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pro vyhledávání: '"Mayer, Helmut"'
In this tutorial, we present a compact and holistic discussion of Deep Learning with a focus on Convolutional Neural Networks (CNNs) and supervised regression. While there are numerous books and articles on the individual topics we cover, comprehensi
Externí odkaz:
http://arxiv.org/abs/2408.12308
Autor:
Mayer, Helmut
Die Ressource „Land“ ist einer zunehmenden Nutzungskonkurrenz durch einen steigenden Bedarf an Anbaufläche für Ernährungszwecke und für Energiepflanzen ausgesetzt. In dem Beitrag werden die Ergebnisse von Berechnungen der Umweltökonomischen
Externí odkaz:
https://slub.qucosa.de/id/qucosa%3A7542
https://slub.qucosa.de/api/qucosa%3A7542/attachment/ATT-0/
https://slub.qucosa.de/api/qucosa%3A7542/attachment/ATT-0/
Human Body Dimensions Estimation (HBDE) is a task that an intelligent agent can perform to attempt to determine human body information from images (2D) or point clouds or meshes (3D). More specifically, if we define the HBDE problem as inferring huma
Externí odkaz:
http://arxiv.org/abs/2205.12028
Publikováno v:
2021 IEEE Symposium Series on Computational Intelligence (SSCI)
Human shape estimation has become increasingly important both theoretically and practically, for instance, in 3D mesh estimation, distance garment production and computational forensics, to mention just a few examples. As a further specialization, \e
Externí odkaz:
http://arxiv.org/abs/2110.04064
Publikováno v:
In Food Research International May 2024 184
Autor:
Tejeda, Yansel Gonzalez, Mayer, Helmut
In this paper we present CALVIS, a method to calculate $\textbf{C}$hest, w$\textbf{A}$ist and pe$\textbf{LVIS}$ circumference from 3D human body meshes. Our motivation is to use this data as ground truth for training convolutional neural networks (CN
Externí odkaz:
http://arxiv.org/abs/2003.00834
Autor:
Mayer, Helmut
A core component of all Structure from Motion (SfM) approaches is bundle adjustment. As the latter is a computational bottleneck for larger blocks, parallel bundle adjustment has become an active area of research. Particularly, consensus-based optimi
Externí odkaz:
http://arxiv.org/abs/1910.08138
Autor:
Kissner, Michael, Mayer, Helmut
Many current methods to learn intuitive physics are based on interaction networks and similar approaches. However, they rely on information that has proven difficult to estimate directly from image data in the past. We aim to narrow this gap by infer
Externí odkaz:
http://arxiv.org/abs/1905.09891
Autor:
Kissner, Michael, Mayer, Helmut
Publikováno v:
41st German Conference, GCPR 2019, Proceedings
We follow the idea of formulating vision as inverse graphics and propose a new type of element for this task, a neural-symbolic capsule. It is capable of de-rendering a scene into semantic information feed-forward, as well as rendering it feed-backwa
Externí odkaz:
http://arxiv.org/abs/1905.08910
Publikováno v:
In Urban Climate July 2022 44