Perceptual completion is ubiquitous when estimating properties such as the shape, size, or number of objects in partially occluded scenes. Behavioral experiments showed that the number of hidden objects is underestimated in partially occluded scenes compared with an estimation based on the density of visible objects and the amount of occlusion. It is still unknown at which processing level this (under)estimation of the number of hidden objects occurs. We studied this question using a passive viewing task in which observers viewed a game board that was initially partially occluded and later was uncovered to reveal its hidden parts. We simultaneously measured the electroencephalographic responses to the partially occluded board presentation and its uncovering. We hypothesized that if the underestimation is a result of early sensory processing, it would be observed in the activities of P1 and N1, whereas if it is because of higher level processes such as expectancy, it would be reflected in P3 activities. Our data showed that P1 amplitude increased with numerosity in both occluded and uncovered states, indicating a link between P1 and simple stimulus features. The N1 amplitude was highest when both the initially visible and uncovered areas of the board were completely filled with game pieces, suggesting that the N1 component is sensitive to the overall Gestalt. Finally, we observed that P3 activity was reduced when the density of game pieces in the uncovered parts matched the initially visible parts, implying a relationship between the P3 component and expectation mismatch. Overall, our results suggest that inferences about the number of hidden items are reflected in high-level processing.
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PLoS One
January 2025
North China Institute of Aerospace Engineering, Langfang, China.
As the global economy expands, waterway transportation has become increasingly crucial to the logistics sector. This growth presents both significant challenges and opportunities for enhancing the accuracy of ship detection and tracking through the application of artificial intelligence. This article introduces a multi-object tracking system designed for unmanned aerial vehicles (UAVs), utilizing the YOLOv7 and Deep SORT algorithms for detection and tracking, respectively.
View Article and Find Full Text PDFPLoS One
January 2025
Department of Psychology, Tokyo Woman's Christian University, Tokyo, Japan.
We perceive and understand others' emotional states from multisensory information such as facial expressions and vocal cues. However, such cues are not always available or clear. Can partial loss of visual cues affect multisensory emotion perception? In addition, the COVID-19 pandemic has led to the widespread use of face masks, which can reduce some facial cues used in emotion perception.
View Article and Find Full Text PDFRetin Cases Brief Rep
December 2024
Vision and Ocular Health Research Group (VISOC) / Vision and Ocular Health Research Group (VISOC), Ophthalmology Service, Universidad del Valle, Hospital Universitario del Valle, Cali, Colombia.
Purpose: To describe a case of Wyburn-Mason syndrome in a young child with initially declined treatment leading to delayed intervention.
Methodology: Case report.
Results: We report a 6-year-old boy with mild periocular trauma following a fall, who was incidentally found to have a retinal arteriovenous malformation (AVM) associated with a brain AVM, indicative of Wyburn-Mason Syndrome.
PeerJ Comput Sci
October 2024
Department of Computer Science and Statistics, Universidad Rey Juan Carlos, Mostoles, Madrid, Spain.
Detecting people carrying firearms in outdoor or indoor scenes usually identifies (or avoids) potentially dangerous situations. Nevertheless, the automatic detection of these weapons can be greatly affected by the scene conditions. Commonly, in real scenes these firearms can be seen from different perspectives.
View Article and Find Full Text PDFCatheter Cardiovasc Interv
January 2025
Pediatrics & Medicine, Weill Cornell Medicine Chief International Patients Services & Chair, Sidra Department Cardiovascular Diseases, University of Jordan, Amman, Jordan.
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