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  1. 1. Estimation of Height, Weight, Sex and Age from Magnetic Resonance Images using 3D Convolutional Neural Networks

    University essay from Linköpings universitet/Institutionen för medicinsk teknik

    Author : Carl Nimhed; [2022]
    Keywords : mr; magnetic resonance; machine learning; deep learning;

    Abstract : Magnetic resonance imagining is a non-invasive 3D imaging technology widely used in the medical field for partial and full body scans. AMRA Medical AB is a medical company which combines MRI images with additional patient attributes such as height, weight, sex and age to perform analysis such as body composition profiling. READ MORE

  2. 2. AATrackT: A deep learning network using attentions for tracking fast-moving and tiny objects : (A)ttention (A)ugmented - (Track)ing on (T)iny objects

    University essay from Jönköping University/JTH, Avdelningen för datavetenskap

    Author : Fredric Lundberg Andersson; [2022]
    Keywords : Machine learning; Computer vision; Visual tracking; Attentions; Tiny fast-moving object;

    Abstract : Recent advances in deep learning have made it possible to visually track objects from a video sequence. Moreover, as transformers got introduced in computer vision, new state-of-the-art performances were achieved in visual tracking. READ MORE

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

    University essay from Linköpings universitet/Institutionen för systemteknik

    Author : Justus Karlsson; [2022]
    Keywords : 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;

    Abstract : 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. READ MORE

  4. 4. Comparing Weak and Strong Annotation Strategies for Multiple Instance Learning in Digital Pathology

    University essay from KTH/Skolan för kemi, bioteknologi och hälsa (CBH)

    Author : Alice Ciallella; [2022]
    Keywords : Multiple-Instance Learning MIL ; prostate cancer; bag creation; digital pathology; binary classification; multiclass classification;

    Abstract : Prostate cancer is the second most diagnosed cancer worldwide and its diagnosis is done through visual inspection of biopsy tissue by a pathologist, who assigns a score used by doctors to decide on the treatment. However, the scoring system, the Gleason score, is affected by a high inter and intra-observer variability, lack of standardization, and overestimation. READ MORE

  5. 5. Prediction of the number of weekly covid-19 infections : A comparison of machine learning methods

    University essay from Högskolan i Skövde/Institutionen för informationsteknologi

    Author : Nicklas Branding; [2022]
    Keywords : Machine learning; deep learning; covid-19; public health science; number of infection; regression; long short term memory; gated recurrent unit; support vector regressor; long short term memory-convolutional neural network; bidirectional-long short term memory;

    Abstract : The thesis two-folded problem aim was to identify and evaluate candidate Machine Learning (ML) methods and performance methods, for predicting the weekly number of covid-19 infections. The two-folded problem aim was created from studying public health studies where several challenges were identified. READ MORE