Sökning: "Färgdiagram"

Visar resultat 1 - 5 av 6 uppsatser innehållade ordet Färgdiagram.

1. 1. Smart Scooter : Solving e-scooter safety problems with multi-modal, privacy-preserving sensor technology and machine learning

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

   Författare :Beatrice Lovely; [2022]
   Nyckelord :Smart Devices; Machine Learning; Sensors; Radar; Inertial Measurement Unit; Computer Vision; Smarta Saker; Maskininlärning; Sensorer; Radar; Tröghetsmåttenhet; Dator- seende;

   Sammanfattning : Micromobility ride-share scooters (e-scooters) have become a popular mode of transport in several major cities around the world, yet several safety and accessibility issues stem from how these scooters are operated, including sidewalk riding, unsafe parking and wrong-way riding. This thesis tackles these issues through a novel, privacy-preserving, end-to-end sensor system that employs lightweight machine learning models to provide real-time feedback to users to present unsafe scooter operation. LÄS MER

3. 2. Improve game performance tracking tools : Heatmap as a tool

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

   Författare :Niklas Wessman; [2022]
   Nyckelord :Software Performance Tracking; Software Performance profiling; Heatmap; Software Testing; Automatic Testing; Game Development; Game Testing; Mjukvaruprestandaspårning; Mjukvaruprestandaprofilinger; Färgdiagram; Mjukvarutestning; Automatisk testning; Spelutveckling; Speltestning;

   Sammanfattning : Software testing is a crucial development technique to capture defects and slow code. When testing 3D graphics, it is hard to create automatic tests that detect errors or slow performance. Finding performance issues in game maps is a complex task that requires much manual work. LÄS MER

4. 3. Human pose estimation in low-resolution images

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

   Författare :Hugo Nilsson; [2022]
   Nyckelord :Human Pose Estimation; Low-Resolution Images; Heatmap Decoding; Computer Vision; Deep Learning; Mänsklig Poseuppskattning; Lågupplösta Bilder; Färgdiagram Avkodning; Datorseende; Djupinlärning;

   Sammanfattning : This project explores the understudied, yet important, case of human pose estimation in low-resolution images. This is done in the use-case of images with football players of known scale in the image. Human pose estimation can mainly be done in two different ways, the bottom-up method and the top-down method. LÄS MER

5. 4. Using Layer-wise Relevance Propagation and Sensitivity Analysis Heatmaps to understand the Classification of an Image produced by a Neural Network

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

   Författare :Matilda Rosenlew; Timas Ljungdahl; [2019]
   Nyckelord :Machine learning; neural networks; layer-wise relevance propagation; sensitivity analysis; image classification;

   Sammanfattning : Neural networks are regarded as state of the art within many areas of machine learning, however due to their growing complexity and size, a question regarding their trustability and understandability has been raised. Thus, neural networks are often being considered a "black-box". LÄS MER

7. 5. Using eye tracking to study variable naming conventions and their effect on code readability

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

   Författare :Pontus Broberg; Shapour Jahanshahi; [2019]
   Nyckelord :;

   Sammanfattning : Using camel case when naming variables is largely considered to be best practise when writing code these days. But is it really the best variable naming convention when it comes to code readability and understanding? And how does different variable naming conventions affect the readability of code? This thesis researches these questions using eye tracking technology. LÄS MER