Sökning: "fashion algorithms"
Visar resultat 6 - 10 av 42 uppsatser innehållade orden fashion algorithms.
6. A Digital Design Flow - From Concept to RTL Description, Using Mathworks and Cadence's Tools
Master-uppsats, Lunds universitet/Institutionen för elektro- och informationsteknikSammanfattning : This report presents our digital design flow for creating high speed very large scale integration circuits using a fifth generation disruptive beamforming control and data processing circuit as example. The flow consists of different stages. LÄS MER
7. Quantum Portfolio Optimization : a Multi-Level Perspective Study of the Swedish Fund Management Industry
Master-uppsats, KTH/Industriell ekonomi och organisation (Inst.)Sammanfattning : In recent years, quantum computers have achieved new levels of sophistication and are by some estimates only a few years from being used in production. A growing body of literature points toward their potential uses within various industries, with the finance industry identified as exceptionally full of prospective applications. LÄS MER
8. Analysing User Viewing Behaviour in Video Streaming Services
Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)Sammanfattning : The user experience offered by a video streaming service plays a fundamental role in customer satisfaction. This experience can be degraded by poor playback quality and buffering issues. These problems can be caused by a user demand that is higher than the video streaming service capacity. LÄS MER
9. Efficient graph embeddings with community detection
Master-uppsats, Umeå universitet/Institutionen för fysikSammanfattning : Networks are useful when modeling interactions in real-world systems based on relational data. Since networks often contain thousands or millions of nodes and links, analyzing and exploring them requires powerful visualizations. LÄS MER
10. Analysing different optimization algorithms for training of neural networks
Kandidat-uppsats, KTH/Skolan för teknikvetenskap (SCI)Sammanfattning : This thesis analyses four different optimization algorithms for training a convolutional neural network (CNN) using three different datasets. The algorithms studied were stochastic gradient descent (SGD), Polyak momentum, Nesterov momentum and Adaptive Moment Estimation (ADAM). LÄS MER