Sökning: "fashion algorithms"
Visar resultat 21 - 25 av 42 uppsatser innehållade orden fashion algorithms.
21. Using Machine Learning to Detect Customer Acquisition Opportunities and Evaluating the Required Organizational Prerequisites
Kandidat-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)Sammanfattning : This paper aims to investigate whether or not it is possible to identify users who are about change provider of service with machine learning. It is believed that the Consumer Decision Journey is a better model than traditional funnel models when it comes to depicting the processes which consumers go through, leading up to a purchase. LÄS MER
22. Pushing the Limits of Gossip-Based Decentralised Machine Learning
Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)Sammanfattning : Recent years have seen a sharp increase in the ubiquity and power of connected devices, such as smartphones, smart appliances and smart sensors. These de- vices produce large amounts of data that can be extremely precious for training larger, more advanced machine learning models. LÄS MER
23. Text-to-image Synthesis for Fashion Design
Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)Sammanfattning : Generating high-quality images from textual descriptions is an active research direction in image generation and has aroused great interest in fashion design. The synthesized image should be consistent with the meaning of text as well as being of acceptable quality. LÄS MER
24. Interactive Robot Art : A turn-based system for painting together with a robot
Kandidat-uppsats, Högskolan i Halmstad/Akademin för informationsteknologiSammanfattning : A large amount of people suffer from mental illnesses such as depression and autism. Receiving the care they need can be a very difficult process, with long queues and expensive bills. Automating part of the therapeutic process might be a solution to this. More patients could be treated at the same time, and the cost could be decreased. LÄS MER
25. Towards unification of organ labeling in radiation therapy using a machine learning approach based on 3D geometries
Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)Sammanfattning : In radiation therapy, it is important to control the radiation dose absorbed by Organs at Risk (OARs). The OARs are represented as 3D volumes delineated by medical experts, typically using computed tomography images of the patient. LÄS MER