Visuelle Wahrnehmung

Quiz Fragen zu der Vorlesung

Quiz Fragen zu der Vorlesung


L. M.
This flashcard set delves into the intricate world of visual perception at a university level, focusing on object recognition, color theory, and the underlying models and systems that govern how we interpret visual stimuli. It explores various theories and models, such as the HMO model, recognition-by-components, and view-based models, highlighting their strengths and limitations. The flashcards are particularly useful for students and researchers in computer science and cognitive psychology, offering insights into how the human visual system processes and recognizes objects, scenes, and colors, and how these processes can be replicated or understood through computational models.
Karten
151
Lernende
2
Sprache
Englisch
Kategorie
Informatik
Stufe
Universität
Erstellt / Aktualisiert
01.11.2017 / 27.01.2018

Lernkarten

8: Viewpoint invariance refers to the idea that

objects schould be just as easy to recognize from any viewpoint

8: Yasmins and colleagues from the DiCarlo lab at MIT published an artivle in 2014 in which the presented their HMO model, standing for ---

hierarchical modular optimization

8: Yasmins and colleagues from the DiCarlo lab at MIT published an artivle in 2014 in which the presented their HMO model, standing for hierarchical modular optimization.

The HMO model belongs in the larger class of --- models, standing for --- model.

DNN

deep neural network

8: Yasmins and colleagues from the DiCarlo lab at MIT published an artivle in 2014 in which the presented their HMO model, standing for hierarchical modular optimization.

The HMO model's essential architectural characteristic is its --- : There are, for example, many --- connections and different parameter ---.

heteroogeneity

bypass

settings even at the same level

8: Yasmins and colleagues from the DiCarlo lab at MIT published an artivle in 2014 in which the presented their HMO model, standing for hierarchical modular optimization.

---, the basic operations performed locally are --- troughout the network.

However

the same

8: Yasmins and colleagues from the DiCarlo lab at MIT published an artivle in 2014 in which the presented their HMO model, standing for hierarchical modular optimization.

In the Yamins et al. (2014) article they report a large-scale modelling effort, evaluating around ---. Yamins et al. compared their models both to the response of cells in IT cortex (roughly N = --- cells) as well as on how well the models categorized a set of images (roughly N = --- images). One central finding was that models optimized for --- were also superior at --- .

5000DNN architectures

300 oder 100

6.000

categorization performance

explaining variance in IT

 

8: Yasmins and colleagues from the DiCarlo lab at MIT published an artivle in 2014 in which the presented their HMO model, standing for hierarchical modular optimization.

In order to obtain a categorization performance from the HMO model, a --- decoder was --- the activity of units at the --- level(s) of the HMO network. Using such a procedure, the HMO model's performance was --- than that of --- models of object recognition on the difficult  --- variation task.

linear

trained on

highest

better

both computer vision and neuronally inspired

high

Lernen