AI Medical Compendium Journal:
Journal of vision

Showing 11 to 20 of 42 articles

The developmental trajectory of object recognition robustness: Children are like small adults but unlike big deep neural networks.

Journal of vision
In laboratory object recognition tasks based on undistorted photographs, both adult humans and deep neural networks (DNNs) perform close to ceiling. Unlike adults', whose object recognition performance is robust against a wide range of image distorti...

When will AI misclassify? Intuiting failures on natural images.

Journal of vision
Machine recognition systems now rival humans in their ability to classify natural images. However, their success is accompanied by a striking failure: a tendency to commit bizarre misclassifications on inputs specifically selected to fool them. What ...

Important feature identification for perceptual sex of point-light walkers using supervised machine learning.

Journal of vision
The present study aimed to elucidate the dynamic features that are highly predictive in the biological and perceptual sex classification of point-light walkers (PLWs) and how these features behave in sex classification using supervised machine learni...

Can deep convolutional neural networks support relational reasoning in the same-different task?

Journal of vision
Same-different visual reasoning is a basic skill central to abstract combinatorial thought. This fact has lead neural networks researchers to test same-different classification on deep convolutional neural networks (DCNNs), which has resulted in a co...

Identifying specular highlights: Insights from deep learning.

Journal of vision
Specular highlights are the most important image feature for surface gloss perception. Yet, recognizing whether a bright patch in an image is due to specular reflection or some other cause (e.g., texture marking) is challenging, and it remains unclea...

Could simplified stimuli change how the brain performs visual search tasks? A deep neural network study.

Journal of vision
Visual search is a complex behavior influenced by many factors. To control for these factors, many studies use highly simplified stimuli. However, the statistics of these stimuli are very different from the statistics of the natural images that the h...

Contrast sensitivity functions in autoencoders.

Journal of vision
Three decades ago, Atick et al. suggested that human frequency sensitivity may emerge from the enhancement required for a more efficient analysis of retinal images. Here we reassess the relevance of low-level vision tasks in the explanation of the co...

DeepGaze III: Modeling free-viewing human scanpaths with deep learning.

Journal of vision
Humans typically move their eyes in "scanpaths" of fixations linked by saccades. Here we present DeepGaze III, a new model that predicts the spatial location of consecutive fixations in a free-viewing scanpath over static images. DeepGaze III is a de...

Distinguishing mirror from glass: A "big data" approach to material perception.

Journal of vision
Distinguishing mirror from glass is a challenging visual inference, because both materials derive their appearance from their surroundings, yet we rarely experience difficulties in telling them apart. Very few studies have investigated how the visual...

From photos to sketches - how humans and deep neural networks process objects across different levels of visual abstraction.

Journal of vision
Line drawings convey meaning with just a few strokes. Despite strong simplifications, humans can recognize objects depicted in such abstracted images without effort. To what degree do deep convolutional neural networks (CNNs) mirror this human abilit...