Comparison of computer vision models for object detection using low-power hardware

Prilikom izvođenja algoritama računalnog vida za potrebe detekcije objekata pretežito se koristi sklopovlje s visokim procesorskim performansama. Pritom, ako se isti koriste u stvarnom vremenu na sklopovlju s niskim performansama javlja se problem nedostatka procesorske snage. Kao rješenje nameće se upotreba algoritama zasnovanih na jednom prolasku kroz sliku (engl. singl shot detection). U ovome radu napravit će se usporedba različitih modela računalnog vida za detekciju objekata na konkretnom ugradbenom sklopu niske potrošnje. Rezultati rada će se koristiti za odabir optimalnog modela s obzirom na parametre poput primjerice potrošnje energije sklopovlja, brzine obrade podataka te preciznost odabranog modela. Svu potrebnu literaturu osigurat će središnja knjižnica fakulteta te Zavod za osnove elektrotehnike i električna mjerenja.When performing computer vision algorithms, high-performance hardware is predominantly used for object detection purposes. In addition, if they are used in real time on low-performance hardware, there is a problem of lack of processing power. As a solution, the use of algorithms based on single shot detection is imposed. In this paper, a comparison of different computer vision models for object detection on a specific low - consumption installation will be made. The results of the work will be used to select the optimal model with regard to parameters such as hardware power consumption, data processing speed and accuracy of the selected model. All the necessary literature will be provided by the central library of the faculty and the Department of Fundamentals of Electrical Engineering and Electrical Measurements