26 citations · 78 across the 18 of their papers we have counts for
7 papers · 1 filter
A Possible Reason for why Data-Driven Beats Theory-Driven Computer Vision
John K. Tsotsos, Iuliia Kotseruba, Alexander Andreopoulos +1
Why do some continue to wonder about the success and dominance of deep learning methods in computer vision and AI? Is it not enough that these methods provide practical solutions t…
Scene Classification in Indoor Environments for Robots using Context Based Word Embeddings
Bao Xin Chen, Raghavender Sahdev, Dekun Wu +3
Scene Classification has been addressed with numerous techniques in computer vision literature. However, with the increasing number of scene classes in datasets in the field, it ha…
Multiplicative modulations in hue-selective cells enhance unique hue representation
Paria Mehrani, Andrei Mouraviev, John K. Tsotsos
There is still much to understand about the color processing mechanisms in the brain and the transformation from cone-opponent representations to perceptual hues. Moreover, it is u…
Fast Visual Object Tracking with Rotated Bounding Boxes
Bao Xin Chen, John K. Tsotsos
In this paper, we demonstrate a novel algorithm that uses ellipse fitting to estimate the bounding box rotation angle and size with the segmentation(mask) on the target for online…
High-Level Perceptual Similarity is Enabled by Learning Diverse Tasks
Amir Rosenfeld, Richard Zemel, John K. Tsotsos
Predicting human perceptual similarity is a challenging subject of ongoing research. The visual process underlying this aspect of human vision is thought to employ multiple differe…
Rapid Visual Categorization is not Guided by Early Salience-Based Selection
John K. Tsotsos, Iuliia Kotseruba, Calden Wloka
The current dominant visual processing paradigm in both human and machine research is the feedforward, layered hierarchy of neural-like processing elements. Within this paradigm, v…