Essays about: "Self-supervised learning"
Showing result 1 - 5 of 49 essays containing the words Self-supervised learning.
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1. 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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2. Exploring adaptation of self-supervised representation learning to histopathology images for liver cancer detection
University essay from Luleå tekniska universitet/Institutionen för system- och rymdteknikAbstract : This thesis explores adapting self-supervised representation learning to visual domains beyond natural scenes, focusing on medical imaging. The research addresses the central question: "How can self-supervised representation learning be specifically adapted for detecting liver cancer in histopathology images?" The study utilizes the PAIP 2019 dataset for liver cancer segmentation and employs a self-supervised approach based on the VICReg method. READ MORE
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3. Learning Embeddings for Fashion Images
University essay from Linköpings universitet/DatorseendeAbstract : Today the process of sorting second-hand clothes and textiles is mostly manual. In this master’s thesis, methods for automating this process as well as improving the manual sorting process have been investigated. READ MORE
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4. Understanding the Robustnessof Self Supervised Representations
University essay from Luleå tekniska universitet/Institutionen för system- och rymdteknikAbstract : This work investigates the robustness of learned representations of self-supervised learn-ing approaches, focusing on distribution shifts in computer vision. Joint embedding architecture and method-based self-supervised learning approaches have shown advancesin learning representations in a label-free manner and efficient knowledge transfer towardreducing human annotation needs. READ MORE
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5. Football Trajectory Modeling Using Masked Autoencoders : Using Masked Autoencoder for Anomaly Detection and Correction for Football Trajectories
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : Football trajectory modeling is a powerful tool for predicting and evaluating the movement of a football and its dynamics. Masked autoencoders are scalable self-supervised learners used for representation learning of partially observable data. READ MORE
