scholarly journals Curvilinear features are important for animate/inanimate categorization in macaques

2020 ◽  
Author(s):  
Marissa Yetter ◽  
Sophia Robert ◽  
Grace Mammarella ◽  
Barry Richmond ◽  
Mark A. G. Eldridge ◽  
...  
Keyword(s):  
High Accuracy ◽  
Image Feature ◽  
Perceptual Categorization ◽  
Current Experiment ◽  
Global Shape ◽  
Object Categories ◽  
Intermediate Image ◽  
Synthetic Images ◽  
Curvilinear Features

AbstractThe current experiment investigated the extent to which perceptual categorization of animacy, i.e. the ability to discriminate animate and inanimate objects, is facilitated by image-based features that distinguish the two object categories. We show that, with nominal training, naïve macaques could classify a trial-unique set of 1000 novel images with high accuracy. To test whether image-based features that naturally differ between animate and inanimate objects, such as curvilinear and rectilinear information, contribute to the monkeys’ accuracy, we created synthetic images using an algorithm that distorted the global shape of the original animate/inanimate images while maintaining their intermediate features (Portilla and Simoncelli, 2000). Performance on the synthesized images was significantly above chance and was predicted by the amount of curvilinear information in the images. Our results demonstrate that, without training, macaques can use an intermediate image feature, curvilinearity, to facilitate their categorization of animate and inanimate objects.

A Novel PIV Interrogation Algorithm

2011 ◽  
Vol 356-360 ◽  
pp. 1079-1084
Author(s):  
Lian Feng Xu ◽  
Gang Chen
Keyword(s):  
High Accuracy ◽  
Synthetic Images ◽  
Computing Speed

Based on the thoroughly analysis of two conventional PIV algorithm, a new velocity extracting methods called Pre-estimate Searching Algorithm(PESA) is presented in this paper which combines the superiorities of the two conventional PIV algorithms. And the realization procedure of this new algorithm is provided also. Both the synthetic images and real PIV images experiments show that the new algorithm has the advantage of high accuracy and fast computing speed.

Sparse Based Image Classification With Bag-of-Visual-Words Representations

2011 ◽  
Vol 3 (1) ◽  
pp. 1-15 ◽  
Author(s):  
Yuanyuan Zuo ◽  
Bo Zhang
Keyword(s):  
Sparse Representation ◽  
Image Classification ◽  
Image Feature ◽  
Support Vector ◽  
Bag Of Visual Words ◽  
Human Face Recognition ◽  
Visual Words ◽  
Object Categories ◽  
Comparable Performance ◽  
Background Clutter

The sparse representation based classification algorithm has been used to solve the problem of human face recognition, but the image database is restricted to human frontal faces with only slight illumination and expression changes. This paper applies the sparse representation based algorithm to the problem of generic image classification, with a certain degree of intra-class variations and background clutter. Experiments are conducted with the sparse representation based algorithm and Support Vector Machine (SVM) classifiers on 25 object categories selected from the Caltech101 dataset. Experimental results show that without the time-consuming parameter optimization, the sparse representation based algorithm achieves comparable performance with SVM. The experiments also demonstrate that the algorithm is robust to a certain degree of background clutter and intra-class variations with the bag-of-visual-words representations. The sparse representation based algorithm can also be applied to generic image classification task when the appropriate image feature is used.

AN IMAGE RETRIEVAL SYSTEM BASED ON THE IMAGE FEATURE OF COLOR DIFFERENCES ON EDGES IN SPIRAL SCAN ORDER

2003 ◽  
Vol 17 (08) ◽  
pp. 1417-1429 ◽  
Author(s):  
YUNG-KUAN CHAN ◽  
YI-TUNG LIU
Keyword(s):  
Image Retrieval ◽  
Retrieval System ◽  
High Accuracy ◽  
Image Feature ◽  
Accuracy Rate ◽  
Color Differences ◽  
Image Retrieval System ◽  
Spiral Scan

In this paper, an image feature of color differences on edges in spiral scan order (CDESSO) is presented. This proposed CDESSO feature can characterize the principal pixel colors, color complexity and color differences among adjacent objects in an image. In addition, this paper employs the CDESSO feature to develop an image retrieval system. The CDESSO-based image retrieval system can provide a high accuracy rate in finding the database images that satisfy the users' requirement. Besides, it can also resist the scale variants of images as well as the shift and rotation variants of objects in images.

Sparse Based Image Classification With Bag-of-Visual-Words Representations

2013 ◽  
pp. 16-30
Author(s):  
Yuanyuan Zuo ◽  
Bo Zhang
Keyword(s):  
Sparse Representation ◽  
Image Classification ◽  
Image Feature ◽  
Support Vector ◽  
Bag Of Visual Words ◽  
Human Face Recognition ◽  
Visual Words ◽  
Object Categories ◽  
Comparable Performance ◽  
Background Clutter

The sparse representation based classification algorithm has been used to solve the problem of human face recognition, but the image database is restricted to human frontal faces with only slight illumination and expression changes. This paper applies the sparse representation based algorithm to the problem of generic image classification, with a certain degree of intra-class variations and background clutter. Experiments are conducted with the sparse representation based algorithm and Support Vector Machine (SVM) classifiers on 25 object categories selected from the Caltech101 dataset. Experimental results show that without the time-consuming parameter optimization, the sparse representation based algorithm achieves comparable performance with SVM. The experiments also demonstrate that the algorithm is robust to a certain degree of background clutter and intra-class variations with the bag-of-visual-words representations. The sparse representation based algorithm can also be applied to generic image classification task when the appropriate image feature is used.

A New 1,000 kV Electron Microscope

1967 ◽  
Vol 25 ◽  
pp. 260-261
Author(s):  
M. Nishigaki ◽  
S. Katagiri ◽  
H. Kimura ◽  
B. Tadano
Keyword(s):  
Electron Microscope ◽  
High Voltage ◽  
Basic Research ◽  
Chromatic Aberration ◽  
High Accuracy ◽  
Biological Specimen ◽  
Voltage Electron ◽  
High Voltage Electron Microscope ◽  
High Voltage Electron

The high voltage electron microscope has many advantageous features in comparison with the ordinary electron microscope. They are a higher penetrating efficiency of the electron, low chromatic aberration, high accuracy of the selected area diffraction and so on. Thus, the high voltage electron microscope becomes an indispensable instrument for the metallurgical, polymer and biological specimen studies. The application of the instrument involves today not only basic research but routine survey in the various fields. Particularly for the latter purpose, the performance, maintenance and reliability of the microscope should be same as those of commercial ones. The authors completed a 500 kV electron microscope in 1964 and a 1,000 kV one in 1966 taking these points into consideration. The construction of our 1,000 kV electron microscope is described below.

High-resolution electron microscopy of the atomic structure of some grain boundaries in Au

1986 ◽  
Vol 44 ◽  
pp. 414-415
Author(s):  
W. Krakow ◽  
D. A. Smith
Keyword(s):  
Atomic Structure ◽  
High Resolution Electron Microscopy ◽  
Image Features ◽  
Image Feature ◽  
Resolution Electron ◽  
Tilt Boundaries ◽  
Processing Techniques ◽  
Atom Position ◽  
Structure Configuration

The successful determination of the atomic structure of [110] tilt boundaries in Au stems from the investigation of microscope performance at intermediate accelerating voltages (200 and 400kV) as well as a detailed understanding of how grain boundary image features depend on dynamical diffraction processes variation with specimen and beam orientations. This success is also facilitated by improving image quality by digital image processing techniques to the point where a structure image is obtained and each atom position is represented by a resolved image feature. Figure 1 shows an example of a low angle (∼10°) Σ = 129/[110] tilt boundary in a ∼250Å Au film, taken under tilted beam brightfield imaging conditions, to illustrate the steps necessary to obtain the atomic structure configuration from the image. The original image of Fig. 1a shows the regular arrangement of strain-field images associated with the cores of ½ [10] primary dislocations which are separated by ∼15Å.

The Ego Could Be Depleted, Providing Initial Exertion Is Depleting

2017 ◽  
Vol 48 (4) ◽  
pp. 242-245 ◽  
Author(s):  
Junhua Dang ◽  
Ying Liu ◽  
Xiaoping Liu ◽  
Lihua Mao
Keyword(s):  
Stroop Task ◽  
Meta Analysis ◽  
Ego Depletion ◽  
Current Experiment ◽  
The Past ◽  
Depletion Effect

Abstract. The ego depletion effect has been examined by over 300 independent studies during the past two decades. Despite its pervasive influence, recently this effect has been severely challenged and asserted to be a fake. Based on an up-to-date meta-analysis that examined the effectiveness of each frequently used depleting task, we preregistered the current experiment with the aim to examine whether there would be an ego depletion effect when the Stroop task is used as the depleting task. The results demonstrated a significant ego depletion effect. The current research highlights the importance of the depleting task’s effectiveness. That is to say, the “ego” could be “depleted,” but only when initial exertion is “depleting.”

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