Machine vision - theory, algorithms, practicalities

2004

294 citations recorded by the source corpus.

Subfields: Computer Vision and Pattern Recognition

View Paper: https://www.semanticscholar.org/paper/b4e30bcea2b040c1ab035257c97adba1c9562fd5

Citations in the corpus

• Towards perceptual shared autonomy for robotic mobile manipulation (2011, unknown): “For example, reliable interpretation of images is still a largely unsolved research problem [19].”
• Learning monocular reactive UAV control in cluttered natural environments (2012, unknown): “2) In addition to the lack of feedback, providing the correct actions in real-time after the first iteration when the drone is in control can be hard for the pilot as he must react to what the drone is doing and not what he expects to happen: e.g., if the drone suddenly starts turning towards a tree…”
• False discovery rate revisited: FDR and topological inference using Gaussian random fields (2009, unknown): “These are reminiscent of the models used in “ image-restoration ” (Rosenfeld and Kak,1976) and machine-vision problems (Davies, 2005); however they are not appropriate models of distributed signals ( e.g ., neuronal activations).”
• Dynamic clustering using particle swarm optimization with application in image segmentation (2006, unknown): “The K-means algorithm suffers from the following drawbacks [18]:”