The Descriptiveness of Feature Descriptors with Reduced Dimensionality

2021 ◽  
pp. 317-322
Author(s):  
Dániel Varga ◽  
János Márk Szalai-Gindl ◽  
Sándor Laki
Keyword(s):  
Reduced Dimensionality ◽  
Feature Descriptors

A Study on Multi Class Classification from Breast Cancer Images using Ensemble Network and Transfer Learning

2020 ◽  
Vol 14 ◽  
Author(s):  
Lahari Tipirneni ◽  
Rizwan Patan
Keyword(s):  
Breast Cancer ◽  
Neural Network ◽  
Convolutional Neural Network ◽  
Binary Classification ◽  
Disease Diagnosis ◽  
Feature Descriptors ◽  
Histopathological Images ◽  
Viable Approach ◽  
Multi Class Classification

Abstract:: Millions of deaths all over the world are caused by breast cancer every year. It has become the most common type of cancer in women. Early detection will help in better prognosis and increases the chance of survival. Automating the classification using Computer-Aided Diagnosis (CAD) systems can make the diagnosis less prone to errors. Multi class classification and Binary classification of breast cancer is a challenging problem. Convolutional neural network architectures extract specific feature descriptors from images, which cannot represent different types of breast cancer. This leads to false positives in classification, which is undesirable in disease diagnosis. The current paper presents an ensemble Convolutional neural network for multi class classification and Binary classification of breast cancer. The feature descriptors from each network are combined to produce the final classification. In this paper, histopathological images are taken from publicly available BreakHis dataset and classified between 8 classes. The proposed ensemble model can perform better when compared to the methods proposed in the literature. The results showed that the proposed model could be a viable approach for breast cancer classification.

scholarly journals An Evaluation of Traditional and CNN-based Feature Descriptors for Cartoon Pornography Detection

IEEE Access ◽  
2021 ◽  
pp. 1-1
Author(s):  
Nouar AlDahoul ◽  
Hezerul Abdul Karim ◽  
Mohd Haris Lye Abdullah ◽  
Abdulaziz Saleh Ba Wazir ◽  
Mohammad Faizal Ahmad Fauzi ◽  
...  
Keyword(s):  
Feature Descriptors

scholarly journals Nanometer-Thick [(FPEA)2PbX4; X=I, Br] 2D Halide Perovskite Based Thin Films for Pollutant Detection and Nonconventional Photocatalytic Degradation

2021 ◽  
Author(s):  
Arindam Mondal ◽  
Akash Lata ◽  
Aarya Prabhakaran ◽  
Satyajit Gupta
Keyword(s):  
Thin Films ◽  
Photocatalytic Degradation ◽  
Three Dimensional ◽  
Two Dimensional ◽  
Reduced Dimensionality ◽  
P Application ◽  
Halide Perovskites ◽  
Halide Perovskite ◽  
Pollutant Detection

Application of three-dimensional (3D)-halide perovskites (HaP) in photocatalysis encourages the new exercise with two-dimensional (2D) HaP based thin-films for photocatalytic degradation of dye. The reduced dimensionality to 2D-HaPs, with a...

scholarly journals FSD-BRIEF: A Distorted BRIEF Descriptor for Fisheye Image Based on Spherical Perspective Model

Sensors ◽  
2021 ◽  
Vol 21 (5) ◽  
pp. 1839
Author(s):  
Yutong Zhang ◽  
Jianmei Song ◽  
Yan Ding ◽  
Yating Yuan ◽  
Hua-Liang Wei
Keyword(s):  
Feature Matching ◽  
Field Of View ◽  
Image Feature ◽  
Feature Points ◽  
Matching Process ◽  
Feature Descriptors ◽  
Coordinate Mapping ◽  
Matching Performance ◽  
Perspective Model ◽  
Attitude Matrix

Fisheye images with a far larger Field of View (FOV) have severe radial distortion, with the result that the associated image feature matching process cannot achieve the best performance if the traditional feature descriptors are used. To address this challenge, this paper reports a novel distorted Binary Robust Independent Elementary Feature (BRIEF) descriptor for fisheye images based on a spherical perspective model. Firstly, the 3D gray centroid of feature points is designed, and the position and direction of the feature points on the spherical image are described by a constructed feature point attitude matrix. Then, based on the attitude matrix of feature points, the coordinate mapping relationship between the BRIEF descriptor template and the fisheye image is established to realize the computation associated with the distorted BRIEF descriptor. Four experiments are provided to test and verify the invariance and matching performance of the proposed descriptor for a fisheye image. The experimental results show that the proposed descriptor works well for distortion invariance and can significantly improve the matching performance in fisheye images.

Application of feature descriptors to low-pixel-count persistent surveillance tracking systems

2013 ◽  
Author(s):  
Jason Edelberg ◽  
Christopher Miller ◽  
Michael Wilson
Keyword(s):  
Tracking Systems ◽  
Feature Descriptors
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