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| Fältnamn | Indikatorer | Metadata |
|---|---|---|
| 000 | 05810nam a2200517 4500 | |
| 001 | oai:research.chalmers.se:44c5606c-9a8a-4d56-8e25-4c2cb22d48e8 | |
| 003 | SwePub | |
| 008 | 230901s2023 | |||||||||||000 ||eng| | |
| 024 | 7 | a https://research.chalmers.se/publication/5372362 URI |
| 040 | a (SwePub)cth | |
| 041 | a engb eng | |
| 042 | 9 SwePub | |
| 072 | 7 | a lic2 swepub-publicationtype |
| 072 | 7 | a vet2 swepub-contenttype |
| 100 | 1 | a Blanch, Krister,d 1991u Chalmers tekniska högskola,Chalmers University of Technology4 aut0 (Swepub:cth)blanch |
| 245 | 1 0 | a Beyond-application datasets and automated fair benchmarking |
| 264 | 1 | a Gothenburg,c 2023 |
| 338 | a electronic2 rdacarrier | |
| 520 | a Beyond-application perception datasets are generalised datasets that emphasise the fundamental components of good machine perception data. When analysing the history of perception datatsets, notable trends suggest that design of the dataset typically aligns with an application goal. Instead of focusing on a specific application, beyond-application datasets instead look at capturing high-quality, high-volume data from a highly kinematic environment, for the purpose of aiding algorithm development and testing in general. Algorithm benchmarking is a cornerstone of autonomous systems development, and allows developers to demonstrate their results in a comparative manner. However, most benchmarking systems allow developers to use their own hardware or select favourable data. There is also little focus on run time performance and consistency, with benchmarking systems instead showcasing algorithm accuracy. By combining both beyond-application dataset generation and methods for fair benchmarking, there is also the dilemma of how to provide the dataset to developers for this benchmarking, as the result of a high-volume, high-quality dataset generation is a significant increase in dataset size when compared to traditional perception datasets. This thesis presents the first results of attempting the creation of such a dataset. The dataset was built using a maritime platform, selected due to the highly dynamic environment presented on water. The design and initial testing of this platform is detailed, as well as as methods of sensor validation. Continuing, the thesis then presents a method of fair benchmarking, by utilising remote containerisation in a way that allows developers to present their software to the dataset, instead of having to first locally store a copy. To test this dataset and automatic online benchmarking, a number of reference algorithms were required for initial results. Three algorithms were built, using the data from three different sensors captured on the maritime platform. Each algorithm calculates vessel odometry, and the automatic benchmarking system was utilised to show the accuracy and run-time performance of these algorithms. It was found that the containerised approach alleviated data management concerns, prevented inflated accuracy results, and demonstrated precisely how computationally intensive each algorithm was. | |
| 650 | 7 | a NATURVETENSKAPx Data- och informationsvetenskapx Datorteknik0 (SwePub)102062 hsv//swe |
| 650 | 7 | a NATURAL SCIENCESx Computer and Information Sciencesx Computer Engineering0 (SwePub)102062 hsv//eng |
| 650 | 7 | a NATURVETENSKAPx Data- och informationsvetenskapx Programvaruteknik0 (SwePub)102052 hsv//swe |
| 650 | 7 | a NATURAL SCIENCESx Computer and Information Sciencesx Software Engineering0 (SwePub)102052 hsv//eng |
| 650 | 7 | a TEKNIK OCH TEKNOLOGIERx Elektroteknik och elektronik0 (SwePub)2022 hsv//swe |
| 650 | 7 | a ENGINEERING AND TECHNOLOGYx Electrical Engineering, Electronic Engineering, Information Engineering0 (SwePub)2022 hsv//eng |
| 650 | 7 | a TEKNIK OCH TEKNOLOGIERx Elektroteknik och elektronikx Robotteknik och automation0 (SwePub)202012 hsv//swe |
| 650 | 7 | a ENGINEERING AND TECHNOLOGYx Electrical Engineering, Electronic Engineering, Information Engineeringx Robotics0 (SwePub)202012 hsv//eng |
| 650 | 7 | a TEKNIK OCH TEKNOLOGIERx Elektroteknik och elektronikx Signalbehandling0 (SwePub)202052 hsv//swe |
| 650 | 7 | a ENGINEERING AND TECHNOLOGYx Electrical Engineering, Electronic Engineering, Information Engineeringx Signal Processing0 (SwePub)202052 hsv//eng |
| 650 | 7 | a NATURVETENSKAPx Data- och informationsvetenskapx Datavetenskap0 (SwePub)102012 hsv//swe |
| 650 | 7 | a NATURAL SCIENCESx Computer and Information Sciencesx Computer Sciences0 (SwePub)102012 hsv//eng |
| 650 | 7 | a TEKNIK OCH TEKNOLOGIERx Elektroteknik och elektronikx Datorsystem0 (SwePub)202062 hsv//swe |
| 650 | 7 | a ENGINEERING AND TECHNOLOGYx Electrical Engineering, Electronic Engineering, Information Engineeringx Computer Systems0 (SwePub)202062 hsv//eng |
| 650 | 7 | a NATURVETENSKAPx Data- och informationsvetenskapx Datorseende och robotik0 (SwePub)102072 hsv//swe |
| 650 | 7 | a NATURAL SCIENCESx Computer and Information Sciencesx Computer Vision and Robotics0 (SwePub)102072 hsv//eng |
| 650 | 7 | a TEKNIK OCH TEKNOLOGIERx Elektroteknik och elektronikx Annan elektroteknik och elektronik0 (SwePub)202992 hsv//swe |
| 650 | 7 | a ENGINEERING AND TECHNOLOGYx Electrical Engineering, Electronic Engineering, Information Engineeringx Other Electrical Engineering, Electronic Engineering, Information Engineering0 (SwePub)202992 hsv//eng |
| 653 | a algorithm evaluation | |
| 653 | a autonomous systems | |
| 653 | a containerisation | |
| 653 | a vehicle odometry | |
| 653 | a Beyond-application datasets | |
| 653 | a automatic fair benchmarking | |
| 710 | 2 | a Chalmers tekniska högskola4 org |
| 856 | 4 | u https://research.chalmers.se/publication/537236/file/537236_Fulltext.pdfx primaryx freey FULLTEXT |
| 856 | 4 8 | u https://research.chalmers.se/publication/537236 |
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