Sökning: "calibration detection"

Visar resultat 1 - 5 av 77 uppsatser innehållade orden calibration detection.

  1. 1. Quantification of Pharmaceuticals at the sub-cellular level using the NanoSIMS

    Uppsats för yrkesexamina på avancerad nivå, Uppsala universitet/Analytisk kemi

    Författare :Maryam Dost; [2024]
    Nyckelord :Mass spectroscopy imaging; AstraZeneca; Nanosims; Therapeutics; pharmacokinetics; pharmacodynamics; Quantitative Visualization; calibration curve; RSF; pharmacology; Data Analysis; Chemistry; Quantification; isotopes; Pharmaceuticals; subcellular; drug; drug target; nucleotide; biodistribution; Bioanalytical electrochemistry; spectroscopy; mass spectrometry; analytical separations; Analytical Chemistry; ROI; Bioanalytical Chemistry; Masspektroskopi avbildning; AstraZeneca; Nanosims; Terapeutik; farmakokinetik; farmakodynamik; Kvantitativ visualisering; kalibreringskurva; RSF; farmakologi; Dataanalys; Kemi; Kvantifiering; isotoper; Läkemedel; subcellulär; läkemedel; läkemedelsmål; bioskopisk elektrofördelning; nukleotid; bioskopisk bioskopisk distribution; masspektrometri; analytiska separationer; analytisk kemi; bioanalytisk kemi;

    Sammanfattning : Mass spectroscopy imaging (MSI) has become a vital tool in modern research due to its ability to visualize the spatial distribution of molecules within tissue samples. The collaboration between researchers at AZ, the University of Gothenburg, and Chalmers University of Technology using the NanoSIMS instrument and MSI-SIMS technology has opened up new avenues of exploration in pharmaceutical development, particularly in examining drugs and metabolites at sub-cellular levels. LÄS MER

  3. 2. Robust Multi-Modal Fusion for 3D Object Detection : Using multiple sensors of different types to robustly detect, classify, and position objects in three dimensions.

    Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Författare :Viktor Kårefjärd; [2023]
    Nyckelord :Computer Vision; 3D Object Detection; Multi-Modal Fusion; Deep Learning; Datorseenden; 3D-objektdetektion; Multimodal fusion; Djupinlärning;

    Sammanfattning : The computer vision task of 3D object detection is fundamentally necessary for autonomous driving perception systems. These vehicles typically feature a multitude of sensors, such as cameras, radars, and light detection and ranging sensors. LÄS MER

  4. 3. Static Extrinsic Calibration of a Vehicle-Mounted Lidar Using Spherical Targets

    Uppsats för yrkesexamina på avancerad nivå, Umeå universitet/Institutionen för fysik

    Författare :Philip Sandström; [2023]
    Nyckelord :;

    Sammanfattning : Self-driving cars are steadily becoming a reality by a growing number of driver assistance functions enabled by smart perception sensors. The light detection and ranging (lidar) sensor show great potential for perception tasks due to its precise distance measurements. LÄS MER

  5. 4. The effect of model calibration on noisy label detection

    Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Författare :Max Joel Söderberg; [2023]
    Nyckelord :Area Under the Margin; Calibration; Image classification; Label smoothing; Noisy labels; Overconfidence; Area under marginalen; Kalibrering; Bildklassificering; Etikettutjämning; Brusiga etiketter; Övertro;

    Sammanfattning : The advances in deep neural networks in recent years have opened up the possibility of using image classification as a valuable tool in various areas, such as medical diagnosis from x-ray images. However, training deep neural networks requires large amounts of annotated data which has to be labelled manually, by a person. LÄS MER

  7. 5. Image and RADAR fusion for autonomous vehicles

    Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Författare :Xavier de Gibert Duart; [2023]
    Nyckelord :Image; Camera; Computer Vision; Data Fusion; Sensors; 3D data processing; Point Clouds; Calibration; MATLAB and RADAR; RADAR; kamera; datorseende; datafusion; sensorer; 3D-databehandling; punktmoln; kalibrering; MATLAB Image;

    Sammanfattning : Robust detection, localization, and tracking of objects are essential for autonomous driving. Computer vision has largely driven development based on camera sensors in recent years, but 3D localization from images is still challenging. Sensors such as LiDAR or RADAR are used to compute depth; each having its own advantages and drawbacks. LÄS MER