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1	Investigation of Increased Mapping Quality Generated by a Neural Network for Camera-LiDAR Sensor Fusion / Ökning av kartläggningskvalitet genom att använda ett neuralt natverk för fusion av kamera och LiDAR data Correa Silva, Joan Li Guisell, Jönsson, Sofia January 2021 (has links) This study’s aim was to investigate the mapping part of Simultaneous Localisation And Mapping (SLAM) in indoor environments containing error sources relevant to two types of sensors. The sensors used were an Intel Realsense depth camera and an RPlidar Light Detection AndRanging (LiDAR). Both cameras and LiDARs are frequently used as exteroceptive sensors in SLAM. Cameras typically struggle with strong light in the environment, and LiDARs struggle with reflective surfaces. Therefore, this study investigated the possibility of using a neural network to detect an error in either sensors’ data caused by mentioned error sources. The network identified which sensor produced erroneous data. The sensor fusion algorithm momentarily excluded said sensor’s data, consequently, improving the mapping quality when possible. The quantitative results showed no significant difference in the measured mean squared error and structural similarity between the final maps generated with and without the network, when compared to the ground truth. However, the qualitative analysis showed some advantages with using the network. Many of the camera’s errors were filtered out with the neural network, and led to a more accurate continuous mapping than without the network implemented. The conclusion was that a neural network can to a limited extent recognise the sensors’ data errors, but only the camera data benefited from the proposed solution. The study also produced important findings from the implementation which are presented. Future work recommendations include neural network optimisation, sensor selection, and sensor fusion implementation. / Denna studie undersökte kartläggningen i Simultaneous Localisation And Mapping (SLAM) problem, i kontexten av två sensorers felkällor. Sensorerna som användes var en Intel Realsense djupseende kamera samt en LiDAR fran RPlidar. Både kameror och LiDARs är vanliga sensorer i SLAM system, och båda har olika typer av felkällor. Kameror är typiskt känsliga för mycket starkt ljus, medan LiDARs har svårt med reflekterande ytor. Med detta som bakgrund har denna studie undersökt möjligheten att implementera ett neuralt nätverk för att detektera när varje sensor är utsatt för en felkälla (och därmed ger fel data). Nätverkets klassificering används sedan för att i varje tidssteg exkludera den sensors data som det är fel på för att förbättra kartläggningen. De qvantitativa resultaten visade ingen signifikant skillnad mellan kartorna genererade med nätverket och de utan nätverket. Dock visade den kvalitativa analysen att det finns vissa fördelar med att använda det neutrala nätverket. Manga av kamerans fel blev korrigerade när nätverket var implementerat, vilket ledde till mer korrekta kartor under kontinuerlig körning. Slutsatsen blev att ett nätverk kan bli tränat för att identifiera fel i datan, men att kameran drar mest nytta av det. Studien producerade även sekundara resultat som också redovisas. Slutligen rekommenderas optimering av nätverket, val av sensorer, samt uppdaterad algoritm för sensor fusionen som möjliga områden till fortsatt forskning inom området. sensor fusion error detection neural network sources of error mapping quality SLAM sensor fusion felavkänning neuralt nätverk felkällor kartläggningskvalitet SLAM Mechanical Engineering Maskinteknik
2	Om informationstekniskt bevis Ekfeldt, Jonas January 2016 (has links) Information technology evidence consists of a mix of representations of various applications of digital electronic equipment, and can be brought to the fore in all contexts that result in legal decisions. The occurrence of such evidence in legal proceedings, and other legal decision-making, is a phenomenon previously not researched within legal science in Sweden. The thesis examines some of the consequences resulting from the occurrence of information technology evidence within Swedish practical legal and judicial decision-making. The thesis has three main focal points. The first consists of a broad identification of legal problems that information technology evidence entails. The second focal point examines the legal terminology associated with information technology evidence. The third focal point consists of identifying sources of error pertaining to information technology evidence from the adjudicator’s point of view. The examination utilizes a Swedish legal viewpoint from a perspective of the public trust in courts. Conclusions include a number of legal problems in several areas, primarily in regards to the knowledge of the adjudicator, the qualification of different means of evidence and the consequences of representational evidence upon its evaluation. In order to properly evaluate information technology evidence, judges are – to a greater extent than for other types of evidence – in need of (objective) knowledge supplementary to that provided by parties and their witnesses and experts. Furthermore, the current Swedish evidence terminology has been identified as a complex of problems in and of itself. The thesis includes suggestions on certain additions to this terminology. Several sources of error have been identified as being attributable to different procedures associated with the handling of information technology evidence, in particular in relation to computer forensic investigations. There is a general need for future research focused on matters regarding both standards of proof for and evaluation of information technology evidence. In addition, a need for deeper legal scientific studies aimed at evidence theory has been identified, inter alia regarding the extent to which frequency theories are applicable in respect to information technology evidence. The need for related further discussions on future emerging areas such as negative evidence and predictive evidence are foreseen. accountability audit trail authenticity computer evidence criminal procedure data quality digital evidence digital images digital traces electronic evidence evaluation of evidence evidence law evidence terminology evidential value evidentiary facts forensic evidence handling of evidence ict-evidence informatics information quality information representation information security it-evidence law and information technology legal evidence log log analysis machine identity means of evidence personal identity reliability representation information screen dump sources of error traceability validity autenticitet bevisfakta bevismedel bevishantering bevisprövning bevisrätt bevisterminologi bevisvärdering datakvalitet digitala bevis digitala bilder digitala spår elektroniska bevis elektroniska spår felkällor filer forensiska bevis ikt informatik informationskvalitet informationsrepresentation informationsteknik informationstekniskt bevis it-bevis it-säkerhet juridiskt bevis logganalys maskinell identitet personell identitet principen om fri bevisprövning representationsinformation riktighet rättsinformatik skärmdump spårbarhet straffprocessrätt

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Investigation of Increased Mapping Quality Generated by a Neural Network for Camera-LiDAR Sensor Fusion / Ökning av kartläggningskvalitet genom att använda ett neuralt natverk för fusion av kamera och LiDAR data

Om informationstekniskt bevis