Spectrogram contour features for intraspecific classification of narrow‐band animal sounds.

1996 ◽  
Vol 99 (4) ◽  
pp. 2557-2574
Author(s):  
Ben Pinkowski
Keyword(s):  
Narrow Band ◽  
Intraspecific Classification

scholarly journals Manual versus Automatic Classification of Laryngeal Lesions based on Vascular Patterns in CE+NBI Images

2020 ◽  
Vol 6 (3) ◽  
pp. 70-73
Author(s):  
Nazila Esmaeili ◽  
Alfredo Illanes ◽  
Axel Boese ◽  
Nikolaos Davaris ◽  
Christoph Arens ◽  
...  
Keyword(s):  
Vocal Fold ◽  
Narrow Band ◽  
Narrow Band Imaging ◽  
Automatic Classification ◽  
Vascular Pattern ◽  
Objective Interpretation ◽  
Laryngeal Lesions ◽  
Malignant Lesions ◽  
Manual Classification

AbstractLongitudinal and perpendicular changes in the blood vessels of the vocal fold have been related to the advancement from benign to malignant laryngeal cancer stages. The combination of Contact Endoscopy (CE) and Narrow Band Imaging (NBI) provides intraoperative realtime visualization of vascular pattern in Larynx. The evaluation of these vascular patterns in CE+NBI images is a subjective process leading to differentiation difficulty and subjectivity between benign and malignant lesions. The main objective of this work is to compare multi-observer classification versus automatic classification of laryngeal lesions. Six clinicians visually classified CE+NBI images into benign and malignant lesions. For the automatic classification of CE+NBI images, we used an algorithm based on characterizing the level of the vessel’s disorder. The results of the manual classification showed that there is no objective interpretation, leading to difficulties to visually distinguish between benign and malignant lesions. The results of the automatic classification of CE+NBI images on the other hand showed the capability of the algorithm to solve these issues. Based on the observed results we believe that, the automatic approach could be a valuable tool to assist clinicians to classifying laryngeal lesions.

scholarly journals Luminosity Classification of Be Stars by Balmer Line Narrow Band Photometry

1982 ◽  
Vol 98 ◽  
pp. 37-40
Author(s):  
Wolfgang Zeuge
Keyword(s):  
Narrow Band ◽  
Balmer Line ◽  
Be Stars ◽  
The Absolute ◽  
Absolute Luminosity

The absolute luminosity of most Be stars can be determined by using Balmer line narrow band photometry with an accuracy of about 0.4 mag. The few cases in which this method fails can be detected.

VASCULAR PATTERN CLASSIFICATION OF COLORECTAL LESIONS WITH NARROW BAND IMAGING MAGNIFYING ENDOSCOPY

2011 ◽  
Vol 23 ◽  
pp. 106-111 ◽  
Author(s):  
YOSHIKI WADA ◽  
SHIN-EI KUDO ◽  
MASASHI MISAWA ◽  
NOBUNAO IKEHARA ◽  
SHIGEHARU HAMATANI
Keyword(s):  
Pattern Classification ◽  
Narrow Band ◽  
Narrow Band Imaging ◽  
Magnifying Endoscopy ◽  
Vascular Pattern

scholarly journals Abundance Effects in the Classification of K Stars

1976 ◽  
Vol 72 ◽  
pp. 87-90
Author(s):  
P. M. Williams
Keyword(s):  
Spectral Type ◽  
Near Infrared ◽  
Narrow Band ◽  
Infrared Photometry ◽  
Metal Abundance ◽  
Metal Abundances ◽  
Effective Temperatures

The influence of metal abundance and gravity on the relation between spectral type and effective temperatures of late G and K type stars is investigated and calibrated using metal abundances from narrow-band photometry, near infrared photometry and independent luminosity estimates.

scholarly journals Comparison of deep learning and conventional machine learning methods for classification of colon polyp types

2021 ◽  
Vol 5 (1) ◽  
pp. 34-42
Author(s):  
Refika Sultan Doğan ◽  
Bülent Yılmaz
Keyword(s):  
Machine Learning ◽  
Deep Learning ◽  
White Light ◽  
Narrow Band ◽  
Optical Biopsy ◽  
Colon Polyps ◽  
Tissue Biopsy ◽  
Conventional Machine ◽  
White Light Imaging

AbstractDetermination of polyp types requires tissue biopsy during colonoscopy and then histopathological examination of the microscopic images which tremendously time-consuming and costly. The first aim of this study was to design a computer-aided diagnosis system to classify polyp types using colonoscopy images (optical biopsy) without the need for tissue biopsy. For this purpose, two different approaches were designed based on conventional machine learning (ML) and deep learning. Firstly, classification was performed using random forest approach by means of the features obtained from the histogram of gradients descriptor. Secondly, simple convolutional neural networks (CNN) based architecture was built to train with the colonoscopy images containing colon polyps. The performances of these approaches on two (adenoma & serrated vs. hyperplastic) or three (adenoma vs. hyperplastic vs. serrated) category classifications were investigated. Furthermore, the effect of imaging modality on the classification was also examined using white-light and narrow band imaging systems. The performance of these approaches was compared with the results obtained by 3 novice and 4 expert doctors. Two-category classification results showed that conventional ML approach achieved significantly better than the simple CNN based approach did in both narrow band and white-light imaging modalities. The accuracy reached almost 95% for white-light imaging. This performance surpassed the correct classification rate of all 7 doctors. Additionally, the second task (three-category) results indicated that the simple CNN architecture outperformed both conventional ML based approaches and the doctors. This study shows the feasibility of using conventional machine learning or deep learning based approaches in automatic classification of colon types on colonoscopy images.

Narrow-band photometric classification of eclipsing binaries

1966 ◽  
Vol 24 ◽  
pp. 190-210
Author(s):  
D. H. McNamara
Keyword(s):  
Temperature Scale ◽  
Narrow Band ◽  
Eclipsing Binaries ◽  
Spectral Classification ◽  
Uniform System ◽  
Fundamental Properties ◽  
Eclipsing Stars ◽  
Accurate Knowledge ◽  
Observational Program

Although a great deal of work has been devoted in recent years to the problem of improving our knowledge of the spectroscopic and light elements of the eclipsing stars, little effort has been expended on the problem of two-dimensional spectral classification of the component stars on a uniform system. The only serious attempt in this direction appears to be the MK classification of a number of eclipsing stars by Miss Roman (i). Since the light- and velocity-curves of eclipsing systems provide us with fundamental properties such as radii, masses, and densities it is extremely important to have accurate knowledge of the luminosities and spectral types of these objects. In this paper we describe the results of an observational program designed specifically to improve our knowledge of the luminosities and colors of these important stars. The luminosities and colors are then utilized in a discussion of the mass-luminosity relation and effective-temperature scale of stars brigher than the Sun.

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