Essays about: "Supervised Deep Learning"
Showing result 1 - 5 of 164 essays containing the words Supervised Deep Learning.
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1. ML implementation for analyzing and estimating product prices
University essay from Karlstads universitet/Institutionen för matematik och datavetenskap (from 2013)Abstract : Efficient price management is crucial for companies with many different products to keep track of, leading to the common practice of price logging. Today, these prices are often adjusted manually, but setting prices manually can be labor-intensive and prone to human error. READ MORE
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2. Learning a Grasp Prediction Model for Forestry Applications
University essay from Umeå universitet/Institutionen för fysikAbstract : Since the advent of machine learning and machine vision methods, progress has been made in tackling the long-standing research question of autonomous grasping of arbitrary objects using robotic end-effectors. Building on these efforts, we focus on a subset of the general grasping problem concerning the automation of a forwarder. READ MORE
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3. Self-Supervised Learning for Tabular Data: Analysing VIME and introducing Mix Encoder
University essay from Lunds universitet/Fysiska institutionenAbstract : We introduce Mix Encoder, a novel self-supervised learning framework for deep tabular data models based on Mixup [1]. Mix Encoder uses linear interpolations of samples with associated pretext tasks to form useful pre-trained representations. READ MORE
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4. Virtual H&E Staining Using PLS Microscopy and Neural Networks
University essay from Lunds universitet/Matematik LTHAbstract : Histopathological examination, crucial in diagnosing diseases such as cancer, traditionally relies on time- and resource-consuming, poorly standardized chemical staining for tissue visualization. This thesis presents a novel digital alternative using generative neural networks and a point light source (PLS) microscope to transform unstained skin tissue images into their stained counterparts. READ MORE
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5. Domain Adaptation for Multi-Contrast Image Segmentation in Cardiac Magnetic Resonance Imaging
University essay from KTH/Skolan för kemi, bioteknologi och hälsa (CBH)Abstract : Accurate segmentation of the ventricles and myocardium on Cardiac Magnetic Resonance (CMR) images is crucial to assess the functioning of the heart or to diagnose patients suffering from myocardial infarction. However, the domain shift existing between the multiple sequences of CMR data prevents a deep learning model trained on a specific contrast to be used on a different sequence. READ MORE