Use deep learning to identify three types of rice leaf diseases. Photo by Dafne, Michael Mazourek on Dribbble Classifying plant species or diseases in plants can sometimes be a challenging task for the human eye, especially for people with limited experience in the field. There is little margin for error allowed when it comes to crops […]
Classifying diseases in rice leaves on cAInvas. Read More »
Photo by Süha Eryaşar on Dribbble The main use of this application is to do sheep detection from the image, which can then be used for many purposes like counting sheep and keeping track of the sheep in the yard. It will help farms to maintain a proper record of there sheep too. So, Lets get
Photo by ILLO on Dribbble Classifying different types of flowers based on their images drawn from different datasets. Some classes are very narrow, containing only a particular sub-type of flower (e.g. pink primroses) while other classes contain many sub-types (e.g. wild roses). Task Classification of flowers is a difficult task because there are flowers that look
Classifying Flower through Sequential-API-Deep Learning Read More »
Photo by Julien Laureau on Dribbble Introduction Fall detection is major problem in healthcare. Old people fall often and there should be immediate aid for them as injury can be series, even lead to the death. In this project, we will use Convolutional Neural Network architecture to detect whether a person has fallen or not in
Fall Detection using CNN architecture Read More »
Photo by Wevoke on Dribbble Introduction In this project, we will examine the data and build a deep neural network that will classify glass based upon certain features. Data Source The data is available publicly over the Kaggle from here you can easily download. About data The purpose of the dataset is predict the class of
Glass Classification Using Deep Learning Read More »
Photo by dongkyu lim on Dribbble We all come across numerous flowers on a daily basis. But we don’t even know their names at times. We all wonder “I wish my computer/mobile could classify this” when we come across a beautiful looking flower. That is the motive behind this article, to classify flower images. The main
Flower Classification using CNN Read More »
Photo by Irina Mir on Dribbble Context This database contains 76 attributes, but all published experiments refer to using a subset of 14 of them. In particular, the Cleveland database is the only one that has been used by ML researchers to this date. The “goal” field refers to the presence of heart disease in the
Heart Disease UCI Prediction using NN Read More »
Photo by Eugene Machiavelli for Shakuro on Dribbble You’ll want to evaluate almost every model you ever build. In most (though not all) applications, the relevant measure of model quality is predictive accuracy. In other words, will the model’s predictions be close to what actually happens. Many people make a huge mistake when measuring predictive accuracy.
Mobile Price Range Classifier Read More »