A MACHINE LEARNING-BASED PRICE PREDICTION FOR COWS

Autor: Md Atiquer Rahman, Md Alamgir Kabir, Md. Ezazul Haque, B M Mainul Hossain
Rok vydání: 2021
DOI: 10.5281/zenodo.4817940
Popis: 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%.
Databáze: OpenAIRE