AIMC Topic: Pattern Recognition, Visual
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Neural correlates of the uncanny valley effect for robots and hyper-realistic masks.
PloS one
Mar 18, 2025
Viewing artificial objects and images that are designed to appear human can elicit a sense of unease, referred to as the 'uncanny valley' effect. Here we investigate neural correlates of the uncanny valley, using still images of androids (robots desi...
Configural processing as an optimized strategy for robust object recognition in neural networks.
Communications biology
Mar 7, 2025
Configural processing, the perception of spatial relationships among an object's components, is crucial for object recognition, yet its teleology and underlying mechanisms remain unclear. We hypothesize that configural processing drives robust recogn...
Bio-inspired two-stage network for efficient RGB-D salient object detection.
Neural networks : the official journal of the International Neural Network Society
Feb 7, 2025
Recently, with the development of the Convolutional Neural Network and Vision Transformer, the detection accuracy of the RGB-D salient object detection (SOD) model has been greatly improved. However, most of the existing methods cannot balance comput...
Human-like face pareidolia emerges in deep neural networks optimized for face and object recognition.
PLoS computational biology
Jan 27, 2025
The human visual system possesses a remarkable ability to detect and process faces across diverse contexts, including the phenomenon of face pareidolia--seeing faces in inanimate objects. Despite extensive research, it remains unclear why the visual ...
DCTCNet: Sequency discrete cosine transform convolution network for visual recognition.
Neural networks : the official journal of the International Neural Network Society
Jan 18, 2025
The discrete cosine transform (DCT) has been widely used in computer vision tasks due to its ability of high compression ratio and high-quality visual presentation. However, conventional DCT is usually affected by the size of transform region and res...
Exploring neural architectures for simultaneously recognizing multiple visual attributes.
Scientific reports
Dec 3, 2024
Much experimental evidence in neuroscience has suggested a division of higher visual processing into a ventral pathway specialized for object recognition and a dorsal pathway specialized for spatial recognition. Previous computational studies have su...
Parallel development of object recognition in newborn chicks and deep neural networks.
PLoS computational biology
Dec 2, 2024
How do newborns learn to see? We propose that visual systems are space-time fitters, meaning visual development can be understood as a blind fitting process (akin to evolution) in which visual systems gradually adapt to the spatiotemporal data distri...
Spike-VisNet: A novel framework for visual recognition with FocusLayer-STDP learning.
Neural networks : the official journal of the International Neural Network Society
Nov 26, 2024
Current vision-inspired spiking neural networks (SNNs) face key challenges due to their model structures typically focusing on single mechanisms and neglecting the integration of multiple biological features. These limitations, coupled with limited s...
Plant-based egg washes for use in baked goods: Machine learning and visual parameter analysis.
Journal of food science
Sep 27, 2024
Pea protein is one potential environmentally sustainable way of recreating the functionality of eggs in coatings for baked goods. These coatings are commonly applied to enhance visual properties of baked goods that consumers desire, especially color ...
Visual search and real-image similarity: An empirical assessment through the lens of deep learning.
Psychonomic bulletin & review
Sep 26, 2024
The ability to predict how efficiently a person finds an object in the environment is a crucial goal of attention research. Central to this issue are the similarity principles initially proposed by Duncan and Humphreys, which outline how the similari...
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