Sökning: "HDBSCAN"

Visar resultat 1 - 5 av 17 uppsatser innehållade ordet HDBSCAN.

1. 1. Unsupervised Clustering of Behavior Data From a Parking Application : A Heuristic and Deep Learning Approach

   Uppsats för yrkesexamina på avancerad nivå, Umeå universitet/Institutionen för matematik och matematisk statistik

   Författare :Edvard Magnell; Joakim Nordling; [2023]
   Nyckelord :ML; Machine learning; clustering; unsupervised learning; deep learning; autoencoder; AI; artificial intelligence;

   Sammanfattning : This report aims to present a project in the field of unsupervised clustering on human behavior in a parking application. With increasing opportunities to collect and store data, the demands to utilize the data in meaningful ways also increase. LÄS MER

3. 2. Clustering on groups for human tracking with 3D LiDAR

   Master-uppsats, Umeå universitet/Institutionen för datavetenskap

   Författare :Simon Utterström; [2023]
   Nyckelord :Computer Vision; Computer Science; AI; Machine Learning; clustering; Kernel Density Clustering; tracking; LiDAR; 3D LiDAR; tracking; human; pedestrian; real time; Datavetenskap; Dataseende; clustering; SLR; CVC; KDEG; KDE; Kernel Density Clustering; HDBSCAN; DBSCAN; LiDAR; point cloud; tracking; human; pedestrian;

   Sammanfattning : 3D LiDAR people detection and tracking applications rely on extracting individual people from the point cloud for reliable tracking. A recurring problem for these applications is under-segmentation caused by people standing close or interacting with each other, which in turn causes the system to lose tracking. LÄS MER

4. 3. Advancing Keyword Clustering Techniques: A Comparative Exploration of Supervised and Unsupervised Methods : Investigating the Effectiveness and Performance of Supervised and Unsupervised Methods with Sentence Embeddings

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

   Författare :Filippo Caliò; [2023]
   Nyckelord :Keyword Clustering; Supervised Learning; Unsupervised Learning; Cluster Labels; Natural Language Processing; Sentence Embeddings; Nyckelord Klustring; övervakad inlärning; oövervakad inlärning; klustermärkning; naturlig språkbehandling; Inbäddning av meningar;

   Sammanfattning : Clustering keywords is an important Natural Language Processing task that can be adopted by several businesses since it helps to organize and group related keywords together. By clustering keywords, businesses can better understand the topics their customers are interested in. LÄS MER

5. 4. Automatic Interpretation of Ion Beam Measurements of Walls in Fusion Machines

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

   Författare :Daniel Lundberg; Ludvig Johansson; [2023]
   Nyckelord :;

   Sammanfattning : The purpose of this study is to investigate whether it is possible to automatically interpret theresults of Time-of-flight Elastic Recoil Detection Analysis (ToF-ERDA). And if so, find out if the automaticinterpretation is quicker and/or more accurate than the current approach that consists of manualanalysis. LÄS MER

7. 5. Intelligence Extraction Using Machine Learning for Threat Identification Purposes : An Overview

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

   Författare :Jonatan Lindgren; [2022]
   Nyckelord :Machine learning; Radar threat identification; Clustering; Performance metrics for unsupervised learning; Feature scaling; Electronic warfare; Maskininlärning; Identifikation av radarhot; Klustring; Prestandamått för oövervakad inlärning; Skalning av dataparametrar; Elektronisk krigsföring;

   Sammanfattning : Radar is an invaluable tool for detecting and assessing threats on land, on the seas and in the air. To properly evaluate threats, radar operators construct threat libraries where the signal characteristics of emitters are stored and mapped to specific types of platforms. LÄS MER