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pro vyhledávání: '"Wang, Brian"'
Class agnostic counting (CAC) is a vision task that can be used to count the total occurrence number of any given reference objects in the query image. The task is usually formulated as a density map estimation problem through similarity computation
Externí odkaz:
http://arxiv.org/abs/2404.09826
While IoT sensors in physical spaces have provided utility and comfort in our lives, their instrumentation in private and personal spaces has led to growing concerns regarding privacy. The existing notion behind IoT privacy is that the sensors whose
Externí odkaz:
http://arxiv.org/abs/2401.08037
Existing building recognition methods, exemplified by BRAILS, utilize supervised learning to extract information from satellite and street-view images for classification and segmentation. However, each task module requires human-annotated data, hinde
Externí odkaz:
http://arxiv.org/abs/2312.12479
Path planning in obstacle-dense environments is a key challenge in robotics, and depends on inferring scene attributes and associated uncertainties. We present a multiple-hypothesis path planner designed to navigate complex environments using obstacl
Externí odkaz:
http://arxiv.org/abs/2308.07420
Autor:
Zhao, Hui, Wang, Brian, Sarkar, Vikren, Rassiah-Szegedi, Prema, Huang, Y. Jessica, Szegedi, Martin, Huang, Long, Gonzalez, Victor, Salter, Bill
We investigate the difference between surface matching and target matching for pelvic radiation image guidance. The uniqueness of our study is that all patients have multiple CT-on-rails (CTOR) scans to compare to corresponding AlignRT images. Ten pa
Externí odkaz:
http://hdl.handle.net/10150/617402
http://arizona.openrepository.com/arizona/handle/10150/617402
http://arizona.openrepository.com/arizona/handle/10150/617402
We present a method for detecting and mapping trees in noisy stereo camera point clouds, using a learned 3-D object detector. Inspired by recent advancements in 3-D object detection using a pseudo-lidar representation for stereo data, we train a Poin
Externí odkaz:
http://arxiv.org/abs/2103.15967
Autor:
Wang, Brian H., Chao, Wei-Lun, Wang, Yan, Hariharan, Bharath, Weinberger, Kilian Q., Campbell, Mark
Object segmentation in three-dimensional (3-D) point clouds is a critical task for robots capable of 3-D perception. Despite the impressive performance of deep learning-based approaches on object segmentation in 2-D images, deep learning has not been
Externí odkaz:
http://arxiv.org/abs/1910.13955
Radiation therapy of thoracic and abdominal tumors requires incorporating the respiratory motion into treatments. To precisely account for the patient respiratory motions and predict the respiratory signals, a generalized model for predictions of dif
Externí odkaz:
http://arxiv.org/abs/1901.08638
Akademický článek
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Autor:
Wang, Yan, Lai, Zihang, Huang, Gao, Wang, Brian H., van der Maaten, Laurens, Campbell, Mark, Weinberger, Kilian Q.
Many applications of stereo depth estimation in robotics require the generation of accurate disparity maps in real time under significant computational constraints. Current state-of-the-art algorithms force a choice between either generating accurate
Externí odkaz:
http://arxiv.org/abs/1810.11408