Zobrazeno 1 - 10
of 321
pro vyhledávání: '"van der Sommen, Fons"'
Autor:
Viviers, Christiaan, Valiuddin, Amaan, Caetano, Francisco, Abdi, Lemar, Filatova, Lena, de With, Peter, van der Sommen, Fons
Detecting Out-of-Distribution~(OOD) sensory data and covariate distribution shift aims to identify new test examples with different high-level image statistics to the captured, normal and In-Distribution (ID) set. Existing OOD detection literature la
Externí odkaz:
http://arxiv.org/abs/2409.03043
Autor:
Lehman, Dan, Schoonbeek, Tim J., Hung, Shao-Hsuan, Kustra, Jacek, de With, Peter H. N., van der Sommen, Fons
Recognizing errors in assembly and maintenance procedures is valuable for industrial applications, since it can increase worker efficiency and prevent unplanned down-time. Although assembly state recognition is gaining attention, none of the current
Externí odkaz:
http://arxiv.org/abs/2408.12945
Autor:
Schoonbeek, Tim J., Balachandran, Goutham, Onvlee, Hans, Houben, Tim, Hung, Shao-Hsuan, Kustra, Jacek, de With, Peter H. N., van der Sommen, Fons
Assembly state recognition facilitates the execution of assembly procedures, offering feedback to enhance efficiency and minimize errors. However, recognizing assembly states poses challenges in scalability, since parts are frequently updated, and th
Externí odkaz:
http://arxiv.org/abs/2408.11700
Autor:
Jaspers, Tim J. M., de Jong, Ronald L. P. D., Khalil, Yasmina Al, Zeelenberg, Tijn, Kusters, Carolus H. J., Li, Yiping, van Jaarsveld, Romy C., Bakker, Franciscus H. A., Ruurda, Jelle P., Brinkman, Willem M., De With, Peter H. N., van der Sommen, Fons
Over the past decade, computer vision applications in minimally invasive surgery have rapidly increased. Despite this growth, the impact of surgical computer vision remains limited compared to other medical fields like pathology and radiology, primar
Externí odkaz:
http://arxiv.org/abs/2407.17904
Autor:
Viviers, Christiaan G. A., Filatova, Lena, Termeer, Maurice, de With, Peter H. N., van der Sommen, Fons
Publikováno v:
IEEE Transactions on Image Processing (2024) (Volume: 33) Page(s): 2462 - 2476
Accurate 6-DoF pose estimation of surgical instruments during minimally invasive surgeries can substantially improve treatment strategies and eventual surgical outcome. Existing deep learning methods have achieved accurate results, but they require c
Externí odkaz:
http://arxiv.org/abs/2405.11677
Although action recognition for procedural tasks has received notable attention, it has a fundamental flaw in that no measure of success for actions is provided. This limits the applicability of such systems especially within the industrial domain, s
Externí odkaz:
http://arxiv.org/abs/2310.17323
Autor:
Viviers, Christiaan, Ramaekers, Mark, Valiuddin, Amaan, Hellström, Terese, Tasios, Nick, van der Ven, John, Jacobs, Igor, Ewals, Lotte, Nederend, Joost, de With, Peter, Luyer, Misha, van der Sommen, Fons
Pancreatic ductal adenocarcinoma (PDAC) is a highly aggressive cancer with limited treatment options. This research proposes a workflow and deep learning-based segmentation models to automatically assess tumor-vessel involvement, a key factor in dete
Externí odkaz:
http://arxiv.org/abs/2310.00639
Autor:
Valiuddin, M. M. Amaan, Viviers, Christiaan G. A., van Sloun, Ruud J. G., de With, Peter H. N., van der Sommen, Fons
Data uncertainties, such as sensor noise, occlusions or limitations in the acquisition method can introduce irreducible ambiguities in images, which result in varying, yet plausible, semantic hypotheses. In Machine Learning, this ambiguity is commonl
Externí odkaz:
http://arxiv.org/abs/2307.16694
Encoding-decoding CNNs play a central role in data-driven noise reduction and can be found within numerous deep-learning algorithms. However, the development of these CNN architectures is often done in ad-hoc fashion and theoretical underpinnings for
Externí odkaz:
http://arxiv.org/abs/2307.13425
Autor:
Viviers, Christiaan G. A., Valiuddin, Amaan M. M., de With, Peter H. N., van der Sommen, Fons
Uncertainty quantification in medical images has become an essential addition to segmentation models for practical application in the real world. Although there are valuable developments in accurate uncertainty quantification methods using 2D images
Externí odkaz:
http://arxiv.org/abs/2305.00950