Sökning: "semi-supervised machine learning"

Visar resultat 1 - 5 av 39 uppsatser innehållade orden semi-supervised machine learning.

1. 1. Classification of Radar Emitters using Semi-Supervised Contrastive Learning

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

   Författare :Tim Jonsson; [2023]
   Nyckelord :;

   Sammanfattning : Radar is a commonly used radio equipment in military and civilian settings for discovering and locating foreign objects. In a military context, pilots being discovered by radar could have fatal consequences. LÄS MER

3. 2. RNN-based Graph Neural Network for Credit Load Application leveraging Rejected Customer Cases

   Uppsats för yrkesexamina på avancerad nivå, Högskolan i Halmstad/Akademin för informationsteknologi

   Författare :Oskar Nilsson; Benjamin Lilje; [2023]
   Nyckelord :Machine Learning; Deep Learning; Reject Inference; GNN; GCN; Graph Neural Networks; RNN; Recursive Neural Network; LSTM; Semi-Supervised Learning; Encoding; Decoding; Feature Elimination;

   Sammanfattning : Machine learning plays a vital role in preventing financial losses within the banking industry, and still, a lot of state of the art and industry-standard approaches within the field neglect rejected customer information and the potential information that they hold to detect similar risk behavior.This thesis explores the possibility of including this information during training and utilizing transactional history through an LSTM to improve the detection of defaults. LÄS MER

4. 3. Anomaly detection for prediction of failures in manufacturing environments : Machine learning based semi-supervised anomaly detection for multivariate time series to predict failures in a CNC-machine

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

   Författare :Felix Boltshauser; [2023]
   Nyckelord :Machine learning; Anomaly Detection; DeepAnT; ROCKET; OCSVM; manufacturing; predictive maintenance; Maskin inlärning; Anomali Detektion; DeepAnT; ROCKET; OCSVM; tillverkning; prediktivt underhåll;

   Sammanfattning : For manufacturing enterprises, the potential of collecting large amounts of data from production processes has enabled the usage of machine learning for prediction-based monitoring and maintenance of machines. Yet common maintenance strategies still include reactive handling of machine failures or schedule-based maintenance conducted by experienced personnel. LÄS MER

5. 4. Semi-Supervised Domain Adaptation for Semantic Segmentation with Consistency Regularization : A learning framework under scarce dense labels

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

   Författare :Daniel Morales Brotons; [2023]
   Nyckelord :Domain Adaptation; Semi-Supervised Learning; Semi-Supervised Domain Adaptation; Semantic Segmentation; Consistency Regularization; Domain Adaptation; Semi-Supervised Learning; Semi-Supervised Domain Adaptation; Semantisk Segmentering; Konsistensregularisering;

   Sammanfattning : Learning from unlabeled data is a topic of critical significance in machine learning, as the large datasets required to train ever-growing models are costly and impractical to annotate. Semi-Supervised Learning (SSL) methods aim to learn from a few labels and a large unlabeled dataset. LÄS MER

7. 5. Using Semi-Supervised Learning for Email Classification

   Master-uppsats, KTH/Matematik (Avd.)

   Författare :Anders Inde; [2022]
   Nyckelord :applied mathematics; semi-supervised learning; self-training; doc2vec; classification; tillämpad matematik; semi-vägledd inlärning; self-training; doc2vec; klassificering;

   Sammanfattning : In this thesis, we investigate the use of self-training, a semi-supervised learning method, to improve binary classification of text documents. This means making use of unlabeled samples, since labeled samples can be expensive to generate. More specifically, we want to classify emails that are retrieved by Skandinaviska Enskilda Banken (SEB). LÄS MER