AIMC Topic: Visual Perception
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Predicting Single Neuron Responses of the Primary Visual Cortex with Deep Learning Model.
Advanced science (Weinheim, Baden-Wurttemberg, Germany)
Feb 13, 2024
Modeling neuron responses to stimuli can shed light on next-generation technologies such as brain-chip interfaces. Furthermore, high-performing models can serve to help formulate hypotheses and reveal the mechanisms underlying neural responses. Here ...
Using deep neural networks to disentangle visual and semantic information in human perception and memory.
Nature human behaviour
Feb 8, 2024
Mental representations of familiar categories are composed of visual and semantic information. Disentangling the contributions of visual and semantic information in humans is challenging because they are intermixed in mental representations. Deep neu...
Language with vision: A study on grounded word and sentence embeddings.
Behavior research methods
Dec 19, 2023
Grounding language in vision is an active field of research seeking to construct cognitively plausible word and sentence representations by incorporating perceptual knowledge from vision into text-based representations. Despite many attempts at langu...
End-To-End Deep Neural Network for Salient Object Detection in Complex Environments.
Journal of visualized experiments : JoVE
Dec 15, 2023
Salient object detection has emerged as a burgeoning area of interest within the realm of computer vision. However, prevailing algorithms exhibit diminished precision when tasked with detecting salient objects within intricate and multifaceted enviro...
How well do rudimentary plasticity rules predict adult visual object learning?
PLoS computational biology
Dec 11, 2023
A core problem in visual object learning is using a finite number of images of a new object to accurately identify that object in future, novel images. One longstanding, conceptual hypothesis asserts that this core problem is solved by adult brains t...
Thinking beyond the ventral stream: Comment on Bowers et al.
The Behavioral and brain sciences
Dec 6, 2023
Bowers et al. rightly emphasise that deep learning models often fail to capture constraints on visual perception that have been discovered by previous research. However, the solution is not to discard deep learning altogether, but to design stimuli a...
A deep new look at color.
The Behavioral and brain sciences
Dec 6, 2023
Bowers et al. counter deep neural networks (DNNs) as good models of human visual perception. From our color perspective we feel their view is based on three misconceptions: A misrepresentation of the state-of-the-art of color perception; the type of ...
Neural networks need real-world behavior.
The Behavioral and brain sciences
Dec 6, 2023
Bowers et al. propose to use controlled behavioral experiments when evaluating deep neural networks as models of biological vision. We agree with the sentiment and draw parallels to the notion that "neuroscience needs behavior." As a promising path f...
Modelling human vision needs to account for subjective experience.
The Behavioral and brain sciences
Dec 6, 2023
Vision is inseparably connected to perceptual awareness which can be seen as the culmination of sensory processing. Studies on conscious vision reveal that object recognition is just one of the means through which our representation of the world is b...
Hierarchies in Visual Pathway: Functions and Inspired Artificial Vision.
Advanced materials (Deerfield Beach, Fla.)
Nov 30, 2023
The development of artificial intelligence has posed a challenge to machine vision based on conventional complementary metal-oxide semiconductor (CMOS) circuits owing to its high latency and inefficient power consumption originating from the data shu...
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