The spatial contrast sensitivity (CSF) of the chicken has been measured using a behavioural technique. The results obtained show that spatial vision in this species is relatively poor compared with the human observer. For a visual stimulus luminance of 16 c dm(-2), the upper frequency limit of spatial vision in the chicken (acuity) was found to be about 7.0 c deg(-1), with peak spatial vision occurring at around 1.0 c deg(-1). Under equivalent stimulus conditions, the acuity of the human is around 50 c deg(-1) with a peak in spatial vision at about 3.0 c deg(-1). Peak spatial contrast sensitivity in the chicken was also found to be only about 2% that for the human. At a lower stimulus luminance of 0.1 c dm(-2), the chicken CSF reduced in overall magnitude and indicated an acuity level of about 5.0 c deg(-1). These experimental results were successfully modelled using modulation transfer (MTF) theory. This theoretical treatment enabled important neural mechanisms underlying spatial vision in the chicken to be revealed. The role played by spatial vision in the chicken's ability to recognise detailed shapes in its visual environment was also examined by deploying the CSF as a visual weighting function with the Fourier series of a chicken comb.
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http://dx.doi.org/10.1016/j.visres.2009.02.019 | DOI Listing |
Biomed Phys Eng Express
January 2025
Shandong University, No. 72, Binhai Road, Jimo, Qingdao City, Shandong Province, Qingdao, 266200, CHINA.
U-Net is widely used in medical image segmentation due to its simple and flexible architecture design. To address the challenges of scale and complexity in medical tasks, several variants of U-Net have been proposed. In particular, methods based on Vision Transformer (ViT), represented by Swin UNETR, have gained widespread attention in recent years.
View Article and Find Full Text PDFInt Conf Indoor Position Indoor Navig
October 2024
Computer Science and Engineering, University of California, Santa Cruz, Santa Cruz, United States.
In this paper, we present PALMS, an innovative indoor global localization and relocalization system for mobile smartphones that utilizes publicly available floor plans. Unlike most vision-based methods that require constant visual input, our system adopts a dynamic form of localization that considers a single instantaneous observation and odometry data. The core contribution of this work is the introduction of a particle filter initialization method that leverages the Certainly Empty Space (CES) constraint along with principal orientation matching.
View Article and Find Full Text PDFFront Plant Sci
January 2025
School of Computer Science and Technology, Henan Institute of Science and Technology, Xinxiang, China.
Introduction: With the advent of technologies such as deep learning in agriculture, a novel approach to classifying wheat seed varieties has emerged. However, some existing deep learning models encounter challenges, including long processing times, high computational demands, and low classification accuracy when analyzing wheat seed images, which can hinder their ability to meet real-time requirements.
Methods: To address these challenges, we propose a lightweight wheat seed classification model called LWheatNet.
Eur J Neurosci
January 2025
Pavlov Institute of Physiology RAS, Saint-Petersburg, Russia.
The "oblique effect" refers to the reduced visual performance for stimuli presented at oblique orientations compared to those at cardinal orientations. In the cortex, neurons that respond to specific orientations are organized into orientation columns. This raises the question: Are the orientation signals in the iso-orientation columns associated with cardinal orientations the same as those in the iso-orientation columns associated with oblique orientations, and is this signal influenced by experience? To explore this, iso-orientation columns in visual area 18 were examined using optical imaging techniques.
View Article and Find Full Text PDFJ Alzheimers Dis
January 2025
Health and Biosecurity, Commonwealth Scientific and Industrial Research Organisation, Brisbane, QLD, Australia.
Background: The introduction of therapeutics for Alzheimer's disease has led to increased interest in precisely quantifying amyloid-β (Aβ) burden for diagnosis, treatment monitoring, and further clinical research. Recent positron emission tomography (PET) hardware innovations including digital detectors have led to superior resolution and sensitivity, improving quantitative accuracy. However, the effect of PET scanner on Centiloid remains relatively unexplored and is assumed to be minimized by harmonizing PET resolutions.
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