1,672 research outputs found
Learning motion: Human vs. optimal Bayesian learner
We used the optimal perceptual learning paradigm (Eckstein, Abbey, Pham, & Shimozaki, 2004) to investigate the dynamics of human rapid learning processes in motion discrimination tasks and compare it to an optimal Bayesian learner. This paradigm consists of blocks of few trials defined by a set of target attributes, and it has been shown its ability to detect learning effects appearing as soon as after the first trial. In the present task a sequence consisting of four patches containing random-dot patterns is presented at four separate locations equidistant from a fixation point. On each trial, the random dots in three patches moved with a mean speed and the fourth, target patch, could move either with slower or faster mean speed. Observers' task was to indicate what speed, faster or slower, was present in the display. The mean direction of the target patch was kept invariant along a block of trials. Observers learned the target relevant motion direction through indirect feedback, leading to an improvement in speed identification performance ranging from 15% to 30% which is greater than previously studied contrast defined targets and faces. However, comparison to an ideal learner revealed incomplete or partial learning for the motion task which was lower than previously measured for contrast defined targets and faces. A sub-optimal model that included inefficiencies in the updating of motion direction weights due to memory effects could account for the human learning. Finally, the similarity of the rapid learning effect observed here for motion perception with that found for contrast defined targets for localization and identification tasks could be suggesting a general strategy for learning in the human visual system and some common limitations such as memory.Fil: Trenti, Edgardo Javier. Universidad Nacional de Salta. Facultad de Ciencias Exactas; ArgentinaFil: Barraza, Jose Fernando. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tucumán. Instituto de Investigación en Luz, Ambiente y Visión. Universidad Nacional de Tucumán. Facultad de Ciencias Exactas y Tecnología. Instituto de Investigación en Luz, Ambiente y Visión; ArgentinaFil: Eckstein, Miguel P.. University of California; Estados Unido
Object Detection Through Exploration With A Foveated Visual Field
We present a foveated object detector (FOD) as a biologically-inspired
alternative to the sliding window (SW) approach which is the dominant method of
search in computer vision object detection. Similar to the human visual system,
the FOD has higher resolution at the fovea and lower resolution at the visual
periphery. Consequently, more computational resources are allocated at the
fovea and relatively fewer at the periphery. The FOD processes the entire
scene, uses retino-specific object detection classifiers to guide eye
movements, aligns its fovea with regions of interest in the input image and
integrates observations across multiple fixations. Our approach combines modern
object detectors from computer vision with a recent model of peripheral pooling
regions found at the V1 layer of the human visual system. We assessed various
eye movement strategies on the PASCAL VOC 2007 dataset and show that the FOD
performs on par with the SW detector while bringing significant computational
cost savings.Comment: An extended version of this manuscript was published in PLOS
Computational Biology (October 2017) at
https://doi.org/10.1371/journal.pcbi.100574
Evolution and Optimality of Similar Neural Mechanisms for Perception and Action during Search
A prevailing theory proposes that the brain's two visual pathways, the ventral and dorsal, lead to differing visual processing and world representations for conscious perception than those for action. Others have claimed that perception and action share much of their visual processing. But which of these two neural architectures is favored by evolution? Successful visual search is life-critical and here we investigate the evolution and optimality of neural mechanisms mediating perception and eye movement actions for visual search in natural images. We implement an approximation to the ideal Bayesian searcher with two separate processing streams, one controlling the eye movements and the other stream determining the perceptual search decisions. We virtually evolved the neural mechanisms of the searchers' two separate pathways built from linear combinations of primary visual cortex receptive fields (V1) by making the simulated individuals' probability of survival depend on the perceptual accuracy finding targets in cluttered backgrounds. We find that for a variety of targets, backgrounds, and dependence of target detectability on retinal eccentricity, the mechanisms of the searchers' two processing streams converge to similar representations showing that mismatches in the mechanisms for perception and eye movements lead to suboptimal search. Three exceptions which resulted in partial or no convergence were a case of an organism for which the targets are equally detectable across the retina, an organism with sufficient time to foveate all possible target locations, and a strict two-pathway model with no interconnections and differential pre-filtering based on parvocellular and magnocellular lateral geniculate cell properties. Thus, similar neural mechanisms for perception and eye movement actions during search are optimal and should be expected from the effects of natural selection on an organism with limited time to search for food that is not equi-detectable across its retina and interconnected perception and action neural pathways
A signal detection model predicts the effects of set size on visual search accuracy for feature, conjunction, triple conjunction, and disjunction displays
Studies of and production in and Pb collisions
The production of and mesons is studied in proton-proton and
proton-lead collisions collected with the LHCb detector. Proton-proton
collisions are studied at center-of-mass energies of and ,
and proton-lead collisions are studied at a center-of-mass energy per nucleon
of . The studies are performed in center-of-mass rapidity
regions (forward rapidity) and
(backward rapidity) defined relative to the proton beam direction. The
and production cross sections are measured differentially as a function
of transverse momentum for and , respectively. The differential cross sections are used to
calculate nuclear modification factors. The nuclear modification factors for
and mesons agree at both forward and backward rapidity, showing
no significant evidence of mass dependence. The differential cross sections of
mesons are also used to calculate cross section ratios,
which show evidence of a deviation from the world average. These studies offer
new constraints on mass-dependent nuclear effects in heavy-ion collisions, as
well as and meson fragmentation.Comment: All figures and tables, along with machine-readable versions and any
supplementary material and additional information, are available at
https://lhcbproject.web.cern.ch/Publications/p/LHCb-PAPER-2023-030.html (LHCb
public pages
Observation of Cabibbo-suppressed two-body hadronic decays and precision mass measurement of the baryon
The first observation of the singly Cabibbo-suppressed
and decays
is reported, using proton-proton collision data at a centre-of-mass energy of
, corresponding to an integrated luminosity of , collected with the LHCb detector between 2016 and 2018. The
branching fraction ratios are measured to be
,
. In addition, using the
decay channel, the baryon
mass is measured to be , improving the
precision of the previous world average by a factor of four.Comment: All figures and tables, along with any supplementary material and
additional information, are available at
https://cern.ch/lhcbproject/Publications/p/LHCb-PAPER-2023-011.html (LHCb
public pages
- …