Sökning: "Oövervakat lärande"
Visar resultat 1 - 5 av 16 uppsatser innehållade orden Oövervakat lärande.
1. Discover patterns within train log data using unsupervised learning and network analysisMaster-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)
Sammanfattning : With the development of information technology in recent years, log analysis has gradually become a hot research topic. However, manual log analysis requires specialized knowledge and is a time-consuming task. Therefore, more and more researchers are searching for ways to automate log analysis. LÄS MER
2. Matching Sticky Notes Using Latent RepresentationsMaster-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)
Sammanfattning : his project addresses the issue of accurately identifying repeated images of sticky notes. Due to environmental conditions and the 3D location of the camera, different pictures taken of sticky notes may look distinct enough to be hard to determine if they belong to the same note. LÄS MER
3. Grouping Similar Bug Reports from Crash Dumps with Unsupervised LearningMaster-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)
Sammanfattning : Quality software usually means high reliability, which in turn has two main components; the software should provide correctness, which means it should perform the specified task, and robustness in the sense that it should be able to manage unexpected situations. In other words, reliable systems are systems without bugs. LÄS MER
4. EVALUATION OF UNSUPERVISED MACHINE LEARNING MODELS FOR ANOMALY DETECTION IN TIME SERIES SENSOR DATAKandidat-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)
Sammanfattning : With the advancement of the internet of things and the digitization of societies sensor recording time series data can be found in an always increasing number of places including among other proximity sensors on cars, temperature sensors in manufacturing plants and motion sensors inside smart homes. This always increasing reliability of society on these devices lead to a need for detecting unusual behaviour which could be caused by malfunctioning of the sensor or by the detection of an uncommon event. LÄS MER
5. Depth Estimation from Images using Dense Camera-Lidar Correspondences and Deep LearningMaster-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)
Sammanfattning : Depth estimation from 2D images is a fundamental problem in Computer Vision, and is increasingly becoming an important topic for Autonomous Driving. A lot of research is driven by innovations in Convolutional Neural Networks, which efficiently encode low as well as high level image features and are able to fuse them to find accurate pixel correspondences and learn the scale of the objects. LÄS MER