Chord recognition system for an electronic musical instrument

1982 ◽  
Vol 71 (3) ◽  
pp. 779-779
Author(s):  
Angelo A. Bione ◽  
Robert J. Sehnert ◽  
Horace E. Taylor
Keyword(s):  
Recognition System ◽  
Musical Instrument ◽  
Chord Recognition

Musical Experience Shapes Neural Processing

2020 ◽  
Vol 31 (2) ◽  
pp. 81-86
Author(s):  
Wido Nager ◽  
Tilla Franke ◽  
Tobias Wagner-Altendorf ◽  
Eckart Altenmüller ◽  
Thomas F. Münte
Keyword(s):  
Mismatch Negativity ◽  
Pure Tone ◽  
Musical Instrument ◽  
Active Listening ◽  
Musical Experience ◽  
Neural Processing ◽  
Neural Adaptations

Abstract. Playing a musical instrument professionally has been shown to lead to structural and functional neural adaptations, making musicians valuable subjects for neuroplasticity research. Here, we follow the hypothesis that specific musical demands further shape neural processing. To test this assumption, we subjected groups of professional drummers, professional woodwind players, and nonmusicians to pure tone sequences and drum sequences in which infrequent anticipations of tones or drum beats had been inserted. Passively listening to these sequences elicited a mismatch negativity to the temporally deviant stimuli which was greater in the musicians for tone series and particularly large for drummers for drum sequences. In active listening conditions drummers more accurately and more quickly detected temporally deviant stimuli.

Picture naming reveals the major invariances expected of a shape recognition system

1991 ◽  
Author(s):  
Irving Biederman ◽  
Eric E. Cooper ◽  
Peter C. Gerhardstein
Keyword(s):  
Picture Naming ◽  
Shape Recognition ◽  
Recognition System

IRIS AND FINGER VEIN MULTI MODEL RECOGNITION SYSTEM BASED ON SIFT FEATURES

2018 ◽  
Vol 1 (2) ◽  
pp. 34-44
Author(s):  
Faris E Mohammed ◽  
Dr. Eman M ALdaidamony ◽  
Prof. A. M Raid
Keyword(s):  
Iris Recognition ◽  
Recognition Performance ◽  
Recognition System ◽  
Individual Identification ◽  
Work Place ◽  
Identification Process ◽  
Finger Vein ◽  
Noise Point ◽  
Vein Recognition ◽  
A New Technique

Individual identification process is a very significant process that resides a large portion of day by day usages. Identification process is appropriate in work place, private zones, banks …etc. Individuals are rich subject having many characteristics that can be used for recognition purpose such as finger vein, iris, face …etc. Finger vein and iris key-points are considered as one of the most talented biometric authentication techniques for its security and convenience. SIFT is new and talented technique for pattern recognition. However, some shortages exist in many related techniques, such as difficulty of feature loss, feature key extraction, and noise point introduction. In this manuscript a new technique named SIFT-based iris and SIFT-based finger vein identification with normalization and enhancement is proposed for achieving better performance. In evaluation with other SIFT-based iris or SIFT-based finger vein recognition algorithms, the suggested technique can overcome the difficulties of tremendous key-point extraction and exclude the noise points without feature loss. Experimental results demonstrate that the normalization and improvement steps are critical for SIFT-based recognition for iris and finger vein , and the proposed technique can accomplish satisfactory recognition performance. Keywords: SIFT, Iris Recognition, Finger Vein identification and Biometric Systems.   © 2018 JASET, International Scholars and Researchers Association    

Survey on Segmentation to Iris Recognition System

2012 ◽  
Vol 3 (4) ◽  
pp. 514-515
Author(s):  
Meenakshi BK Meenakshi BK ◽  
◽  
Prasad M R Prasad M R
Keyword(s):  
Iris Recognition ◽  
Recognition System
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