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Dermatologist-level classification of skin cancer with deep neural networks

￥240-2000 CNY

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Julkaistu

yli 6 vuotta sitten

￥240-2000 CNY

Maksettu toimituksen yhteydessä

skin cancer using deep learning.I needed to improve the accuracy of, three way accuracy and nine way accuracy. you can used any algo of deep learning to improve the accuracy.... here i attached the artical, please first check the artical and then talk with me. 1. at the end of paper results are given, i needed improve resutls 2. data set link are avalable in paper

Matlab and Mathematica

Projektin tunnus (ID): 14996565

Tietoa projektista

4 ehdotukset

Etäprojekti

Aktiivinen 7 vuotta sitten

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Sähköpostiosoite

Freelancerin tarjouskilpailun edut

Aseta budjettisi ja aikataulu

Saa maksu työstäsi

Kuvaile ehdotustasi

Rekisteröinti ja töihin tarjoaminen on ilmaista

4 freelancerit tarjoavat keskimäärin ￥2 390 CNY tätä projektia

Maan NIGERIA lippu

Hi, I'm postive about offering an outstanding services that will lead to a long term business relationship. I will like to ask? When do you need the service delivered and how much can you pay for it? Relevant Skills and Experience We can discuss further and see how I can help you better I have several years of experience in this and willing to use my experience to meet your immediate need. Please reply and give me a trial.

￥1 244 CNY 3 päivässä

4,0

(6 arvostelua)

4,0

4,0

Maan INDIA lippu

A proposal has not yet been provided

￥1 650 CNY 3 päivässä

0,0

(1 arvostelu)

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Julkaise tällainen projekti

Tietoja asiakkaasta

Maan CHINA lippu

hefei, China

5,0

3

Liittynyt elok. 11, 2017

Asiakkaan vahvistus

Muita töitä tältä asiakkaalta

Two vedios and each vedio have 15 second, using deep learning classificaton and compared the both vedios

predict the future of this data set using fellowing methods, see project description

Find the corelation between the image using deep learning or deep neural network

we have two type of image and want to classify using deep learning(see details attach document)

just print the accuracy ( code is attached)

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