Sökning: "Multimodal Classification"

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

1. 1. Classifying femur fractures using federated learning

   Master-uppsats, Linköpings universitet/Statistik och maskininlärning

   Författare :Hong Zhang; [2024]
   Nyckelord :Atypical femur fracture; Federated Learning; Neural Network; Classification;

   Sammanfattning : The rarity and subtle radiographic features of atypical femoral fractures (AFF) make it difficult to distinguish radiologically from normal femoral fractures (NFF). Compared with NFF, AFF has subtle radiological features and is associated with the long-term use of bisphosphonates for the treatment of osteoporosis. LÄS MER

3. 2. Automated Interpretation of Lung Ultrasound for COVID-19 and Tuberculosis diagnosis

   Master-uppsats, Lunds universitet/Matematik LTH

   Författare :Chloé Soormally; [2023]
   Nyckelord :Tuberculosis; COVID-19; Lung Ultrasound; Computer-aided detection CAD ; Deep learning; Technology and Engineering;

   Sammanfattning : BACKGROUND. Early and accurate detection of infectious respiratory diseases like COVID-19 and tuberculosis (TB) plays a crucial role in effective management and the reduction of preventable mortality. LÄS MER

4. 3. 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

5. 4. 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

7. 5. 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