Master Thesis - Learning from Specific Scenarios to Improve a Pre-trained Edge Model

Job Title

Job Description

Category

Computer Science, Artificial Intelligence 

Scope

Master Thesis 30 hp, 2 students completing 30 credits each 

Background

Surveillance systems often rely on pre-installed cameras operating in well-defined, fixed environments. In such setups, the visual context or scenario remains relatively similar over time. This creates a valuable opportunity — by learning from a specific camera's scenario using a small number of annotated examples to improve performance. 

Goal

The objective of this thesis is to investigate how scenario-specific learning can improve the performance of a pre-trained deep learning model in real-world applications. Specifically, the aim is to explore methods for precision and recall enhancement when limited data from a known environment is available.  

This thesis will evaluate and compare various deep learning strategies, network architecture changes, and training approaches tailored to this task. These include:   

• Server-based training: Traditional training pipelines where models are trained in the cloud or on powerful servers and then deployed.  

• Edge/device-based training: On-camera or on-prem-device training. 

• Zero-training approaches: Methods that leverage pre-trained models and scenario-specific adaptation without the need for retraining.  

The thesis work includes implementation and testing of multiple methods across these categories and conducting a systematic comparison of their performance, scalability, computational cost, and suitability for deployment in constrained environments. The thesis will also discuss trade-offs between model complexity, generalization ability, and responsiveness to new scenario-specific data.  

Who are you? 

For this Thesis proposal we target students with a strong interest in Artificial Intelligence and Machine Learning. Most likely you are studying a Master Program with courses in Machine Intelligence or Computer Vision 

OK, I am interested! What do I do now?
You are valuable to us – how nice that you are interested in one of our proposals! There are a few things for you to keep in mind when applying.

• Applications are accepted in both Swedish and English, and you apply via the proposal advert.
• The announced thesis is open only to students affiliated with a Swedish University/College either directly or via an exchange program.
• When the thesis proposal states that it includes two students working together, we would like you to apply in pairs. In these cases, send one application each but make sure to clearly state in your application who your co-applicant is. If you have any questions regarding this, please do not hesitate to contact us.
• Please attach your CV and University/College grade summary.

Who to contact for any questions regarding the position!

Marie Lundin Marie.Lundin@axis.com 

Type of Employment

Posting End Date

Certain roles at Axis require background checks, which means applicable verifications will be done in these recruitments. Notice will be provided before we take any action.

About Axis Communications

We enable a smarter, safer world by creating innovative solutions for improving security and business performance. As a network technology company and industry leader, we offer solutions in video surveillance, access control, intercom, and audio systems, enhanced by intelligent analytics applications.

With around 5000 committed employees in over 50 countries, we collaborate with partners worldwide. Together, we thrive in our friendly, open, and collaborative culture and inspire each other to think beyond the expected. United by our commitment to inclusion, diversity, and sustainability, we consistently seek to develop our skills and way of working.

Let´s create a smarter, safer world

For more information about Axis, please visit our website www.axis.com.

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