Sökning: "one class classification"

Visar resultat 1 - 5 av 167 uppsatser innehållade orden one class classification.

1. 1. Utilizing energy-saving techniques to reduce energy and memory consumption when training machine learning models : Sustainable Machine Learning

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

   Författare :Khalid El Yaacoub; [2024]
   Nyckelord :Sustainable AI; Machine learning; Quantization-Aware Training; Model Distillation; Quantized Distillation; Siamese Neural Networks; Continual Learning; Experience Replay; Data Efficient AI; Energy Consumption; Energy-Savings; Sustainable ML; Computation resources; Hållbar maskin inlärning; Hållbar AI; Maskininlärning; Quantization-Aware Training; Model Distillation; Quantized Distillation; siamesiska neurala nätverk; Continual Learning; Experience Replay; Dataeffektiv AI; Energiförbrukning; Energibesparingar; Beräkningsresurser;

   Sammanfattning : Emerging machine learning (ML) techniques are showing great potential in prediction performance. However, research and development is often conducted in an environment with extensive computational resources and blinded by prediction performance. LÄS MER

3. 2. IDENTIFYING HATE SPEECH IN SOCIAL MEDIA THROUGH CONTENT AND SOCIAL CONNECTIONS ANALYSIS

   Master-uppsats, Göteborgs universitet / Institutionen för filosofi, lingvistik och vetenskapsteori

   Författare :Milan Stanišić; [2023-06-19]
   Nyckelord :hate speech; social media; natural language processing; classification;

   Sammanfattning : Hate speech is a problem which puts its targets at risk of serious harm. It spreads fast and has a real influence on the society because of the ubiquity of the internet and social media, and so various research efforts have been put to find solutions to automatic hate speech detection. LÄS MER

4. 3. Robustness Against Non-Normality : Evaluating LDA and QDA in Simulated Settings Using Multivariate Non-Normal Distributions

   Kandidat-uppsats, Uppsala universitet/Statistiska institutionen

   Författare :Gånheim Viktor; Åslund Isak; [2023]
   Nyckelord :Classification; Linear Discriminant Analysis; Quadratic Discriminant Analysis; Normality Assumption;

   Sammanfattning : Evaluating classifiers in controlled settings is essential for empirical applications, as extensive knowledge on model-behaviour is needed for accurate predictions. This thesis investigates robustness against non-normality of two prominent classifiers, LDA and QDA. LÄS MER

5. 4. Multidimensional Classification of Radar Signals : A comparison between unidimensional and multidimensional classification models for pulsed radar signals

   Master-uppsats, Umeå universitet/Institutionen för datavetenskap

   Författare :Max Ek Törmä; [2023]
   Nyckelord :pulsed radar classification; Bayesian Gaussian mixture models; Dirichlet process mixture models; multidimensional radar classification; pulsed radar signals; radar signal classification;

   Sammanfattning : Radar is a technique used by many different types of remote sensing systems to keep track of their surroundings. The transmitted radar signals may carry information that could be used to infer the type of transmitter. Multiple papers have investigated the classification of pulse repetition intervals produced by radar systems. LÄS MER

7. 5. Anomaly Detection with Machine Learning using CLIP in a Video Surveillance Context

   Master-uppsats, Linköpings universitet/Datorseende

   Författare :Christoffer Gärdin; [2023]
   Nyckelord :Datorseende; maskininlärning; CLIP; anomalidetektion; videoövervakning;

   Sammanfattning : This thesis explores the application of Contrastive Language-Image Pre-Training (CLIP), a vision-language model, in an automated video surveillance system for anomaly detection. The ability of CLIP to perform zero-shot learning, coupled with its robustness against minor image alterations due to its lack of reliance on pixel-level image analysis, makes it a suitable candidate for this application. LÄS MER