total internal reflection of light at the interface of two dielectric media (1D) and Bragg reflection of a multilayer stack (2D) in transmission mode. The wavevectors…

Optics · Physics 2019-11-26 Ali Pour Mohammad Qoli Vafa , Parisa Karimi , Amin Khavasi

Few-shot object detection (FSOD) aims to detect objects with limited samples for novel classes, while relying on abundant data for base classes. Existing FSOD approaches, predominantly built on the Faster R-CNN detector, entangle objectness…

Computer Vision and Pattern Recognition · Computer Science 2025-06-30 Taijin Zhao , Heqian Qiu , Yu Dai , Lanxiao Wang , Fanman Meng , Qingbo Wu , Hongliang Li