Zobrazeno 1 - 10
of 119
pro vyhledávání: '"Valiuddin"'
Autor:
Valiuddin, M. M. A., van Sloun, R. J. G., Viviers, C. G. A., de With, P. H. N., van der Sommen, F.
Advancements in image segmentation play an integral role within the greater scope of Deep Learning-based computer vision. Furthermore, their widespread applicability in critical real-world tasks has given rise to challenges related to the reliability
Externí odkaz:
http://arxiv.org/abs/2411.16370
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:
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
Publikováno v:
Mehran University Research Journal of Engineering and Technology, Vol 35, Iss 2, Pp 161-170 (2016)
A control scheme is being presented for the trajectory tracking of a nonholonomic kinematic model of mobile robots. As a kinematic model of mobile robots is nonlinear in nature, therefore, it is controlling is always being a difficult task. Thus, a c
Externí odkaz:
https://doaj.org/article/309fb276126c4ae69ce6572baea5912e
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
Publikováno v:
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol XL-3/W2, Pp 169-175 (2015)
Rapid advancement in remote sensing open new avenues to explore the hyperspectral Hyperion imagery pre-processing techniques, analysis and application for land use mapping. The hyperspectral data consists of 242 bands out of which 196 calibrated/usef
Externí odkaz:
https://doaj.org/article/04be6f800a0e4d62a546087a4344f32c
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
Autor:
Valiuddin, M. M. Amaan, Viviers, Christiaan G. A., van Sloun, Ruud J. G., de With, Peter H. N., van der Sommen, Fons
Melanoma is a serious form of skin cancer with high mortality rate at later stages. Fortunately, when detected early, the prognosis of melanoma is promising and malignant melanoma incidence rates are relatively low. As a result, datasets are heavily
Externí odkaz:
http://arxiv.org/abs/2208.04639
Autor:
Valiuddin, M. M. A., Viviers, C. G. A., van Sloun, R. J. G., de With, P. H. N., van der Sommen, F.
Quantifying uncertainty in medical image segmentation applications is essential, as it is often connected to vital decision-making. Compelling attempts have been made in quantifying the uncertainty in image segmentation architectures, e.g. to learn a
Externí odkaz:
http://arxiv.org/abs/2108.02155
Autor:
Valiuddin, M. M. A., Viviers, C. G. A.
Generative modelling has been a topic at the forefront of machine learning research for a substantial amount of time. With the recent success in the field of machine learning, especially in deep learning, there has been an increased interest in expla
Externí odkaz:
http://arxiv.org/abs/2103.12672