Essays about: "oövervakad maskininlärning"

Showing result 1 - 5 of 41 essays containing the words oövervakad maskininlärning.

1. 1. Beståndsanpassad aptering: metodutveckling och utfallsprövning : effekter av varierande längdstyrning i egenskapsskilda beståndsgrupper

   University essay from SLU/Department of Forest Biomaterials and Technology (from 131204)

   Author : William Svederberg; [2023]
   Keywords : beståndsanpassad aptering; maskininlärning; produktionsstyrning;

   Abstract : Idag är tillgången till skogliga data mycket stor. En bidragande faktor till detta är insamlingen av data vid maskinell avverkning. Denna datamängd används i stor utsträckning för bland annat produktionsuppföljning men med viss bearbetning kan de användas för att digitalt återskapa den avverkade skogen. READ MORE

3. 2. A Transformer-Based Scoring Approach for Startup Success Prediction : Utilizing Deep Learning Architectures and Multivariate Time Series Classification to Predict Successful Companies

   University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)

   Author : Gustaf Halvardsson; [2023]
   Keywords : Machine learning; Time Series Classification; Transformers; Gated Recurrent Unit; Venture Capital; Maskininlärning; tidsseriesklassifiering; Transformer; Gated Recurrent Unit; riskkapital;

   Abstract : The Transformer, an attention-based deep learning architecture, has shown promising capabilities in both Natural Language Processing and Computer Vision. Recently, it has also been applied to time series classification, which has traditionally used statistical methods or the Gated Recurrent Unit (GRU). READ MORE

4. 3. Unsupervised Domain Adaptation for Regressive Annotation : Using Domain-Adversarial Training on Eye Image Data for Pupil Detection

   University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)

   Author : Erik Zetterström; [2023]
   Keywords : Neural networks; Deep learning; Convolutional neural networks; Transfer learning; Domain adaptation; Unsupervised training; Adversarial training; Keypoint detection; Regression; Neurala nätverk; Djupinlärning; Faltningsnätverk; Överförningsinlärning; Domänadaptering; Oövervakad inlärning; Motstående träning; Nyckelpunktsdetektion; Regression;

   Abstract : Machine learning has seen a rapid progress the last couple of decades, with more and more powerful neural network models continuously being presented. These neural networks require large amounts of data to train them. READ MORE

5. 4. Unsupervised Machine Learning Based Anomaly Detection in Stockholm Road Traffic

   University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)

   Author : Vilma Hellström; [2023]
   Keywords : Anomaly detection; DBSCAN; LSTM; Machine learning; Synthetic anomalies; Unsupervised learning; Anomalidetektering; DBSCAN; LSTM; maskininlärning; syntetiska anomalier; oövervakad inlärning;

   Abstract : This thesis is a study of anomaly detection in vehicle traffic data in central Stockholm. Anomaly detection is an important tool in the analysis of traffic data for improved urban planing. Two unsupervised machine learning models are used, the DBSCAN clustering model and the LSTM deep learning neural network. READ MORE

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

   University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)

   Author : Jonatan Lindgren; [2022]
   Keywords : 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;

   Abstract : 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. READ MORE