Sökning: "Djupinlärningsmodeller"
Visar resultat 1 - 5 av 53 uppsatser innehållade ordet Djupinlärningsmodeller.
1. Dynamik och tillförlighet i finansiell prognostisering : En analys av djupinlärningsmodeller och deras reaktion på marknadsmanipulation
M1-uppsats, KTH/Hälsoinformatik och logistikSammanfattning : Under åren har intensiv forskning pågått för att förbättra maskininlärningsmodellers förmåga att förutse marknadsrörelser. Trots detta har det, under finanshistorien, inträffat flera händelser, såsom "Flash-crash", som har påverkat marknaden och haft dramatiska konsekvenser för prisrörelserna. LÄS MER
2. Deep Learning Model Deployment for Spaceborne Reconfigurable Hardware : A flexible acceleration approach
Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)Sammanfattning : Space debris and space situational awareness (SSA) have become growing concerns for national security and the sustainability of space operations, where timely detection and tracking of space objects is critical in preventing collision events. Traditional computer-vision algorithms have been used extensively to solve detection and tracking problems in flight, but recently deep learning approaches have seen widespread adoption in non-space related applications for their high accuracy. LÄS MER
3. Mitigating Unintended Bias in Toxic Comment Detection using Entropy-based Attention Regularization
Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)Sammanfattning : The proliferation of hate speech is a growing challenge for social media platforms, as toxic online comments can have dangerous consequences also in real life. There is a need for tools that can automatically and reliably detect hateful comments, and deep learning models have proven effective in solving this issue. LÄS MER
4. Dataset characteristics effect on time series forecasting : comparison of statistical and deep learning models
Kandidat-uppsats, Högskolan i Halmstad/Akademin för informationsteknologiSammanfattning : Time series are points of data measured throughout time in equally spaced periods. They present characteristics such as level, noise, trend, seasonality, and outliers. Time series forecasting is the attempt to predict single or multiple future values. LÄS MER
5. Deep Learning-Driven EEG Classification in Human-Robot Collaboration
Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)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