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Relevant bibliographies by topics / Convolutional neuralt nätverk

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Academic literature on the topic 'Convolutional neuralt nätverk'

Author: Grafiati

Published: 30 June 2021

Last updated: 29 July 2025

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Dissertations / Theses on the topic "Convolutional neuralt nätverk"

1

Lavenius, Axel. "Automatic identification of northern pike (Exos Lucius) with convolutional neural networks." Thesis, Uppsala universitet, Institutionen för geovetenskaper, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-418639.

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The population of northern pike in the Baltic sea has seen a drasticdecrease in numbers in the last couple of decades. The reasons for this are believed to be many, but the majority of them are most likely anthropogenic. Today, many measures are being taken to prevent further decline of pike populations, ranging from nutrient runoff control to habitat restoration. This inevitably gives rise to the problem addressed in this project, namely: how can we best monitor pike populations so that it is possible to accurately assess and verify the effects of these measures over the coming decades? Pike

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Du, Zekun. "Algorithm Design and Optimization of Convolutional Neural Networks Implemented on FPGAs." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-254575.

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Deep learning develops rapidly in recent years. It has been applied to many fields, which are the main areas of artificial intelligence. The combination of deep learning and embedded systems is a good direction in the technical field. This project is going to design a deep learning neural network algorithm that can be implemented on hardware, for example, FPGA. This project based on current researches about deep learning neural network and hardware features. The system uses PyTorch and CUDA as assistant methods. This project focuses on image classification based on a convolutional neural netwo

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Elander, Filip. "Semantic segmentation of off-road scenery on embedded hardware using transfer learning." Thesis, KTH, Mekatronik, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-301154.

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Real-time semantic scene understanding is a challenging computer vision task for autonomous vehicles. A limited amount of research has been done regarding forestry and off-road scene understanding, as the industry focuses on urban and on-road applications. Studies have shown that Deep Convolutional Neural Network architectures, using parameters trained on large datasets, can be re-trained and customized with smaller off-road datasets, using a method called transfer learning and yield state-of-the-art classification performance. This master’s thesis served as an extension of such existing off-r

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Spång, Anton. "Automatic Image Annotation by Sharing Labels Based on Image Clustering." Thesis, KTH, Skolan för datavetenskap och kommunikation (CSC), 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-210164.

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The growth of image collection sizes during the development has currently made manual annotation unfeasible, leading to the need for accurate and time efficient image annotation methods. This project evaluates a system for Automatic Image Annotation to see if it is possible to share annotations between images based on un-supervised clustering. The evaluation of the system included performing experiments with different algorithms and different unlabeled data sets. The system is also compared to an award winning Convolutional Neural Network model, used as a baseline, to see if the system’s preci

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Engström, Messén Matilda, and Elvira Moser. "Pre-planning of Individualized Ankle Implants Based on Computed Tomography - Automated Segmentation and Optimization of Acquisition Parameters." Thesis, KTH, Fysik, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-297674.

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The structure of the ankle joint complex creates an ideal balance between mobility and stability, which enables gait. If a lesion emerges in the ankle joint complex, the anatomical structure is altered, which may disturb mobility and stability and cause intense pain. A lesion in the articular cartilage on the talus bone, or a lesion in the subchondral bone of the talar dome, is referred to as an Osteochondral Lesion of the Talus (OLT). Replacing the damaged cartilage or bone with an implant is one of the methods that can be applied to treat OLTs. Episurf Medical develops and produces patient-s

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Stjärnholm, Sigfrid. "Ghosts of Our Past: Neutrino Direction Reconstruction Using Deep Neural Networks." Thesis, Uppsala universitet, Högenergifysik, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-448765.

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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. In order to find high-energy neutrinos, large bodies of matter needs to be instrumented. A proposed detector station design called ARIANNA is designed to detect neutrino interactions in the Antarctic ice by measuring radio waves that are created due to the Askaryan effect. In this paper, we present a method

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7

Reiche, Myrgård Martin. "Acceleration of deep convolutional neural networks on multiprocessor system-on-chip." Thesis, Uppsala universitet, Avdelningen för datorteknik, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-385904.

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In this master thesis some of the most promising existing frameworks and implementations of deep convolutional neural networks on multiprocessor system-on-chips (MPSoCs) are researched and evaluated. The thesis’ starting point was a previousthesis which evaluated possible deep learning models and frameworks for object detection on infra-red images conducted in the spring of 2018. In order to fit an existing deep convolutional neural network (DCNN) on a Multiple-Processor-System on Chip it needs modifications. Most DCNNs are trained on Graphic processing units (GPUs) with a bit width of 32 bit.

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Jangblad, Markus. "Object Detection in Infrared Images using Deep Convolutional Neural Networks." Thesis, Uppsala universitet, Avdelningen för systemteknik, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-355221.

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In the master thesis about object detection(OD) using deep convolutional neural network(DCNN), the area of OD is being tested when being applied to infrared images(IR). In this thesis the, goal is to use both long wave infrared(LWIR) images and short wave infrared(SWIR) images taken from an airplane in order to train a DCNN to detect runways, Precision Approach Path Indicator(PAPI) lights, and approaching lights. The purpose for detecting these objects in IR images is because IR light transmits better than visible light under certain weather conditions, for example, fog. This system could then

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Airola, Rasmus, and Kristoffer Hager. "Image Classification, Deep Learning and Convolutional Neural Networks : A Comparative Study of Machine Learning Frameworks." Thesis, Karlstads universitet, Institutionen för matematik och datavetenskap, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:kau:diva-55129.

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The use of machine learning and specifically neural networks is a growing trend in software development, and has grown immensely in the last couple of years in the light of an increasing need to handle big data and large information flows. Machine learning has a broad area of application, such as human-computer interaction, predicting stock prices, real-time translation, and self driving vehicles. Large companies such as Microsoft and Google have already implemented machine learning in some of their commercial products such as their search engines, and their intelligent personal assistants Cor

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Gustavsson, Robin, and Johan Jakobsson. "Lung-segmentering : Förbehandling av medicinsk data vid predicering med konvolutionella neurala nätverk." Thesis, Högskolan i Borås, Akademin för bibliotek, information, pedagogik och IT, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:hb:diva-14380.

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Svenska socialstyrelsen presenterade år 2017 att lungcancer är den vanligaste cancerrelaterade dödsorsaken bland kvinnor i Sverige och den näst vanligaste bland män. Ett sätt att ta reda på om en patient har lungcancer är att en läkare studerar en tredimensionell-röntgenbild av en patients lungor. För att förebygga misstag som kan orsakas av den mänskliga faktorn är det möjligt att använda datorer och avancerade algoritmer för att upptäcka lungcancer. En nätverksmodell kan tränas att upptäcka detaljer och avvikelser i en lungröntgenbild, denna teknik kallas deep structural learning. Det är båd

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