EXAMINATION OF A UAV IMAGE CLASSIFICATION METHOD BY USING MACHINE LEARNING AND WAVELET TRANSFORM

2018 ◽  
Vol 74 (5) ◽  
pp. I_607-I_612
Author(s):  
Akito MOMOSE ◽  
Hitoshi MIYAMOTO ◽  
Shuji IWAMI ◽  
Takayuki NAGAYA
Keyword(s):  
Machine Learning ◽  
Wavelet Transform ◽  
Image Classification ◽  
Classification Method ◽  
Uav Image

scholarly journals EXAMINATION OF A UAV IMAGE CLASSIFICATION METHOD BY USING MACHINE LEARNING AND WAVELET TRANSFORM

2021 ◽  
Vol 9 (1) ◽  
pp. 284-290
Author(s):  
Akito MOMOSE ◽  
Hitoshi MIYAMOTO ◽  
Shuji IWAMI ◽  
Takayuki NAGAYA
Keyword(s):  
Machine Learning ◽  
Wavelet Transform ◽  
Image Classification ◽  
Classification Method ◽  
Uav Image

scholarly journals AI Enabled Face Mask Detector

2021 ◽  
Vol 9 (VI) ◽  
pp. 2980-2986
Author(s):  
Shivraj Patil
Keyword(s):  
Machine Learning ◽  
Global Health ◽  
Image Classification ◽  
Learning Algorithm ◽  
Face Mask ◽  
Classification Method ◽  
Machine Learning Algorithm ◽  
Health Crisis ◽  
The Face

Covid-19 pandemic is causing a global health crisis. To battle against the virus everyone should wear a face mask. The face mask detector in this study is developed with a machine learning algorithm called MobileNetV2 which is an image classification method. The steps to build the model are collecting the data, pre-processing, split the data, testing the model and implement the model.

Deep Learning Based High-Resolution Remote Sensing Image classification

2017 ◽  
Vol 7 (10) ◽  
pp. 22
Author(s):  
Sumit Kaur
Keyword(s):  
Machine Learning ◽  
Remote Sensing ◽  
Deep Learning ◽  
Image Classification ◽  
Language Processing ◽  
Object Perception ◽  
Remote Sensing Image ◽  
Research Area ◽  
Remote Sensing Image Classification ◽  
Unsupervised Algorithms

Abstract- Deep learning is an emerging research area in machine learning and pattern recognition field which has been presented with the goal of drawing Machine Learning nearer to one of its unique objectives, Artificial Intelligence. It tries to mimic the human brain, which is capable of processing and learning from the complex input data and solving different kinds of complicated tasks well. Deep learning (DL) basically based on a set of supervised and unsupervised algorithms that attempt to model higher level abstractions in data and make it self-learning for hierarchical representation for classification. In the recent years, it has attracted much attention due to its state-of-the-art performance in diverse areas like object perception, speech recognition, computer vision, collaborative filtering and natural language processing. This paper will present a survey on different deep learning techniques for remote sensing image classification. 

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