Sökning: "vad är djupinlärning"

Visar resultat 1 - 5 av 31 uppsatser innehållade orden vad är djupinlärning.

1. 1. Analysis of speaking time and content of the various debates of the presidential campaign : Automated AI analysis of speech time and content of presidential debates based on the audio using speaker detection and topic detection

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

   Författare :Axel Valentin Maza; [2023]
   Nyckelord :Artificial Intelligence; Speaker detection; Speaker recognition; Speaker diarization; Speaker identification; Debate; Politics; Deep Learning; Artificiell intelligens; talardetektion; talarigenkänning; talardiarisering; talaridentifiering; debatt; politik; djupinlärning;

   Sammanfattning : The field of artificial intelligence (AI) has grown rapidly in recent years and its applications are becoming more widespread in various fields, including politics. In particular, presidential debates have become a crucial aspect of election campaigns and it is important to analyze the information exchanged in these debates in an objective way to let voters choose without being influenced by biased data. LÄS MER

3. 2. Deep Learning-Driven EEG Classification in Human-Robot Collaboration

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

   Författare :Yuan Wo; [2023]
   Nyckelord :Human-robot collaboration; Electroencephalogram signal; Signal Processing Feature Extraction; Deep Learning method; Dilated Convolutional Neural Network; Människa-robot-samarbete; Elektroencefalogram-signal; Signalförädlingsfunktionsutvinning; Djupinlärningsmetod; Dilaterat konvolutionellt neuronnätverk.;

   Sammanfattning : Human-robot collaboration (HRC) occurs when people and robots work together in a shared environment. Current robots often use rigid programs unsuitable for HRC. Multimodal robot programming offers an easier way to control robots using inputs like voice and gestures. LÄS MER

4. 3. The Effect Background Traffic in VPNs has on Website Fingerprinting

   Master-uppsats, Karlstads universitet/Institutionen för matematik och datavetenskap (from 2013)

   Författare :Gustav Rehnholm; [2023]
   Nyckelord :Website Fingerprinting; Virtual Private Network; Deep Learning; Mönsterigenkänning; Virtuellt Privat Nätverk; Djup Inlärning;

   Sammanfattning : Tor and VPNs are used by many to be anonymous and circumvent censorship on the Internet. Therefore, traffic analysis attacks that enable adversaries to link users to their online activities are a severe threat. LÄS MER

5. 4. Exploring toxic lexicon similarity methods with the DRG framework on the toxic style transfer task

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

   Författare :Martin Iglesias; [2023]
   Nyckelord :Detoxifcation; Text style transfer; Deep learning; Transformers; Linguistics; Natural Language Processing; Hate speech; Text style-conditional generation; Large language model; Avgiftning; Överföring av textstil; Djupinlärning; Transformatorer; Lingvistik; Naturlig språkbehandling; Hatprat; Textstil - villkorlig generering; Stor språkmodell;

   Sammanfattning : The topic of this thesis is the detoxification of language in social networks with a particular focus on style transfer techniques that combine deep learning and linguistic resources. In today’s digital landscape, social networks are rife with communication that can often be toxic, either intentionally or unintentionally. LÄS MER

7. 5. Artificial Neural Networks and Inductive Biases for Multi-Instance Multi-Modal Tabular Data : A Case Study for Default Probability Estimation in Small-to-Medium Enterprise Lending

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

   Författare :Gustav Röhss; [2022]
   Nyckelord :;

   Sammanfattning : The success of artificial neural networks in homogeneous data domains such as images, textual data, and audio and other signals has had considerable impact on Machine Learning and science in general. The domain of heterogeneous tabular data, while arguably much more common, remains much less explored with regards to artificial neural networks and deep learning. LÄS MER