School of Science and Technology

Image Object Detection using Deep Learning

Motivation and scope

Object detection is the task of localizing and classifying objects in an image. It has a wide range of applications including object tracking, video surveillance, anomaly detection, object counting, and pedestrian and vehicle detection for self-driving cars. Recent scientific progress in deep learning has resulted in a number of powerful machine learning algorithms for object detection that opens up the possibilities for new and interesting applications.

Specific tasks 

The specific task in this project is to detect bees that have been infected with a small but visible parasite, called a varroa. From a given labeled data set your task is to train any state-of-the-art object detection algorithms and evaluate and compare the results with earlier results.

Necessary skills

Good programming skills in at least one of the following: Python, Tensorflow, Keras, PyTorch, and/or Matlab. Basic knowledge in machine learning.


You will learn how to work on a challenging machine learning project using deep learning-based object detection algorithms.


Martin Längkvist