Essays about: "Synthetic data set"
Showing result 11 - 15 of 91 essays containing the words Synthetic data set.
-
11. Parameter Estimation and Simulation of Driving Datasets
University essay from KTH/Väg- och spårfordon samt konceptuell fordonsdesignAbstract : The development of autonomous driving in recent years has been in full swing and one of the aspects that Autonomous Vehicles (AVs) should always focus on is safety. Although the corresponding technology has gradually matured, and AVs have performed well in a large number of tests, people are still uncertain whether AVs can cope with all possible situations. READ MORE
-
12. NOVA: Automated Detection of Violent Threats in Swedish Online Environments
University essay from Stockholms universitet/Institutionen för data- och systemvetenskapAbstract : Social media and online environments have become an integral part of society, allowing for self-expression, information sharing, and discussions online. However, these platforms are also used to express hate and threats of violence. READ MORE
-
13. Segmentation of x-ray images using deep learning trained on synthetic data
University essay from KTH/FysikAbstract : Radiograph examinations play a critical role in various applications such as the detection of bone pathologies and lung cancer, despite the challenge of false negatives. The integration of Artificial Intelligence (AI) holds promise in enhancing image quality and assisting radiologists in their diagnostic processes. READ MORE
-
14. Generation of Synthetic White Blood Cell Images Using Denoising Diffusion
University essay from Lunds universitet/Matematik LTHAbstract : CellaVision’s digital hematology systems are designed to analyze blood and pre-classify different types of blood cells. Some abnormal white blood cells are rare, which can cause imbalanced datasets. This can lead to a decrease in pre- classification performance and a need to carry out more time-consuming data gathering. READ MORE
-
15. Messing With The Gap: On The Modality Gap Phenomenon In Multimodal Contrastive Representation Learning
University essay from Uppsala universitet/Industriell teknikAbstract : In machine learning, a sub-field of computer science, a two-tower architecture model is a specialised type of neural network model that encodes paired data from different modalities (like text and images, sound and video, or proteomics and gene expression profiles) into a shared latent representation space. However, when training these models using a specific contrastive loss function, known as the multimodalinfoNCE loss, seems to often lead to a unique geometric phenomenon known as the modality gap. READ MORE