Essays about: "unsupervised classification"

Showing result 26 - 30 of 109 essays containing the words unsupervised classification.

  1. 26. BERT Language Modelling on Network Log Data for Generalized Unsupervised Intrusion Detection

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

    Author : Fynn van Westen; [2022]
    Keywords : BERT; Language-Modelling; Cyber-Security; Intrusion-Detection; NLP; Anomaly-Detection; One-Class-Classification; BERT; språkmodellering; cybersäkerhet; intrångsdetektering; NLP; anomalidetektering; en-klass-klassificering;

    Abstract : Intrusion detection is the most prominent topic of modern computer network security. The potential attack surface is growing exponentially every year. To cope with the amounts of data which accrue, automated methods for detecting undesired network activity are the only feasible solution. READ MORE

  3. 27. Presence detection by means of RF waveform classification

    University essay from Luleå tekniska universitet/Institutionen för system- och rymdteknik

    Author : Max Lengdell; [2022]
    Keywords : presence detection; machine learning; radio wave classification; unsupervised learning; supervised learning; sensor fusion; unsupervised classification;

    Abstract : This master thesis investigates the possibility to automatically label and classify radio waves for presence detection, where the objective is to obtain information about the number of people in a room based on channel estimates. Labeling data for machine learning is time consuming and tedious process. To address this two approaches are evaluated. READ MORE

  4. 28. Hybrid Variational Autoencoder for Clustering of Single-Cell RNA-seq Data : Introducing HybridVI, a Variational Autoencoder with two Latent Spaces

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

    Author : Sarah Narrowe Danielsson; [2022]
    Keywords : Bioinformatics; scRNAseq; Variational Autoencoder; Single-Cell Analysis; Bioinformatik; scRNAseq; Variational Autoencoder; individuell cellanalys;

    Abstract : Single-cell analysis means to analyze cells on an individual level. This individual analysis enhances the investigation of the heterogeneity among and the classification of individual cells. Single-cell analysis is a broad term and can include various measurements. READ MORE

  5. 29. Carta ex Machina: Testing object-based machine learning and unsupervised classification in land use change detection mapping in the semi-arid governorate of Sidi Bouzid, Tunisia

    University essay from Lunds universitet/Institutionen för naturgeografi och ekosystemvetenskap

    Author : Kristian Emil Havnsgaard Paludan; [2021]
    Keywords : Change detection; Land use mapping; LANDSAT MSS; LANDSAT TM; GEOBIA; Random Forest classification; ISODATA cluster classification; Object-based classification; Semi-arid agriculture; Irrigation mapping; Earth and Environmental Sciences;

    Abstract : Sidi Bouzid, Tunisia is an inland governorate in Tunisia that has undergone a rapid agricultural and urban development since the Tunisian independence in 1952 from being a rural and largely nomadic region into a hub of irrigated agriculture. In 2010 Mohamed Bouazizi sparked the Tunisian revolution by lighting himself on fire int he city of Sidi Bouzid, with some blaming the inequality and water scarcity created by this rapid expansion in the irrigation farming as an important cause (Bayat, 2017; Malka, 2018). READ MORE

  6. 30. Using Machine Learning for Predictive Maintenance in Modern Ground-Based Radar Systems

    University essay from KTH/Matematisk statistik

    Author : Dina Faraj; [2021]
    Keywords : Predictive Maintenance; Machine learning; Isolation forest; K-means clustering; Logistic regression; Radar systems.; Prediktivt underhåll; Maskininlärning; Isolation forest; K-means klustring; Logistisk regression; Radarsystem.;

    Abstract : Military systems are often part of critical operations where unplanned downtime should be avoided at all costs. Using modern machine learning algorithms it could be possible to predict when, where, and at what time a fault is likely to occur which enables time for ordering replacement parts and scheduling maintenance. READ MORE