Sökning: "Automated Feature Extraction"

Visar resultat 11 - 15 av 32 uppsatser innehållade orden Automated Feature Extraction.

1. 11. Deep morphological quantification and clustering of brain cancer cells using phase-contrast imaging

   Uppsats för yrkesexamina på avancerad nivå, Uppsala universitet/Avdelningen för visuell information och interaktion

   Författare :Jonas Engberg; [2021]
   Nyckelord :Glioblastoma; UMAP; Heterogeneity; Clustering; Convolutional neural network; Siamese neural network;

   Sammanfattning : Glioblastoma Multiforme (GBM) is a very aggressive brain tumour. Previous studies have suggested that the morphological distribution of single GBM cells may hold information about the severity. This study aims to find if there is a potential for automated morphological qualification and clustering of GBM cells and what it shows. LÄS MER

3. 12. Exploration of an Automated Motivation Letter Scoring System to Emulate Human Judgement

   Master-uppsats, Högskolan Dalarna/Mikrodataanalys

   Författare :Lorenna Munnecom; Miguel Chaves de Lemos Pacheco; [2020]
   Nyckelord :Natural Language Processing; Machine Learning; Supervised Learning; Unsupervised Learning; Automation; Feature Extraction; Image Processing; Text Processing; Text Exploration; Motivation Letter; Dalarna University; Student Application; Topic Modelling; Business Intelligence; Data Science;

   Sammanfattning : As the popularity of the master’s in data science at Dalarna University increases, so does the number of applicants. The aim of this thesis was to explore different approaches to provide an automated motivation letter scoring system which could emulate the human judgement and automate the process of candidate selection. LÄS MER

4. 13. Automated Bug Classification. : Bug Report Routing

   Master-uppsats, Linköpings universitet/Institutionen för datavetenskap; Linköpings universitet/Filosofiska fakulteten

   Författare :Sridhar Adhikarla; [2020]
   Nyckelord :;

   Sammanfattning : With the growing software technologies companies tend to develop automated solutions to save time and money. Automated solutions have seen tremendous growth in the software industry and have benefited from extensive machine learning research. LÄS MER

5. 14. Improved Data Association for Multi-Pedestrian Tracking Using Image Information

   Master-uppsats, Linköpings universitet/Datorseende

   Författare :Frida Flodin; [2020]
   Nyckelord :Multi-pedestrian tracking; Feature extraction;

   Sammanfattning : Multi-pedestrian tracking (MPT) is the task of localizing and following the trajectory of pedestrians in a sequence. Using an MPT algorithm is an important part in preventing pedestrian-vehicle collisions in Automated Driving (AD) and Advanced Driving Assistance Systems (ADAS). LÄS MER

7. 15. Multitask Convolutional Neural Network Emulators for Global Crop Models - Supervised Deep Learning in Large Hypercubes of Non-IID Data

   Master-uppsats, Lunds universitet/Matematisk statistik

   Författare :Amanda Nilsson; [2020]
   Nyckelord :Multitask Learning; Convolutional Neural Network CNN ; Branched Neural Network; Dynamic Global Vegetation Models DGVM ; Automated Feature Extraction; Feature Importance; Supervised Machine Learning; Emulator; Surrogate Model; Response Surface Model; Approximation Model; Metamodeling; Model Composition; Regularization; Robustness; Hyperparameter Optimization; Mathematics and Statistics;

   Sammanfattning : The aim of this thesis is to establish whether a neural network (NN) can be used for emulation of simulated global crop production - retrieved from the computationally demanding dynamic global vegetation model (DGVM) Lund-Potsdam-Jena General Ecosystem Simulator (LPJ-GUESS). It has been devoted to elaboration with various types of neural network architectures: Branched NNs capable of processing inputs of mixed data types; Convolutional Neural Network (CNN) architectures able to perform automated temporal feature extraction of the given weather time series; simpler fully connected (FC) structures as well as Multitask NNs. LÄS MER