Satellite Images Unsupervised Classification Using Two Methods Fast Otsu and K-means
Publication Date
Sat Jun 06 2020
Journal Name
Journal Of The College Of Education For Women
Image classification with Deep Convolutional Neural Network Using Tensorflow and Transfer of Learning
Convolutional Neural Network (CNN)
Synthetic Aperture Radar (SAR)
TensorFlow
Transfer learning
Visual Geometry Group (VGG16)
The deep learning algorithm has recently achieved a lot of success, especially in the field of computer vision. This research aims to describe the classification method applied to the dataset of multiple types of images (Synthetic Aperture Radar (SAR) images and non-SAR images). In such a classification, transfer learning was used followed by fine-tuning methods. Besides, pre-trained architectures were used on the known image database ImageNet. The model VGG16 was indeed used as a feature extractor and a new classifier was trained based on extracted features.The input data mainly focused on the dataset consist of five classes including the SAR images class (houses) and the non-SAR images classes (Cats, Dogs, Horses, and Humans). The Conv
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Publication Date
Fri May 05 2017
Journal Name
International Journal Of Science And Research (ijsr)
Automatic brain tumor segmentation from MRI images using region growing algorithm
Image Segmentation
Automatic Region Growing
MRI
Brain Tumor
LK Abood, RA Ali, M Maliki, International Journal of Science and Research, 2015 - Cited by 2
Publication Date
Mon Jun 16 2025
Journal Name
Journal Of Physical Education
Publication Date
Sun May 07 2017
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Development Of Two Different Spectrophotometric Methods For The Determination Of Atropine Drug In Pure Form And Pharmaceutical Preparations
Spectrophotometric
atropine
ion-pair
charge-transfer
Two methods have been applied for the spectrophotometric determination of atropine, in
bulk sample and in dosage form. The methods are accurate, simple, rapid, inexpensive and
sensitive. The first method depending on the extraction of the formed ion-pair complex with
bromphenol blue (BPB) as a chromogenic reagent in chloroform, use phthalate buffer of pH
3.0; which showed absorbance maxima at 413 nm against reagent blank. The calibration
graph is linear in the ranges of 0.5-40 µg.mL
-1
with detection limit of 0.363µg.mL
-1
. The
second method depending on the measure of the absorbance maxima of the formed charge-transfer complex with 2,3-dichloro-5,6-dicyano-p-benzoquinone (DDQ) at 457 nm against
Publication Date
Tue May 01 2012
Journal Name
Engineering Analysis With Boundary Elements
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Publication Date
Sat Oct 01 2016
Journal Name
2016 6th International Conference On Information Communication And Management (icicm)
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(2)
Publication Date
Thu May 05 2022
Journal Name
Periodicals Of Engineering And Natural Sciences (pen)
Publication Date
Thu Apr 27 2017
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
The Construction of (k,3)-Arcs in PG(2,9) by Using Geometrical Method
arcs
secant
Projective
Plane
In this work, we construct projectively distinct (k,3)-arcs in the projective plane PG(2,9) by applying a geometrical method. The cubic curves have been been constructed by using the general equation of the cubic. We found that there are complete (13,3)-arcs, complete (15,3)-arcs and we found that the only (16,3)-arcs lead to maximum completeness
Publication Date
Tue Aug 10 2021
Journal Name
Design Engineering
Lossy Image Compression Using Hybrid Deep Learning Autoencoder Based On kmean Clusteri
Image compression
Convolutional Autoencoder (CAE)
k-mean algorithm
PSNR
Compression Rate (CR)
MSE
Clustering
CLIC
Kodak
deep learning
lossy
Image compression plays an important role in reducing the size and storage of data while increasing the speed of its transmission through the Internet significantly. Image compression is an important research topic for several decades and recently, with the great successes achieved by deep learning in many areas of image processing, especially image compression, and its use is increasing Gradually in the field of image compression. The deep learning neural network has also achieved great success in the field of processing and compressing various images of different sizes. In this paper, we present a structure for image compression based on the use of a Convolutional AutoEncoder (CAE) for deep learning, inspired by the diversity of human eye
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Wed Jul 01 2020
Journal Name
Proceedings Of The Institution Of Mechanical Engineers, Part H: Journal Of Engineering In Medicine
Comparison study of classification methods of intramuscular electromyography data for non-human primate model of traumatic spinal cord injury
Traumatic spinal cord injury is a serious neurological disorder. Patients experience a plethora of symptoms that can be attributed to the nerve fiber tracts that are compromised. This includes limb weakness, sensory impairment, and truncal instability, as well as a variety of autonomic abnormalities. This article will discuss how machine learning classification can be used to characterize the initial impairment and subsequent recovery of electromyography signals in an non-human primate model of traumatic spinal cord injury. The ultimate objective is to identify potential treatments for traumatic spinal cord injury. This work focuses specifically on finding a suitable classifier that differentiates between two distinct experimental
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