Modeling cognition (neural, behavioural signals)
Modeling cognition (neural, behavioural signals)
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We show that generic object recognition mechanisms in the macaque Inferior temporal cortex are capable of decoding word and letter shapes. We also show that this code is compositional in nature. Analysis was done on single unit as well as population level neural activity
Harish Katti; S. P. Arun, Monkeys can’t read but their brains can: Compositionality and CAPTCHA decoding in IT neurons. Vision: Representation of Objects and Scenes, Annual meeting of the Society for Neuroscience, San Diego, USA, 2018 (Oral presentation at SfN 2018, manuscript in preperation)
A separable neural code in monkey IT enables perfect CAPTCHA decoding H Katti, SP Arun Journal of Neurophysiology 127 (4), 869-884
We modeled accuracy information in a hard face classification task.
Harish Katti; S. P. Arun, Are you from North or South India? A hard face-classification task reveals systematic representational differences between humans and machines Journal of Vision. 2019;19(7):1 doi:10.1167/19.7.1, Code and dataset: https://github.com/harish2006/IISCIFD
In an effort to combine audio-visual content information with EEG signals, we characterized the potential of EEG information to infer affective states of human viewers.
A Shukla, SS Gullapuram, H Katti, M Kankanhalli, S Winkler, S Ramanathan, Recognition of Advertisement Emotions with Application to Computational Advertising,arXiv preprint arXiv:1904.01778 (research article, under review)
We modeled speed and accuracy in rapid object detection in naturalistic scenes. In a related work we modeled human expectations for the presence of target objects (cars, people) in natural scenes.
H Katti, MV Peelen, SP Arun, Machine vision benefits from human contextual expectations, Scientific reports 9 (1), 2112 (research article) Code and dataset: https://github.com/harish2006/cntxt_likelihood
H Katti, MV Peelen, SP Arun, How do targets, nontargets, and scene context influence real-world object detection? Attention, Perception, & Psychophysics 79 (7), 2021-2036 (research article)
We characterized accuracy information when subjects performed a rapid aesthetics judgement task.
H Katti, KY Bin, TS Chua, M Kankanhalli, Pre-attentive discrimination of interestingness in images, 2008 IEEE International Conference on Multimedia and Expo, 1433-1436 (research article)
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