Sökning: "CNN effekten"

Visar resultat 1 - 5 av 19 uppsatser innehållade orden CNN effekten.

1. 1. A real-time Multi-modal fusion model for visible and infrared images : A light-weight and real-time CNN-based fusion model for visible and infrared images in surveillance

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

   Författare :Jin Wanqi; [2023]
   Nyckelord :Image fusion; deep learning; surveillance; CNN; real time; Bildfusion; djupinlärning; övervakning; CNN; realtid;

   Sammanfattning : Infrared images could highlight the semantic areas like pedestrians and be robust to luminance changes, while visible images provide abundant background details and good visual effects. Multi-modal image fusion for surveillance application aims to generate an informative fused images from two source images real-time, so as to facilitate surveillance observatory or object detection tasks. LÄS MER

3. 2. Classification of fishing vessel types using machine learning methods on vessel monitoring system data

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

   Författare :Peter Mastnak; [2022]
   Nyckelord :trajectory classification; illegal fishing; sustainable fisheries management; vessel monitoring system; vessel type classification; banklassificering; illegalt fiske; hållbar fiskeförvaltning; fartygsövervakningssystem; identifiering av fartygstyp;

   Sammanfattning : The oceans around the world have been heavily impacted by overfishing due to very intensive commercial fishing in recent times. A large number of fish stocks have already been fully exploited. Vessel Monitoring System has been put in place to regulate fishing vessels and enforce sustainable fisheries management. LÄS MER

4. 3. A Comparative Study on the effect of different hyperparameters on the performance of VGGNet-16 for detection of Cardiomegaly in Chest X-ray Images

   Kandidat-uppsats, KTH/Datavetenskap

   Författare :Ouday Ahmed; Oliver Lindblad; [2022]
   Nyckelord :;

   Sammanfattning : Computer aided diagnostics (CAD) systems have been widely researched and used in the medical field since it was introduced in the 1960s. The system functions as a support for radiologists in medical examinations using imaging technology such as X-rays, MRI and CT scans to diagnose diseases and treat injuries. LÄS MER

5. 4. The Effects of Fine-tuning Depth on a Pre-trained AlexNet Architecture Applied to Chest Xrays

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

   Författare :Isabel Redtzer; Amanda Krohn; [2021]
   Nyckelord :;

   Sammanfattning : There is a lack of radiologists in the world and due to the ongoing Covid- 19 pandemic, there is a greater need than usual to be able to diagnose chest x-rays. To be able to counteract this issue and to help create a tool for radiologists to aid in the diagnostic process, a Convolutional Neural Network (CNN) can be used. LÄS MER

7. 5. Ghosts of Our Past: Neutrino Direction Reconstruction Using Deep Neural Networks

   Kandidat-uppsats, Uppsala universitet/Högenergifysik

   Författare :Sigfrid Stjärnholm; [2021]
   Nyckelord :neutrino; neural network; ICECUBE; AI; convolutional neural network; CNN; askaryan emission; charged current; neutral current; CC; NC; Keras; TensoFlow; neutrino; neuralt nätverk; ICECUBE; AI; askaryan emission; Keras; TensorFlow;

   Sammanfattning : Neutrinos are the perfect cosmic messengers when it comes to investigating the most violent and mysterious astronomical and cosmological events in the Universe. The interaction probability of neutrinos is small, and the flux of high-energy neutrinos decreases quickly with increasing energy. LÄS MER