AIMC Topic: Visual Perception

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A Visual Dataset for Anomaly Detection in Self-Driving Laboratories.

Scientific data
Self-driving laboratories accelerate the application of the scientific method and the discovery process through high-throughput experimentation, intelligent perception and planning, and effective human-robot collaboration. However, detecting anomalie...

Emergent neuronal mechanisms mediating covert attention in convolutional neural networks.

Proceedings of the National Academy of Sciences of the United States of America
Covert visual attention allows the brain to select different regions of the visual world without eye movements. Predictive cues of a target location orient covert attention and improve perceptual performance. In most computational models, researchers...

Dynamic reorganization of functional networks underlying audiovisual interactions.

Scientific reports
Crossmodal interactions involve crosstalk between different cortical areas and dynamic recruitment of regions, which is crucial for integrating sensory information into a coherent percept. Despite their significance, the dynamic cortical networks und...

Distinct Portions of Superior Temporal Sulcus Combine Auditory Representations with Different Visual Streams.

The Journal of neuroscience : the official journal of the Society for Neuroscience
In humans, the superior temporal sulcus (STS) combines auditory and visual information. However, the extent to which it relies on visual information from the ventral or dorsal stream remains uncertain. To address this, we analyzed open-source functio...

From biological vision to artificial intelligence: The role of foundational predictive processing.

The Behavioral and brain sciences
This commentary integrates Coombs and Trestman's trait-linkage hypothesis with Teufel and Fletcher's neurocomputational predictive framework to propose that high-resolution visual systems operate as intrinsic bottom-up predictive mechanisms. By mergi...

Decoding covert visual attention of electroencephalography signals using continuous wavelet transform and deep learning approach.

Scientific reports
Covert visual attention decoding from EEG signals is a key challenge in cognitive neuroscience and brain-computer interface applications. Traditional approaches often rely on manual feature extraction and handcrafted pipelines, which limit scalabilit...

Image complexity-based fMRI-BOLD visual network categorization across visual datasets using topological descriptors and deep-hybrid learning.

Scientific reports
This study proposes a new approach that investigates differences in topological characteristics of visual networks, which are constructed using fMRI BOLD time-series corresponding to visual datasets of COCO, ImageNet, and SUN. A publicly available BO...

Recurrent issues with deep neural network models of visual recognition.

Scientific reports
Object recognition requires flexible and robust information processing, especially in view of the challenges posed by naturalistic visual settings. The ventral stream in visual cortex is provided with this robustness by its recurrent connectivity. Re...

Study on rural landscape design strategies integrating computer vision and deep learning: an analysis based on human perception and visual aesthetics.

Scientific reports
With the increasing application of artificial intelligence in environmental design, computer vision and deep learning have emerged as crucial tools for understanding human visual perception. This study focuses on rural landscapes and proposes a visua...

Beyond Divisive Normalization: Scalable Feedforward Networks for Multisensory Integration Across Reference Frames.

The Journal of neuroscience : the official journal of the Society for Neuroscience
The integration of multiple sensory inputs is essential for human perception and action in uncertain environments. This process includes reference frame transformations as different sensory signals are encoded in different coordinate systems. Studies...