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Sensory factors limiting horizontal and vertical visual span
Reading speed for English text is slower for text oriented vertically than horizontally. Yu, Park, Gerold, and Legge (2010) showed that slower reading of vertical text is associated with a smaller visual span (the number of letters recognized with high accuracy without moving the eyes). Three possib
Combined Horizontal and Vertical Projection Feature Extraction
Combined Horizontal and Vertical Projection Feature Extraction Technique for Gurmukhi Handwritten Character Recognition March 2015 DOI: 10.1109/ICACEA.2015.7164646
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Horizontal and vertical features fusion network based on
Electroencephalogram (EEG) based emotion recognition has become an important topic in humancomputer interaction and affective computing. However, existing advanced methods still have some problems.
Simultaneous Recognition of Horizontal and Vertical Text in
Figure 5 depicts the results of attention and recognition for horizontal and vertical characters, both of which confirm that the method works well. The main purpose of our study is to compare the performance between a supervised proposed method and an unsupervised baseline method for text direction. We would like to emphasize that our model
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Digital electric meter reading recognition based on horizontal
These individual digits are segmented from an edge image through the vertical projection. Furthermore, the individually segmented digits are filled and thinned to detect the shapes of the digits. From these segmented digit shapes the Horizontal and Vertical Binary (HVB) pattern features are extracted. This is the key contribution of this paper.
Digital Electric Meter Reading Recognition Based on Horizontal
The meter image has been captured from a ixed distance for better recognition purposes. The horizontal and vertical pattern is generated in [3, 4] to segment each digit which is collected from the
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Sensory factors limiting horizontal and vertical visual span for
Sensory factors limiting horizontal and vertical visual span for letter recognition Deyue Yu # $ College of Optometry, The Ohio State University, Columbus, Ohio, USA (in bits) about letter recognition. Across vertical and horizontal conditions, crowding accounted for 75% of the loss in information, mislocations accounted for 19% of the loss
Emotion recognition (sometimes) depends on horizontal
Face recognition depends critically on horizontal orientations (Goffaux & Dakin, 2010). Face images that lack horizontal features are harder to recognize than those that have that information preserved. The authors compared direct with averted gaze by presenting an array of faces filtered to include horizontal, vertical, or a combination of
Lexical processes in the recognition of Japanese horizontal and
and aloud in both horizontal and vertical alignments. A processing advantage was witnessed for horizontal reading. Half a century later, Tinker (1955) tested an effect of systematic practice in vertical reading. Although vertical reading was 50 % slower than horizontal reading before the practice, this disadvantage was minimized
s and p ch. 4 Flashcards
The _____ effect occurs because humans have more cortical neurons that respond to horizontal and vertical orientations than slanted orientations. She takes the battery out of the car, and finds out that the car won''t start and the lights and stereo don''t work. is the same for pictures of furnished and empty rooms. c.is higher for
Digital electric meter reading recognition based on horizontal
DOI: 10.1109/EICT.2017.8275241 Corpus ID: 24334759; Digital electric meter reading recognition based on horizontal and vertical binary pattern @article{Anis2017DigitalEM, title={Digital electric meter reading recognition based on horizontal and vertical binary pattern}, author={Atif Anis and Md. Khaliluzzaman and Mohammad Yakub and Niloy Chakraborty and Kaushik Deb},
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Horizontal and vertical features fusion network based on
To explore the above issues and further enhance the emotion recognition ability of the subject-independent experiment, this paper constructs a horizontal and vertical features fusion network based on different brain regions (HVF 2 N-DBR), aiming to make the different brain regions features be interacted and explore which brain regions signals of the cerebral cortex
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[1812.07059] Simultaneous Recognition of Horizontal and Vertical
Recent state-of-the-art scene text recognition methods have primarily focused on horizontal text in images. However, in several Asian countries, including China, large amounts of text in signs, books, and TV commercials are vertically directed. Because the horizontal and vertical texts exhibit different characteristics, developing an algorithm that can simultaneously
Horizontal and vertical projections. | Download Scientific Diagram
Optical character recognition – using a deep learning technique that describes an overview of optical character recognition, the basic steps in the optical character recognition problem.
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Braille letter recognition in deep convolutional neural network
braille recognition studies. Braille recognition does not only reduce the dyslexia of the blind but also overcomes the problems of people involved in the world of braille education, such as correcting school work, marking paper [3]. Through computer technology, difficulties in translating braille can be solved by a variety of methods.
Vertical vs. Horizontal Pictures with a Digital Camera
Which is a vertical battery grip. What''s really nice about this is that it puts a second shutter here, in addition to the one here. So you can really comfortably hold it vertical and shoot. Great for sports. Great for portraits. Great for studio work. Again, it''s up to you, vertical versus
Horizontal and vertical features fusion network based on
Therefore, in the article, we raise a horizontal and vertical features fusion network based on different brain regions (HVF2N-DBR) for emotion recognition. The HVF2N-DBR method not only considers the influence of EEG activity in the various brain regions on affective recognition but also obtains the temporal–spatial characteristics of EEG signals.