Sökning: "Multimodal Machine Learning"

Visar resultat 1 - 5 av 25 uppsatser innehållade orden Multimodal Machine Learning.

1. 1. 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

3. 2. Building Information Modeling Connection Recommendation Based on Machine Learning Using Multimodal Information

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

   Författare :Zixin Zhou; [2023]
   Nyckelord :Building information modeling; Tekla Structures; Connection; Classification; Machine learning; Multimodal data fusion;

   Sammanfattning : Den ökande komplexiteten i byggprojekt ger upphov till behovet av ett effektivt sätt att designa, hantera och underhålla strukturer. Byggnadsinformationsmodellering (BIM) underlättar dessa processer genom att tillhandahålla en digital representation av fysiska strukturer. LÄS MER

4. 3. A Transformer-Based Scoring Approach for Startup Success Prediction : Utilizing Deep Learning Architectures and Multivariate Time Series Classification to Predict Successful Companies

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

   Författare :Gustaf Halvardsson; [2023]
   Nyckelord :Machine learning; Time Series Classification; Transformers; Gated Recurrent Unit; Venture Capital; Maskininlärning; tidsseriesklassifiering; Transformer; Gated Recurrent Unit; riskkapital;

   Sammanfattning : The Transformer, an attention-based deep learning architecture, has shown promising capabilities in both Natural Language Processing and Computer Vision. Recently, it has also been applied to time series classification, which has traditionally used statistical methods or the Gated Recurrent Unit (GRU). LÄS MER

5. 4. 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

7. 5. Predicting Chronic Kidney Disease using a multimodal Machine Learning approach

   Magister-uppsats, Stockholms universitet/Institutionen för data- och systemvetenskap

   Författare :Aakruti Mishra; Navaneeth Puthiyandi; [2023]
   Nyckelord :Chronic kidney disease; Multimodal approach; ROCKET; Random Forest; XGBoost; MIMIC-III database; Data imbalance; Temporal and static modalities; Soft voting;

   Sammanfattning : Chronic Kidney Disease (CKD) is a common and dangerous health condition that requires early detection and treatment to be effective. Current diagnostic methods are time-consuming and expensive. In this research, we hope to construct a predictive model for CKD utilizing a combination of time series and static variables for early detection of CKD. LÄS MER