Essays about: "Network model representation"
Showing result 1 - 5 of 119 essays containing the words Network model representation.
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1. Planet-NeRF : Neural Radiance Fields for 3D Reconstruction on Satellite Imagery in Season Changing Environments
University essay from Linköpings universitet/DatorseendeAbstract : This thesis investigates the seasonal predictive capabilities of Neural Radiance Fields (NeRF) applied to satellite images. Focusing on the utilization of satellite data, the study explores how Sat-NeRF, a novel approach in computer vision, per- forms in predicting seasonal variations across different months. READ MORE
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2. Modulating Depth Map Features to Estimate 3D Human Pose via Multi-Task Variational Autoencoders
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : Human pose estimation (HPE) constitutes a fundamental problem within the domain of computer vision, finding applications in diverse fields like motion analysis and human-computer interaction. This paper introduces innovative methodologies aimed at enhancing the accuracy and robustness of 3D joint estimation. READ MORE
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3. Detection of insurance fraud using NLP and ML
University essay from Lunds universitet/Matematisk statistikAbstract : Machine-Learning can sometimes see things we as humans can not. In this thesis we evaluated three different Natural Language Procces-techniques: BERT, word2vec and linguistic analysis (UDPipe), on their performance in detecting insurance fraud based on transcribed audio from phone calls (referred to as audio data) and written text (referred to as text-form data), related to insurance claims. READ MORE
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4. On Linear Mode Connectivity up to Permutation of Hidden Neurons in Neural Network : When does Weight Averaging work?
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : Neural networks trained using gradient-based optimization methods exhibit a surprising phenomenon known as mode connectivity, where two independently trained network weights are not isolated low loss minima in the parameter space. Instead, they can be connected by simple curves along which the loss remains low. READ MORE
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5. Physiology-Guided Machine Learning for Improved Reliability of Non-Invasive Assessment of Pulmonary Hypertension
University essay from Linköpings universitet/Avdelningen för medicinsk teknikAbstract : Diagnosing pulmonary hypertension (PH) with right heart catheterization (RHC) is associated with a risk for complications and high expenses, leading to late diagnoses [1]. Transthoracic echocardiography can be used to assess non-invasive indicators for PH such as right ventricular systolic pressure (RVSP), which can be estimated by combining the peak tricuspid regurgitation velocity (TRV) with the estimated right arterial pressure (RAP). READ MORE
