Projects
Classification of Stationary Items using ML

Classification of Stationary Items using ML

Team: dheerajbhatia60

Project Details

Project Description: We have created a Machine learning based model to classify between eraser and pencil using object recognition technique. Object Recognition: Object recognition is the technique of identifying the object present in images and videos. It is one of the most important applications of machine learning and artificial intelligence. The goal of this field is to teach machines to understand (recognize) the content of an image just like humans do. Image Classification: In Image classification, it takes an image as an input and outputs the classification label of that image with some metric like probability, loss, accuracy, etc. Applications: • Driver-less Cars: Object Recognition is used for detecting road signs, other vehicles, etc. • Medical Image Processing: Object Recognition and Image Processing techniques can help detect disease more accurately. Image segmentation helps to detect the shape of the defect present in the body. For Example, Google AI for breast cancer detection detects more accurately than doctors. • Surveillance and Security: such as Face Recognition, Object Tracking, Activity Recognition, etc. Here you can see the model we have implemented. First, I opened AI and ML environment, named the project and then uploaded the images of objects collected from internet. Now we trained the machine with 10 number of epochs. Training accuracy is approx. 0.92. It can be enhanced by inserting more samples at the time of training. After completion of training test has been performed to differentiate between pencil and eraser. And then model is ported to block code environment. So now it can be used as a product.
Project Theme: Automate the Surroundings
Project Category: AI and ML Projects
Country: India