50 Years of object recognition: Directions forward

By Alexander Andreopoulos, John K. Tsotsos. 2013

344 citations recorded by the source corpus.

Subfields: Computer Vision and Pattern Recognition

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In Computer Vision and Pattern Recognition

Citations in the corpus

A Survey of Autonomous Driving: Common Practices and Emerging Technologies (2019, background): “There exists a number of extensive surveys on general image-based object detection [132]– [134].”
STNet: Selective Tuning of Convolutional Networks for Object Localization (2017, background): “In recent years, while the learning approaches have been matured, various models and algorithms have been developed to present a richer visual representation for various visual tasks such as object classification and detection, semantic segmentation, action recognition, and scene understanding [1, 7”
Automatic moth detection from trap images for pest management (2016, methodology): “Various methods and datasets [29, 30] have been proposed in the last several decades to push this area forward.”
TrueNorth: Design and Tool Flow of a 65 mW 1 Million Neuron Programmable Neurosynaptic Chip (2015, background): “salient targets in the field of view [39].”
Deep Learning for Generic Object Detection: A Survey (2018, background): “11 50 Years of Object Recognition: Directions Forward [5] 2013 CVIU A review of the evolution of object recognition systems in the last five decades”
Learning to Look Around: Intelligently Exploring Unseen Environments for Unknown Tasks (2017, background): “Recent work considers tasks such as active object localization [4, 10, 17, 21, 32,45,46,56,77], action detection in video [73], and object recognition [3,29,31,43] including foveated vision systems that selectively obtain higher resolution data [9, 20, 53].”
A Survey on Object Detection in Optical Remote Sensing Images (2016, methodology): “n systems. Here we mainly focus on reviewing some widely used features for object detection in optical RSIs. Some reviews on feature extraction and feature coding in computer vision are available in (Andreopoulos and Tsotsos, 2013; Huang et al., 2014; Li et al., 2015c). 6.1.1 Histogram of oriented g”