Open AccessMachine Learning-Based Price Prediction for Cows
Author(s) -
Md Atiquer Rahman,
Md. Alamgir Kabir,
Md. Ezazul Haque,
Belal Hossain
Publication year - 2021
Publication title -
american journal of agricultural science, engineering, and technology
Language(s) - English
Resource type - Journals
eISSN - 2164-0920
pISSN - 2158-8104
DOI - 10.54536/ajaset.v5i1.63
Subject(s) - convolutional neural network , artificial neural network , machine learning , artificial intelligence , computer science , range (aeronautics) , agriculture , econometrics , mathematics , geography , engineering , aerospace engineering , archaeology
As Bangladesh is an agricultural country, cows have a great influence on our economy. However, there is no cow-related work or dataset accessible online in the fields of machine learning and artificial intelligence. This study aims to predict cow price ranges using any cow picture. Cow images were collected from different online e-commerce sites which are selling cows and mainly attempted to predict the price range of cows based on the images of the cows. Cows are divided into four classes based on their price range namely low, medium, high, and very high classes. A machine learning-driven approach has been taken for the prediction where convolutional neural network (CNN) is used as an image classifier and linear regression is used for predicting the prices. Our result shows that the price range of a cow can be predicted with an accuracy of 70%.