Ultra-Fast Categorization

Retinotopy improves the categorisation and localisation of visual objects in CNNs
as was presented at the 32nd International Conference on Artificial Neural Networks (ICANN 2023) in Heraklion (Greece). this proceedings paper follows up the poster presented in : Jean-Nicolas Jeremie, Emmanuel Dauce, Laurent U Perrinet (2023).
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Ultra-Fast Image Categorization in biology and in neural models
Humans are able to robustly categorize images and can, for instance, detect the presence of an animal in a briefly flashed image in as …
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Ultra-Fast Image Categorization in biology and in neural models
Retinotopy improves the categorisation and localisation of visual objects in CNNs
as was presented at the Computational Cognitive Neuroscience Society Meeting 2023 in Oxford see a follow-up presentation in: Jean-Nicolas Jeremie, Emmanuel Dauce, Laurent U Perrinet (2023). Retinotopy improves the categorisation and localisation of visual objects in CNNs.
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Ultra-rapid visual search in natural images using active deep learning
👉🏼 Jean-Nicolas Jérémie @JnJerem 📍Poster session at #FENS2022 🎯 Ultra-rapid visual search in natural images using active deep learning.#FENSAmbassador @SocNeuro_Tweets @laurentperrinet 1/2 pic.twitter.com/ldGJMCQb4c — Mélina Cordeau (@CordeauMelina) July 11, 2022 This work extends to natural scenes a previous work on visual search on a simplified task formulated in Emmanuel Dauce, Pierre Albigès, Laurent U Perrinet (2020).
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Ultra-rapid visual search in natural images using active deep learning
Ultra-rapid visual search in natural images using active deep learning
Visual search, that is, the simultaneous localization and detection of a visual target of interest, is a vital task. Applied to the …
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Ultra-rapid visual search in natural images using active deep learning