Thesis – Task-Aware Joint Optimization for Efficient Edge Face Recognition

Axis Communications; Lunds kommun; On-site; SEK 17,000 - 28,000; Full time

Job summary

Axis Communications seeks Master’s or Bachelor students in Computer Science or Software Engineering for a thesis project on task-aware joint optimization for efficient edge face recognition. The project focuses on balancing identity-discriminative information with reduced image detail and processing overhead on FPGA-based edge systems.

Two students may work together, applying to the Axis thesis program. Applicants should attach CV and university grade summaries; contact Marie Åkesson for

Qualifications

• Master's or Bachelor student in Computer Science, Software Engineering, or a related field.

Responsibilities

• Develop a task-aware joint optimization framework for front-end processing and face recognition on resource-constrained edge devices.
• Collaborate on integrating a lightweight, quantized recognition network and evaluate performance across imaging conditions, computational load and energy use.

Education

Computer Science

Software Engineering

Job description

Job TitleThesis – Task-Aware Joint Optimization for Efficient Edge Face RecognitionJob DescriptionCategoryComputer Science, Software EngineeringScope1-2 Master thesis students or 2 Bachelor thesis studentsBackgroundFace recognition in intercoms and access control systems requires reliable performance under varying imaging conditions while operating within limited computational and energy budgets. Recent studies have explored spectral convolution for efficient front-end processing directly in image sensors [1] and sub-byte quantization to reduce the computational requirements of mobile face-recognition networks [2]. However, the joint optimization of front-end processing parameters and face-recognition networks remains underexplored, particularly in terms of selecting task-relevant image information to balance recognition of reliability and computational efficiency.GoalThe goal of this project is to develop a task-aware joint optimization framework for front-end processing and face recognition on resource-constrained edge devices. The front end will be optimized to preserve essential identity-discriminative information while reducing unnecessary image detail and processing overhead. In combination with a lightweight, quantized recognition network, the proposed approach will be evaluated in terms of recognition reliability under varying imaging conditions, computational complexity, and energy consumption, with implementation targeting FPGA-based edge systems.Who are you?Master's or Bachelor student in Computer Science, Software Engineering, or a related field.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 Åkesson on [phone] or [e-mail]1 Cui, Kaiyu, et al. \"Spectral convolutional neural network chip for in-sensor edge computing of incoherent natural light.\" Nature Communications 16.1 (2025): 81.2 Bunda, Sebastian, Luuk Spreeuwers, and Chris Zeinstra. \"Sub-byte quantization of mobile face recognition convolutional neural networks.\" 2022 International Conference of the Biometrics Special Interest Group (BIOSIG). IEEE, 2022.Type of EmploymentThesis Worker (Fixed Term)Posting End Date2026-11-27Certain 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 CommunicationsWe enable a smarter and 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 6,000 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 and safer worldFor more information about Axis, please visit our website www.axis.com .Listen to Axis Communications Playlist