IMPROVING SELF-SUPERVISED REPRESENTATION LEARNING IN MOCO V2 WITH QUEUE OPTIMIZATION

This research is motivated by the need to improve the performance of selfsupervised learning models, particularly the Momentum Contrastive version 2 (MoCo v2) architecture. This study aims to develop a more robust and accurate MoCo v2 model by adding a K-Nearest Neighbors (KNN) mechanism to the q...

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Bibliographic Details
Main Author: Jofandi, Gugun
Format: Theses
Language:Indonesia
Online Access:https://digilib.itb.ac.id/gdl/view/87791
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Institution: Institut Teknologi Bandung
Language: Indonesia

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