However, to what extent the outlined scheme of neural processing of orthographic information also holds true in the case of natural reading has remained an open question. This is because previous studies that were aiming at investi- gating neural processes of natural reading were focusing on ...
Visual representation learning is ubiquitous in various real-world applications, including visual comprehension, video understanding, multi-modal analysis,
The binary image is then skeletonized (see Figure 1c) to determine the graph representation of the plant, as shown in Figure 1d. Figure 1e shows each detected leaf is marked with a distinct color. Finally, Figure 1f shows each leaf numbered in order of emergence. The proposed method ...
[21] tried to find a user's workplace area based on PBS data, and adopted three density-estimation algorithms to label a scope around an individual workplace. Their method required a known personal home location in advance and only detected the work-place location. The visual representation ...
Shan, G.: Color image denoising via monogenic matrix-based sparse representation. Vis. Comput. 2, 1–14 (2017) Google Scholar Sobral, A., Bouwmans, T., Zahzah, E.H.: LRSLibrary: Low-rank and sparse tools for background modeling and subtraction in videos. In: Robust Low-Rank and ...
The contributions of the paper provide an original framework for characterizing deformation properties (and stages of deformation) of an object under interaction with a robot hand using RGB-D data. The original application of the fast level set method in the log-polar representation of the color ...
s= u1 u2 ∼ N {s¯, S} = N u¯ 1 u¯ 2 , U0 0U The probability density function for infinite lines like Plücker, N ¯l, L , is composed of the homogeneous line representation and the covariance matrix defined as follows: ¯l = u¯ 1 × u¯ 2, and L = [u...