Sökning: "Djupinlärningsmetod"

Visar resultat 1 - 5 av 12 uppsatser innehållade ordet Djupinlärningsmetod.

1. 1. Unsupervised Clustering of Behavior Data From a Parking Application : A Heuristic and Deep Learning Approach

   Uppsats för yrkesexamina på avancerad nivå, Umeå universitet/Institutionen för matematik och matematisk statistik

   Författare :Edvard Magnell; Joakim Nordling; [2023]
   Nyckelord :ML; Machine learning; clustering; unsupervised learning; deep learning; autoencoder; AI; artificial intelligence;

   Sammanfattning : This report aims to present a project in the field of unsupervised clustering on human behavior in a parking application. With increasing opportunities to collect and store data, the demands to utilize the data in meaningful ways also increase. 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. A Deep Learning approach to Analysing Multimodal User Feedback during Adaptive Robot-Human Presentations : A comparative study of state-of-the-art Deep Learning architectures against high performing Machine Learning approaches

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

   Författare :Manuel Fraile Rodríguez; [2023]
   Nyckelord :Human Feedback; Deep Learning; Convolutional Neural Networks; Transformers; Mänsklig återmatning; mänsklig feedback; djupinlärning; CNN; transformer;

   Sammanfattning : When two human beings engage in a conversation, feedback is generally present since it helps in modulating and guiding the conversation for the involved parties. When a robotic agent engages in a conversation with a human, the robot is not capable of understanding the feedback given by the human as other humans would. LÄS MER

5. 4. Deep Learning Approach for Time- to-Event Modeling of Credit Risk

   Master-uppsats, KTH/Matematisk statistik

   Författare :Mehnaz Kazi; Natalija Stanojlovic; [2022]
   Nyckelord :Survival Analysis; Credit Risk; Credit Scoring; Time-To-Event; Default Probability; Överlevnadsanalys; Kreditrisk; Kreditprövning; Tid-till-utfall; Sannolikhet för fallissemang;

   Sammanfattning : This thesis explores how survival analysis models performs for default risk prediction of small-to-medium sized enterprises (SME) and investigates when survival analysis models are preferable to use. This is examined by comparing the performance of three deep learning models in a survival analysis setting, a traditional survival analysis model Cox Proportional Hazards, and a traditional credit risk model logistic regression. LÄS MER

7. 5. Pose Classification of Horse Behavior in Video : A deep learning approach for classifying equine poses based on 2D keypoints

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

   Författare :Michaela Söderström; [2021]
   Nyckelord :Deep Learning; Computer Visison; Horse behavior; Pose estimation; 2D key- points; Pose classification; DeepLabCut; Djupinlärning; Datorseende; Hästbeteende; Pose-estimering; Nyckelpunkter; Intressepunkter; Pose-klassificering; DeepLabCut;

   Sammanfattning : This thesis investigates whether Computer Vision can be a useful tool in interpreting the behaviors of monitored horses. In recent years, research in the field of Computer Vision has primarily focused on people, where pose estimation and action recognition are popular research areas. LÄS MER