Sökning: "image classifying CNN."

Visar resultat 1 - 5 av 29 uppsatser innehållade orden image classifying CNN..

1. 1. Object Recognition in Satellite imagesusing improved ConvolutionalRecurrent Neural Network

   Master-uppsats, Blekinge Tekniska Högskola/Institutionen för datavetenskap

   Författare :TARUN NATTALA; [2023]
   Nyckelord :CRNN; CNN; RNN; Machine Learning and Satellite Image Recognition.;

   Sammanfattning : Background:The background of this research lies in detecting the images from satellites. The recognition of images from satellites has become increasingly importantdue to the vast amount of data that can be obtained from satellites. This thesisaims to develop a method for the recognition of images from satellites using machinelearning techniques. LÄS MER

3. 2. Is eXplainable AI suitable as a hypotheses generating tool for medical research? Comparing basic pathology annotation with heat maps to find out

   Kandidat-uppsats, Uppsala universitet/Statistiska institutionen

   Författare :Albert Adlersson; [2023]
   Nyckelord :black box; eXplainable AI XAI ; Convolutional Neural Network CNN ; Mi- crosatellite Instability MSI ; colon cancer; gastric cancer; hypotheses generating; hypotheses generating tool; medical research;

   Sammanfattning : Hypothesis testing has long been a formal and standardized process. Hypothesis generation, on the other hand, remains largely informal. This thesis assess whether eXplainable AI (XAI) can aid in the standardization of hypothesis generation through its utilization as a hypothesis generating tool for medical research. LÄS MER

4. 3. Klassificering av latent diffusion genererade bilder : En metod som använder ett konvolutionellt neuralt nätverk för att klassificera latent diffusion genererade bilder

   Kandidat-uppsats, Högskolan i Skövde/Institutionen för informationsteknologi

   Författare :Sacharias Karlsson; Niklas Johansson; Mikael Freden; [2023]
   Nyckelord :Diffusion; AI; Deep learning; Image; CNN; ResNet50;

   Sammanfattning : Previous studies have used convolutional neural networks (CNN) to classify synthetic images created by generative adversarial networks (GANs) to confirm images as either being synthetic or natural. Similar to other research, this thesis will cover the classification of synthetic images witha CNN. LÄS MER

5. 4. GPS-Free UAV Geo-Localization Using a Reference 3D Database

   Master-uppsats, Linköpings universitet/Institutionen för systemteknik

   Författare :Justus Karlsson; [2022]
   Nyckelord :Deep Learning; Machine Learning; ML; AI; UAV; GPS-Free; CNN; 3D CNN; GCNN; 3D Database; geolocalization; geo-localization; georegistration; Hidden Markov Model; HMM; satellite; satellite database; Batch-Hard; triplet loss; PyTorch Geometric;

   Sammanfattning : The goal of this thesis has been global geolocalization using only visual input and a 3D database for reference. In recent years Convolutional Neural Networks (CNNs) have seen huge success in the task of classifying images. The flattened tensors at the final layers of a CNN can be viewed as vectors describing different input image features. LÄS MER

7. 5. Classifying Electricity Tower Image Data with Unsupervised Curriculum Learning

   Magister-uppsats, Luleå tekniska universitet/Institutionen för system- och rymdteknik

   Författare :Jacob Wedin; [2022]
   Nyckelord :;

   Sammanfattning : The core objective of this thesis is to classify a set of aerial photographs into two categories, those containing an electricity tower and those not containing an electricity tower. While supervised deep learning methods can reach excellent results on such tasks, they require large amounts of labeled data. LÄS MER