Transfer Learning Coupled Convolution Neural Networks in Detecting Retinal Diseases Using OCT Images

Parking vehicles are one of the most frustrating tasks that people face these days. Locating an available parking space is a huge headache especially in urban areas. This paper aims to design one such parking system which, in many ways reduces the hassles of parking. The paper presents a system where a Machine Learning model, Convolution Neural Network(CNN) is used to classify parking slots in a parking space into vacant and filled slots. In order to optimize the task of classification, the method of Transfer Learning is implemented in the paper. The problem of parking stands not only limited to causing inconvenience to the drivers, but also escalates to much larger and extensive problems, affecting a lot more people the environment. Hence it is very important to have a system is used parking system in place. The model proposed in the paper sends across parking information to a driver well in advance, there by greatly reducing the waiting time for the vehicle.

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Transfer Learning with Convolution Neural Networks Models: An Evolutional Comparison

Artificial Intelligence and Global Society ◽

10.1201/9781003006602-7 ◽

2021 ◽

pp. 67-78

Author(s):

Aditi Kajala ◽

Vinod Kumar Jain

Keyword(s):

Neural Networks ◽

Transfer Learning ◽

Convolution Neural Networks

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Exploring Deep Convolution Neural Networks with Transfer Learning for Rectum Toxicity Prediction in Cervical Cancer Radiotherapy

Brachytherapy ◽

10.1016/j.brachy.2017.04.042 ◽

2017 ◽

Vol 16 (3) ◽

pp. S33-S34 ◽

Cited By ~ 1

Author(s):

Xin Zhen ◽

Jiawei Chen ◽

Zichun Zhong ◽

Brian Hrycushko ◽

Steve Jiang ◽

...

Keyword(s):

Neural Networks ◽

Cervical Cancer ◽

Transfer Learning ◽

Toxicity Prediction ◽

Cancer Radiotherapy ◽

Convolution Neural Networks

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MCFT-CNN: Malware classification with fine-tune convolution neural networks using traditional and transfer learning in Internet of Things

Future Generation Computer Systems ◽

10.1016/j.future.2021.06.029 ◽

2021 ◽

Author(s):

Sudhakar ◽

Sushil Kumar

Keyword(s):

Neural Networks ◽

Internet Of Things ◽

Transfer Learning ◽

Convolution Neural Networks ◽

Malware Classification ◽

Fine Tune

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The machine training in problems of satellite images’s processing

Metrologiya ◽

10.32446/0132-4713.2020-4-15-37 ◽

2020 ◽

pp. 15-37

Author(s):

L. P. Bass ◽

Yu. A. Plastinin ◽

I. Yu. Skryabysheva

Keyword(s):

Remote Sensing ◽

Neural Networks ◽

Computer Vision ◽

Satellite Images ◽

Vision Systems ◽

Earth Remote Sensing ◽

Practical Applications ◽

Convolution Neural Networks ◽

Computer Vision Systems ◽

Trained Neural Network

Use of the technical (computer) vision systems for Earth remote sensing is considered. An overview of software and hardware used in computer vision systems for processing satellite images is submitted. Algorithmic methods of the data processing with use of the trained neural network are described. Examples of the algorithmic processing of satellite images by means of artificial convolution neural networks are given. Ways of accuracy increase of satellite images recognition are defined. Practical applications of convolution neural networks onboard microsatellites for Earth remote sensing are presented.

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