scholarly journals A Neural Network based Method for Brain Abnormality Detection in MR Images Using Gabor Wavelets

2010 ◽  
Vol 4 (7) ◽  
pp. 9-15 ◽  
Author(s):  
AmirEhsan Lashkari
Keyword(s):  
Neural Network ◽  
Gabor Wavelets ◽  
Abnormality Detection ◽  
Mr Images ◽  
Brain Abnormality

PH-0411: Neural network based MR-only treatment planning for cervix cancer using low field MR images

2020 ◽  
Vol 152 ◽  
pp. S221-S222
Author(s):  
M. Buschmann ◽  
L. Fetty ◽  
G. Heilemann ◽  
M. Heilmann ◽  
P. Kuess ◽  
...  
Keyword(s):  
Neural Network ◽  
Treatment Planning ◽  
Cervix Cancer ◽  
Mr Images ◽  
Low Field

Developing brain abnormality recognize system using multi-objective pattern producing neural network

2018 ◽  
Vol 10 (8) ◽  
pp. 3287-3295 ◽  
Author(s):  
K. P. Sridhar ◽  
S. Baskar ◽  
P. Mohamed Shakeel ◽  
V. R. Sarma Dhulipala
Keyword(s):  
Neural Network ◽  
Developing Brain ◽  
Multi Objective ◽  
Brain Abnormality

Whole Tumor Segmentation from Brain MR images using Multi-view 2D Convolutional Neural Network

2021 ◽  
Author(s):  
Ritu Lahoti ◽  
Sunil Kumar Vengalil ◽  
Punith B Venkategowda ◽  
Neelam Sinha ◽  
Vinod Veera Reddy
Keyword(s):  
Neural Network ◽  
Convolutional Neural Network ◽  
Tumor Segmentation ◽  
Mr Images ◽  
Brain Mr Images

Pedestrian Attribute Recognition using Gabor Wavelet Layers

2021 ◽  
Author(s):  
Imran N. Junejo
Keyword(s):  
Neural Network ◽  
Public Spaces ◽  
Convolution Neural Network ◽  
Gabor Wavelet ◽  
Gabor Wavelets ◽  
Age Group ◽  
Clothing Style ◽  
Public Dataset ◽  
Attribute Recognition ◽  
Almost All

We address the problem of Pedestrian Attribute Recognition (PAR) in this paper. Owing to the presence of surveillance cameras in almost all outdoor and indoor public spaces, keeping and eye on pedestrian is a sought-after task with many useful applications. The problem entails recognizing attributes such as age-group, clothing style, accessories, footwear style etc. This is a multi-label problem and challenging even for human observers. We propose using a convolution neural network (CNN) with trainable Gabor wavelets (TGW) layers. The proposed layers are learnable and adapt to the dataset for a better recognition. The proposed multi-branch neural network is a mix of TGW and convolutional layers and we show its effectiveness on a public dataset.

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