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Now showing items 11-20 of 31
Automatic Airport Detection with Line Segment Detector and Histogram of Oriented Gradients from Satellite Images
(Ieee, 2018)
Airports are extremely critical targets in both economic and military areas. The earlier detection of these regions provides a very important intelligence information for making that regions unusable against a possible ...
Efficient deep features selections and classification for flower species recognition
(Elsevıer Scı Ltd, 2019)
Image-based automatic flower species classification is an important problem for the biologists who construct digital flower catalogs. A dozen of work about flower species recognition has been proposed so far based on ...
Normal and Acute Tympanic Membrane Diagnosis based on Gray Level Co-Occurrence Matrix and Artificial Neural Networks
(Ieee, 2019)
Otitis Media (OM) is the general name of middle ear inflammation. In order to diagnose this disease, it is important to examine the middle ear tympanic membrane (TM) by a standard otoscopy device. In recent years, biomedical ...
Transfer Learning Based Object Detection and Effect of Majority Voting on Classification Performance
(Ieee, 2019)
The use of traditional machine learning techniques in the classification tasks of image-based automatic object species requires primarily extracting the feature set. This requires deciding which set of features to use, and ...
White Blood Cell Classification Based on Shape and Deep Features
(Ieee, 2019)
Classification of the white blood cells (WBCs) in blood smear images is essential for providing important information to the physicians. In addition, manual analyzing of the blood smear images for determining the various ...
Food Image Classification with Deep Features
(Ieee, 2019)
In this paper, deep feature extraction, feature concatenation and support vector machine (SVM) classifier are used for efficient classification of food images. Classification of foods according to their images becomes a ...
Deep Convolutional Neural Networks for Airport Detection in Remote Sensing Images
(Ieee, 2018)
This study investigated the use of deep convolutional neural networks (CNNs) in providing a solution for the problem of airport detection in remote sensing images (RSIs). In recent years, Deep CNNs have gained much attention ...
Neutrosophic Hough Transform
(Mdpı Ag, 2017)
Hough transform (HT) is a useful tool for both pattern recognition and image processing communities. In the view of pattern recognition, it can extract unique features for description of various shapes, such as lines, ...
A novel microaneurysms detection approach based on convolutional neural networks with reinforcement sample learning algorithm
(Bıomed Central Ltd, 2017)
Microaneurysms (MAs) are known as early signs of diabetic-retinopathy which are called red lesions in color fundus images. Detection of MAs in fundus images needs highly skilled physicians or eye angiography. Eye angiography ...
A Retinal Vessel Detection Approach Based on Shearlet Transform and Indeterminacy Filtering on Fundus Images
(Mdpı, 2017)
A fundus image is an effective tool for ophthalmologists studying eye diseases. Retinal vessel detection is a significant task in the identification of retinal disease regions. This study presents a retinal vessel detection ...