A Visual Processing System for Facial Prediction

1999 ◽  
pp. 739-748 ◽  
Author(s):  
Changsheng Xu ◽  
Jiankang Wu ◽  
Songde Ma
Keyword(s):  
Visual Processing ◽  
Processing System

Centered-Object Integrated Segmentation and Recognition of Overlapping Handprinted Characters

1993 ◽  
Vol 5 (3) ◽  
pp. 419-429 ◽  
Author(s):  
Gale L. Martin
Keyword(s):  
Visual Processing ◽  
Character Recognition ◽  
Processing System ◽  
Visual Object ◽  
Visual Object Recognition ◽  
Single Character ◽  
Backpropagation Network ◽  
Physical Information ◽  
Accuracy Rates ◽  
Single Neural Network

Visual object recognition is often conceived of as a final step in a visual processing system, First, physical information in the raw image is used to isolate and enhance to-be-recognized clumps and then each of the resulting preprocessed representations is fed into the recognizer. This general conception fails when there are no reliable physical cues for isolating the objects, such as when objects overlap. This paper describes an approach, called centered object integrated segmentation and recognition (COISR), for integrating object segmentation and recognition within a single neural network. The application is handprinted character recognition. The approach uses a backpropagation network that scans a field of characters and is trained to recognize whether it is centered over a single character or between characters. When it is centered over a character, the net classifies the character. The approach is tested on a dataset of handprinted digits and high accuracy rates are reported.

ARM-Based Embedded Visual Processing System

2012 ◽  
Vol 220-223 ◽  
pp. 1973-1976
Author(s):  
Guo Hao He
Keyword(s):  
Power Systems ◽  
Visual Processing ◽  
Detection System ◽  
Processing System ◽  
Smart Devices ◽  
Smart Environment ◽  
Embedded Devices ◽  
The Past ◽  
Embedded Computer Vision ◽  
Embedded Computer

Embedded computer vision is a relatively new concept, it is only in the past few years that embedded devices have become fast enough and the component cost low enough that they can be used in small low power systems. In this paper, the design and development of a vision-based detection system with smart devices features is proposed. The main functionality of the equipment is introduced as well as the additional features it should provide to be integrated into a smart environment.

scholarly journals Functional Connectivity Density for Radiation Encephalopathy Prediction in Nasopharyngeal Carcinoma

2021 ◽  
Vol 11 ◽  
Author(s):  
Lin-Mei Zhao ◽  
Ya-Fei Kang ◽  
Jian-Ming Gao ◽  
Li Li ◽  
Rui-Ting Chen ◽  
...  
Keyword(s):  
Functional Connectivity ◽  
Nasopharyngeal Carcinoma ◽  
Visual Processing ◽  
Somatosensory System ◽  
Processing System ◽  
Diagnostic Efficiency ◽  
Resting State Functional Connectivity ◽  
Functional Connectivity Density ◽  
Characteristic Operator ◽  
Radiation Encephalopathy

The diagnostic efficiency of radiation encephalopathy (RE) remains heterogeneous, and prediction of RE is difficult at the pre-symptomatic stage. We aimed to analyze the whole-brain resting-state functional connectivity density (FCD) of individuals with pre-symptomatic RE using multivariate pattern analysis (MVPA) and explore its prediction efficiency. Resting data from NPC patients with nasopharyngeal carcinoma (NPC; consisting of 20 pre-symptomatic RE subjects and 26 non-RE controls) were collected in this study. We used MVPA to classify pre-symptomatic RE subjects from non-RE controls based on FCD maps. Classifier performances were evaluated by accuracy, sensitivity, specificity, and area under the characteristic operator curve. Permutation tests and leave-one-out cross-validation were applied for assessing classifier performance. MVPA was able to differentiate pre-symptomatic RE subjects from non-RE controls using global FCD as a feature, with a total accuracy of 89.13%. The temporal lobe as well as regions involved in the visual processing system, the somatosensory system, and the default mode network (DMN) revealed robust discrimination during classification. Our findings suggest a good classification efficiency of global FCD for the individual prediction of RE at a pre-symptomatic stage. Moreover, the discriminating regions may contribute to the underlying mechanisms of sensory and cognitive disturbances in RE.

Functional abnormalities of the visual processing system in subjects with mild cognitive impairment: An fMRI study

2008 ◽  
Vol 163 (3) ◽  
pp. 248-259 ◽  
Author(s):  
Arun Lawrence Warren Bokde ◽  
Patricia Lopez-Bayo ◽  
Christine Born ◽  
Wentian Dong ◽  
Thomas Meindl ◽  
...  
Keyword(s):  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
Visual Processing ◽  
Processing System ◽  
Fmri Study

A theory of insect vision: velocity parallax

1986 ◽  
Vol 229 (1254) ◽  
pp. 13-27 ◽  
Keyword(s):  
Visual Processing ◽  
Optic Lobe ◽  
Processing System ◽  
Experimental Tests ◽  
Insect Vision ◽  
Lateral Spread ◽  
Alternative Mechanism ◽  
Apparent Velocity ◽  
Velocity Signal ◽  
Primitive Form

Many insects show by their behaviour that they detect visually the existence of separate objects. The experimental material to analyse how they perceive objects is provided by an insect that walks to the end of a stick; then, because it has no alternative, it reaches with a foreleg towards a neighbouring object that it perceives to be within range. Some insects make horizontal peering movements as an aid to vision. The peering motion is exactly appropriate for generating an apparent velocity of nearby objects relative to the background. These experiments, when put together with the known properties of optic lobe neurons, suggest that a mechanism based on velocity parallax projected to the horizontal plane accounts for much insect visual behavour. Velocity parallax is defined as the discrepancy seen at the edge of an object against a distant background when the eye moves laterally. On this theory, perception of an object is inseparable from the local detection of velocity differences. The background may not be ‘perceived' at all when an object occurs in the foreground. The postulated mechanism is a two- or three-stage feedback, in which the perceived velocity (or, more accurately, the spatially correlated contrast frequency) in small-field motion-perception units is reduced by the averaged contrast frequency in larger fields, which feed back upon them. Contrast frequency is defined as the frequency of the flicker that is generated by a pattern moving across the eye. An alternative mechanism to the feedback of the velocity signal with lateral spread is adaptation to the local average background velocity, while sensitivity to a smaller local change in velocity is retained. That idea comes from recent work on the H1 neuron in the fly optic lobe, and could be the basis of a primitive form vision that, if present in mediumfield neurons, is adequate for the whole of the normal visual behaviour of a freely moving insect. These speculations invite a variety of experimental tests, ranging from visual discrimination tests with bees that are shown the velocity parallax situation, to appropriate stimulation of optic lobe neurons, to simulation of a visual processing system that relies on velocity parallax cues to detect objects.

Sign in / Sign up

Export Citation Format

Share Document