prashpratik / object-recognition-using-automotive-ultrasonic-sensor-redpitaya-and-raspberry-pi

Object Recognition using Automotive Ultrasonic Sensor, RedPitaya and Raspberry Pi through Machine Learning classifiers and Deep Learning Neural Network

Object-Recognition-using-Automotive-Ultrasonic-Sensor-RedPitaya-and-Raspberry-Pi

In this project, I have developed an Object Recognition System using Automotive Ultrasonic Sensor, RedPitaya and Raspberry Pi through Machine Learning classifiers and Deep Learning Neural Network. For this purpose, I have used SRF02 Automotive ultrasonic sensor, Red Pitaya and Raspberry Pi 4 as electronic hardware tools. For software part, I have implemented three different object classifiers. These are Naive Bayes classifier, Support Vector Machine (SVM) classifier and classification through LSTM (Long Short-Term Memory). Both Naive Bayes classifier and SVM classifier are Machine Learning algorithms whereas LSTM is a type of Deep Learning Artificial Neural Network. Also, I took three objects for classification – Wall, Human and Car.