A neural and computational model for the chromatic control of accommodation

1990 ◽  
Vol 5 (6) ◽  
pp. 547-555 ◽  
Author(s):  
D. I. Flitcroft
Keyword(s):  
Image Quality ◽  
Computational Model ◽  
Cortical Neurons ◽  
Chromatic Aberration ◽  
Refractive State ◽  
Spatial Frequencies ◽  
Proposed Model ◽  
Band Pass ◽  
Chromatic Cues ◽  
Chromatic Processing

AbstractAccommodation is more accurate with polychromatic stimuli than with narrowband or monochromatic stimuli. The aim of this paper is to develop a computational model for how the visual system uses the extra information in polychromatic stimuli to increase the accuracy of accommodation responses. The proposed model is developed within the context of both trichromacy and also the organization of spatial and chromatic processing within the visual cortex.The refractive error present in the retinal image can be estimated by comparing image quality with and without small additional changes in refractive state. In polychromatic light, the chromatic aberration of the eye results in differences in ocular refractive power for light of different wavelengths. As a result, the refractive state of the eye can be estimated by comparing image quality in the three types of cone photoreceptor. The ability of cortical neurons to perform such comparisons on image quality with a crude form of spatial-frequency analysis is examined theoretically. It is found that spatially band-pass chromatically opponent neurons (that may correspond to double opponent neurons) can perform such calculations and that chromatic cues to accommodation are extracted most effectively by neurons responding to spatial frequencies of between 2 and 8 cycles/deg.

Observability of Very Thick Specimen by Using Transmission Scanning Electron Microscope

1971 ◽  
Vol 29 ◽  
pp. 26-27
Author(s):  
K. Shibatomi ◽  
T. Yamanoto ◽  
H. Koike
Keyword(s):  
Electron Microscope ◽  
Image Quality ◽  
Scanning Electron Microscope ◽  
Chromatic Aberration ◽  
Image Contrast ◽  
Objective Lens ◽  
Thick Specimen ◽  
Transmission Electron ◽  
Scanning Electron

In the observation of a thick specimen by means of a transmission electron microscope, the intensity of electrons passing through the objective lens aperture is greatly reduced. So that the image is almost invisible. In addition to this fact, it have been reported that a chromatic aberration causes the deterioration of the image contrast rather than that of the resolution. The scanning electron microscope is, however, capable of electrically amplifying the signal of the decreasing intensity, and also free from a chromatic aberration so that the deterioration of the image contrast due to the aberration can be prevented. The electrical improvement of the image quality can be carried out by using the fascionating features of the SEM, that is, the amplification of a weak in-put signal forming the image and the descriminating action of the heigh level signal of the background. This paper reports some of the experimental results about the thickness dependence of the observability and quality of the image in the case of the transmission SEM.

scholarly journals UCAN: A Learning-based Model to Enhance Poorly Exposed Images

2020 ◽  
Author(s):  
Lucas R. V. Messias ◽  
Cristiano R. Steffens ◽  
Paulo L. J. Drews-Jr ◽  
Silvia S. C. Botelho
Keyword(s):  
Image Quality ◽  
Image Enhancement ◽  
Dynamic Range ◽  
Low Contrast ◽  
Qualitative And Quantitative ◽  
Fast Learning ◽  
Proposed Model ◽  
Quantitative Results ◽  
Critical Process ◽  
Poor Lighting

Image enhancement is a critical process in imagebased systems. In these systems, image quality is a crucial factor to achieve a good performance. Scenes with a dynamic range above the capability of the camera or poor lighting are challenging conditions, which usually result in low contrast images, and, with that, we can have the underexposure and/or overexposure problem. In this work, our aim is to restore illexposed images. For this purpose, we present UCAN, a small and fast learning-based model capable to restore and enhance poorly exposed images. The obtained results are evaluated using image quality indicators which show that the proposed network is able to improve images damaged by real and simulated exposure. Qualitative and quantitative results show that the proposed model outperforms the existing models for this objective.

scholarly journals Engineering modelling of structural details of a bridge

2013 ◽  
Vol 12 (2) ◽  
pp. 055-062
Author(s):  
Stefan Pradelok ◽  
Piotr Bętkowski ◽  
Adam Rudzik ◽  
Piotr Łaziński
Keyword(s):  
Computational Model ◽  
Personal Computer ◽  
Complex Structure ◽  
Railway Bridge ◽  
Local Effects ◽  
Correct Operation ◽  
Proposed Model ◽  
Short Period ◽  
Structural Details ◽  
Truss Member

This paper presents a method of engineering modelling of structural details, which enables the analysis of local static and dynamic effects in a complex structure with the use of a personal computer. An analysed structural detail, modelled with the use of shell finite elements, is mounted to a spatial truss member system. Then, on the basis of prepared computational model, a static or dynamic analysis is carried out. The proposed model allows to detect the local effects in a theoretical. Conducted analyses confirmed the correct operation of such a computational model. Hence, the method of modelling presented in this paper allows to analyse the local effects on ordinary personal computer and more importantly, the results of such calculations are available within a relatively short period of time. The calculations are carried out by analysing the local effects in a steel node of the truss railway bridge.

scholarly journals A Cognitive Computational Model Inspired by the Immune System Response

2014 ◽  
Vol 2014 ◽  
pp. 1-15
Author(s):  
Mohamed Abdo Abd Al-Hady ◽  
Amr Ahmed Badr ◽  
Mostafa Abd Al-Azim Mostafa
Keyword(s):  
Immune System ◽  
Computational Model ◽  
Cognitive Architecture ◽  
Intelligent Agent ◽  
System Response ◽  
Danger Theory ◽  
Proposed Model ◽  
Immune System Response ◽  
Fuzzy State

The immune system has a cognitive ability to differentiate between healthy and unhealthy cells. The immune system response (ISR) is stimulated by a disorder in the temporary fuzzy state that is oscillating between the healthy and unhealthy states. However, modeling the immune system is an enormous challenge; the paper introduces an extensive summary of how the immune system response functions, as an overview of a complex topic, to present the immune system as a cognitive intelligent agent. The homogeneity and perfection of the natural immune system have been always standing out as the sought-after model we attempted to imitate while building our proposed model of cognitive architecture. The paper divides the ISR into four logical phases: setting a computational architectural diagram for each phase, proceeding from functional perspectives (input, process, and output), and their consequences. The proposed architecture components are defined by matching biological operations with computational functions and hence with the framework of the paper. On the other hand, the architecture focuses on the interoperability of main theoretical immunological perspectives (classic, cognitive, and danger theory), as related to computer science terminologies. The paper presents a descriptive model of immune system, to figure out the nature of response, deemed to be intrinsic for building a hybrid computational model based on a cognitive intelligent agent perspective and inspired by the natural biology. To that end, this paper highlights the ISR phases as applied to a case study on hepatitis C virus, meanwhile illustrating our proposed architecture perspective.

A new procedure for processing strong-motion earthquake signals

1982 ◽  
Vol 72 (2) ◽  
pp. 643-661
Author(s):  
S. Shyam Sunder ◽  
Jerome J. Connor
Keyword(s):  
United States ◽  
Filter Design ◽  
Response Spectrum ◽  
Low Frequency ◽  
Strong Motion ◽  
Sampling Period ◽  
Frequency Limit ◽  
Processing Scheme ◽  
Proposed Model ◽  
Band Pass

Abstract A new procedure for routinely processing strong-motion earthquake signals using state-of-the-art filter design and implementation techniques is presented. The model, shown to be both accuratet and efficient, is sufficiently flexible so that the signal sampling period and filter parameters can be easily varied. A comparison of results from the existing United States model (Trifunac and Lee, 1973) and the proposed model show significant differences in the ground motion and response spectrum characteristics for the same set of filter limits. Drifts in integrated velocity and displacement characteristics and theoretically incorrect asymptotic behavior of response spectrum curves arising out of the existing United States processing scheme have been eliminated. In addition to the importance of appropriately selecting a low-frequency limit for band-pass filtering the signals, this work demonstrates the sensitivity of the acceleration trace to the particular choice of a high-frequency limit.

scholarly journals No-Reference Image Quality Assessment Based on the Fusion of Statistical and Perceptual Features

2020 ◽  
Vol 6 (8) ◽  
pp. 75
Author(s):  
Domonkos Varga
Keyword(s):  
Image Quality ◽  
Quality Assessment ◽  
Image Quality Assessment ◽  
Reference Image ◽  
Phase Congruency ◽  
Perceptual Features ◽  
Proposed Model ◽  
Dark Channel ◽  
Reference Images ◽  
Spatial Domains

The goal of no-reference image quality assessment (NR-IQA) is to predict the quality of an image as perceived by human observers without using any pristine, reference images. In this study, an NR-IQA algorithm is proposed which is driven by a novel feature vector containing statistical and perceptual features. Different from other methods, normalized local fractal dimension distribution and normalized first digit distributions in the wavelet and spatial domains are incorporated into the statistical features. Moreover, powerful perceptual features, such as colorfulness, dark channel feature, entropy, and mean of phase congruency image, are also incorporated to the proposed model. Experimental results on five large publicly available databases (KADID-10k, ESPL-LIVE HDR, CSIQ, TID2013, and TID2008) show that the proposed method is able to outperform other state-of-the-art methods.

scholarly journals Image quality classification algorithm based on InceptionV3 and SVM

2019 ◽  
Vol 277 ◽  
pp. 02036
Author(s):  
Yu Li ◽  
Lizhuang Liu
Keyword(s):  
Image Quality ◽  
Data Augmentation ◽  
Classification Problem ◽  
Support Vector ◽  
Image Size ◽  
Image Description ◽  
Training Strategy ◽  
Video Images ◽  
Quality Classification ◽  
Proposed Model

In this work we investigate the use of deep learning for image quality classification problem. We use a pre-trained Convolutional Neural Network (CNN) for image description, and the Support Vector Machine (SVM) model is trained as an image quality classifier whose inputs are normalized features extracted by the CNN model. We report on different design choices, ranging from the use of various CNN architectures to the use of features extracted from different layers of a CNN model. To cope with the problem of a lack of adequate amounts of distorted picture data, a novel training strategy of multi-scale training, which is selecting a new image size for training after several batches, combined with data augmentation is introduced. The experimental results tested on the actual monitoring video images shows that the proposed model can accurately classify distorted images.

Quasi-PSO Algorithm for Modeling Foraging Dynamics in Social Mammals

2011 ◽  
Vol 3 (1) ◽  
pp. 27-38
Author(s):  
Marco Campenní ◽  
Federico Cecconi
Keyword(s):  
Computational Model ◽  
Animal Behavior ◽  
Pso Algorithm ◽  
Social Phenomenon ◽  
Proposed Model

In this paper, the authors present a computational model of a fundamental social phenomenon in the study of animal behavior: the foraging. The purpose of this work is, first, to test the validity of the proposed model compared to another existing model, the flocking model; then, to try to understand whether the model may provide useful suggestions in studying the size of the group in some species of social mammals.

Envelope-responsive neurons in areas 17 and 18 of cat

1994 ◽  
Vol 72 (5) ◽  
pp. 2134-2150 ◽  
Author(s):  
Y. X. Zhou ◽  
C. L. Baker
Keyword(s):  
Spatial Frequency ◽  
Cortical Neurons ◽  
Narrow Range ◽  
High Spatial Frequency ◽  
Sine Wave ◽  
Relative Strength ◽  
Visual Responses ◽  
Spatial Frequencies ◽  
Sensitivity Level ◽  
Areas 17 And 18

1. Single cortical neurons are known to respond to visual stimuli containing Fourier components only in a narrow range of spatial frequencies. This investigation demonstrates that some neurons in cat area 17 and 18 can also respond to certain stimuli that have no Fourier components inside the cell's luminance spatial frequency passband. 2. To study such “non-Fourier” responses, we used envelope stimuli that consisted of a high-spatial-frequency sinusoidal luminance grating (carrier) whose contrast was modulated by a low-spatial frequency sine wave (envelope). There was no Fourier component at the apparent periodicity of the envelope spatial frequency. However, some cells responded to such a “phantom” component of the envelope modulation when it fell inside the cell's luminance spatial frequency passband while all the real Fourier components in the stimuli were outside. 3. We conducted extensive control experiments to eliminate the possibility of producing artifactual responses to the envelope stimuli due to any small residual nonlinearity of the z-linearized CRT screen. The control experiments included 1) testing of screen linearity to ensure that the effect from the residual screen nonlinearity was no larger than the sensitivity level of visual responses and 2) comparing the responses to envelope stimuli with the responses to the equivalent contrast of the artifact produced by the screen nonlinearity. All these control experiments indicated that any effect of screen nonlinearity did not contribute significantly to the neural envelope responses. 4. We performed a statistical analysis to obtain an index of relative strength of envelope responses for each cell and to objectively classify cells as “envelope-responsive” or “non-envelope-responsive.”(ABSTRACT TRUNCATED AT 250 WORDS)

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