Elektroteknik (E2) // Electrical Engineering (E2)

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https://odr.chalmers.se/handle/20.500.12380/12

Arbetar med hållbara och smarta lösningar på samhällsutmaningar, såsom energieffektivitet och elektrifiering inom områden från transport- och produktionssystem till kommunikationslösningar och medicinteknik.

Läs mer om våra utbildningar

För forskning och forskningspublikationer, se https://research.chalmers.se/organisation/elektroteknik/

At the department of Electrical Engineering research and education are performed in the areas of Communication and Antenna systems, Systems and Control, Signal processing and Biomedical engineering, and Electric Power Engineering.

We work with challenges for a sustainable future in society of today, for example in the growing demands concerning efficient systems for communications and electrification. Our knowledge is of use everywhere where there is advanced technology with integrated electronics, no matter if it involves electricity, electrical signals, optical signals or microwaves.

Studying at the Department of Electrical Engineering at Chalmers

For research and research output, please visit https://research.chalmers.se/en/organization/electrical-engineering/

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Visar 1 - 20 av 2777

3D finite difference time domain simulations and analysis of thrombolytic treatment for microwave measurements of stroke patients
(2014) Stålnacke, Antti; Chalmers tekniska högskola / Institutionen för signaler och system; Chalmers University of Technology / Department of Signals and Systems
3D image reconstruction for biomedical application
(2020) von Hörsten, Henry; Chalmers tekniska högskola / Institutionen för elektroteknik; Gu, Irene
3D localization and mapping using automotive radar
(2016) Hammarsten, Markus; Runemalm, Viktor; Chalmers tekniska högskola / Institutionen för signaler och system; Chalmers University of Technology / Department of Signals and Systems
3D microwave tomography
(2011) Saeed, Adnan; Chalmers tekniska högskola / Institutionen för signaler och system; Chalmers University of Technology / Department of Signals and Systems
3D modelling and finite element analysis of three phase transformer with integrated inductors in COMSOL Multiphysics
(2020) Choudhary, Kunal; Chalmers tekniska högskola / Institutionen för elektroteknik; Serdyuk, Yuriy; Serdyuk, Yuriy
3D modelling of facial skin surface for 3D printing
(2017) Ekberg, Emma; Chalmers tekniska högskola / Institutionen för elektroteknik; Chalmers University of Technology / Department of Electrical Engineering
3D object detection for autonomous driving using deep learning
(2019) Berg Marklund, Olof; Hulthén, Oskar; Chalmers tekniska högskola / Institutionen för elektroteknik; Granström, Karl
3D Object Detection with Perceiver Adapting the Perceiver Architecture for 3D Object Detection with Automotive Image Data
(2024) Sedin, Linnéa; Andersson, Lydia; Chalmers tekniska högskola / Institutionen för elektroteknik; Kahl, Fredrik; Verbeke, Willem; Fatemi, Maryam; Johnander, Joakim
Abstract In the field of autonomous vehicles, accurately understanding and interpreting the environment and surroundings is vital for safe navigation. A robust perception system is fundamental in achieving this, and central to this is the use of computer vision techniques. This project investigates the adaptation of Perceiver [13] for 3D object detection using automotive image data. While the Perceiver architecture, which is based on Transformers, is designed for perception tasks, it has neither been evaluated on large input sizes nor tested on 3D object detection tasks. By using the ZOD dataset [2], which provides a comprehensive collection of automotive image data, this study aims to assess Perceiver’s capabilities in this context. Specifically, 3D object detection is exclusively done on camera images, targeting only vehicle objects. The proposed model in this project implements end-to-end object detection where the loss computation is inspired by the DETR loss computation [4]. The results indicate that the Perceiver architecture does not work without additional configuration for 3D object detection. Challenges in adapting the model highlight the need for further modifications and optimizations to improve its performance in this specific application. Despite these challenges, the study provides valuable insights into the potential and limitations of using the Perceiver architecture for 3D object detection with large input data. This study also provides insight into the impact of different additional modifications to the basic architecture.
3D Pose Estimation of Football Players
Osterman, Joakim; Sjögren, Olof; Chalmers tekniska högskola / Institutionen för elektroteknik; Svensson, Lennart; Sjöberg, Anders
Abstract In the context of football analytics, video recordings of matches play a crucial role in post-game analysis. However, videos are inherently limited because they only allow viewers to follow the match from the camera’s perspective. This thesis is part of a larger project aimed at creating 3D representations of football matches from video, thus enabling users to view the game from anywhere inside the virtual 3D environment. The larger project consists of three parts. This thesis focuses on estimating the camera parameters, as well as the 3D poses and locations of the players in the video. The other two projects focus on player tracking and player texture generation. A pipeline consisting of camera calibration and pose estimation is proposed, taking video recordings and bounding box annotations as input and predicting camera pa rameters as well as the players’ 3D poses and locations. For camera calibration, a model specifically tailored for cameras viewing football fields is used. The results indicate accurately predicted positions and viewing angles for the estimated camera. Pose estimation is performed using a pre-trained model and results in visually ac curate projections, although perspective ambiguities are present when the 3D poses are viewed from different angles. The main approach for positioning players was to detect when players touched the ground and interpolate the positions for ambigu ous frames. The results are promising, but noise in the depth estimations occurs due to perspective ambiguities. Subsequently, an optional optimization of poses and positions using multi-view triangulation is also presented, showing possibilities for further refinement to ensure realistic and consistent human poses. Future work on pose and location optimization could yield a pseudo-truth dataset for further enhancements to improve overall poses and positions from strictly monocular video.
3D real-time positioning system. Positioning and Signals Processing Techniques.
(2006) Kidborg, Stefan; Chalmers tekniska högskola / Institutionen för signaler och system; Chalmers University of Technology / Department of Signals and Systems
3D scenario generation using generative models
(2019) Ramazzina, Andrea; Chalmers tekniska högskola / Institutionen för elektroteknik; Kahl, Fredrik
3D Shape Generation through Point Transformer Diffusion
(2023) Lan, Ji; Chalmers tekniska högskola / Institutionen för elektroteknik; Kahl, Fredrik
Diffusion models are a novel class of generative models, which have demonstrated promising results in 3D point cloud generation. Meanwhile, Transformer-based models have achieved impressive outcomes across various benchmarks in the field of 3D point cloud understanding. However, the integration of a Transformer based on the local self-attention mechanism with a diffusion model for 3D point cloud generation remains unexplored. In this work, we propose Point Transformer Diffusion (PTD), a probabilistic and flexible generative model. PTD integrates the standard Denoising Diffusion Probabilistic Model, adapted for 3D data, with Point Transformer, a local self-attention network specifically designed for 3D point clouds. To enhance PTD’s performance, several adjustments and techniques are implemented to align the Point Transformer model more effectively with the diffusion model and with the specific generation task. Experiments demonstrate PTD’s ability to generate realistic and diverse shapes. Furthermore, the evaluation results of PTD are comparable to, and in some cases even marginally superior to, those achieved by Point-Voxel Diffusion, which is a state-of-the-art approach. We hope that our work will inspire future investigations into architectures that combine diffusion models and Transformers, along with their application to a wide range of 3D generation tasks.
3D video coding - Compression of depth maps for free viewpoint television
(2009) Su, Hui; Chalmers tekniska högskola / Institutionen för signaler och system; Chalmers University of Technology / Department of Signals and Systems
60 GHz contactless transition from microstrip to gap waveguide suitable for integration of RF MMIC with gap waveguide antenna
(2016) Nandi, Uttam; Chalmers tekniska högskola / Institutionen för signaler och system; Chalmers University of Technology / Department of Signals and Systems
600 V DC-DC converter for battery charger investigation
(2020) Rajendran, Udhayaraj; Krishnan, Ganapathy Nathan; Chalmers tekniska högskola / Institutionen för elektroteknik; Thiringer, Torbjörn; Thiringer, Torbjörn
6DOF camera localization through a short image sequence
(2020) Garsten, Jonas; Wikenstedt, Ivar; Chalmers tekniska högskola / Institutionen för elektroteknik; Sattler, Torsten
76-81 GHz planar antenna development and utilization for automotive radar applications
(2016) Wu, Dapeng; Chalmers tekniska högskola / Institutionen för signaler och system; Chalmers University of Technology / Department of Signals and Systems
A Channel Estimation Between a Base Station, Intelligent Reflecting Surface, and a User Equipment
(2023) Saltykova, Ekaterina; Chalmers tekniska högskola / Institutionen för elektroteknik; Monti, Paolo
A comparative study of reinforcement learning algorithms in a multi-agent system
(2019) Myhre, Ingjerd; Chalmers tekniska högskola / Institutionen för elektroteknik; Wymeersch, Henk
A comparison between MPC and PID controllers for education and steam reformers
(2014) Lindberg, Ylva; Chalmers tekniska högskola / Institutionen för signaler och system; Chalmers University of Technology / Department of Signals and Systems

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