Sökning: "deep space network"

Visar resultat 6 - 10 av 87 uppsatser innehållade orden deep space network.

1. 6. Identification of Fibers in Micro-CT Images of Paperboard Using Deep Learning

   Uppsats för yrkesexamina på avancerad nivå, Lunds universitet/Hållfasthetslära; Lunds universitet/Institutionen för byggvetenskaper

   Författare :David Rydgård; [2023]
   Nyckelord :Fiber networks; Paperboard mechanics; Deep learning; Tomography; Image analysis; Technology and Engineering;

   Sammanfattning : This master thesis project explores the possibility of using deep learning to segment individual fibers in three-dimensional tomography images of paperboard fiber networks. We test a method which has previously been used to segment fibers in images of glass fiber reinforced polymers. LÄS MER

3. 7. Robust Multi-Modal Fusion for 3D Object Detection : Using multiple sensors of different types to robustly detect, classify, and position objects in three dimensions.

   Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

   Författare :Viktor Kårefjärd; [2023]
   Nyckelord :Computer Vision; 3D Object Detection; Multi-Modal Fusion; Deep Learning; Datorseenden; 3D-objektdetektion; Multimodal fusion; Djupinlärning;

   Sammanfattning : The computer vision task of 3D object detection is fundamentally necessary for autonomous driving perception systems. These vehicles typically feature a multitude of sensors, such as cameras, radars, and light detection and ranging sensors. LÄS MER

4. 8. Deep Neural Networks for Object Detection in Satellite Imagery

   Uppsats för yrkesexamina på avancerad nivå, Uppsala universitet/Avdelningen Vi3

   Författare :Frederik Fritsch; [2023]
   Nyckelord :Object Detection; Satellite Imagery; Deep Neural Networks; YOLOv8; xView;

   Sammanfattning : With the development of small satellites it has become easier and cheaper to deploy satellites for earth observation from space. While optical sensors capture high-resolution data, this data is traditionally sent to earth for analysis which puts a high constraint on the data link and increases the time for making data based decisions. LÄS MER

5. 9. Deep convolution neural network for attention decoding in multi-channel EEG with conditional variational autoencoder for data augmentation

   Uppsats för yrkesexamina på avancerad nivå, Lunds universitet/Institutionen för reglerteknik

   Författare :M Asjid Tanveer; [2023]
   Nyckelord :Technology and Engineering;

   Sammanfattning : Objectives: This project aims to develop a deep learning-based attention decoding system that can distinguish between noise and speech in noise and also identify the direction of attended speech from the brain data recorded with electroencephalography (EEG) instruments. Two deep convolutional neural network (DCNN) models will be designed: (1) one DCNN model capable of classifying incoming segments of sound as speech or speech in background noise, and (2) one DCNN model identifying the direction (left vs. LÄS MER

7. 10. RNN-based Graph Neural Network for Credit Load Application leveraging Rejected Customer Cases

   Uppsats för yrkesexamina på avancerad nivå, Högskolan i Halmstad/Akademin för informationsteknologi

   Författare :Oskar Nilsson; Benjamin Lilje; [2023]
   Nyckelord :Machine Learning; Deep Learning; Reject Inference; GNN; GCN; Graph Neural Networks; RNN; Recursive Neural Network; LSTM; Semi-Supervised Learning; Encoding; Decoding; Feature Elimination;

   Sammanfattning : Machine learning plays a vital role in preventing financial losses within the banking industry, and still, a lot of state of the art and industry-standard approaches within the field neglect rejected customer information and the potential information that they hold to detect similar risk behavior.This thesis explores the possibility of including this information during training and utilizing transactional history through an LSTM to improve the detection of defaults. LÄS MER