Sökning: "few-shot"

Visar resultat 21 - 25 av 29 uppsatser innehållade ordet few-shot.

1. 21. Lost in Transcription : Evaluating Clustering and Few-Shot learningfor transcription of historical ciphers

   Master-uppsats, Uppsala universitet/Institutionen för lingvistik och filologi

   Författare :Giacomo Magnifico; [2021]
   Nyckelord :Image Recognition; Handwritten Text Recognition; HTR; Deep-learning; K-mean clustering; NN; Neural Network; Few-Shot;

   Sammanfattning : Where there has been a steady development of Optical Character Recognition (OCR) techniques for printed documents, the instruments that provide good quality for hand-written manuscripts by Hand-written Text Recognition  methods (HTR) and transcriptions are still some steps behind. With the main focus on historical ciphers (i.e. LÄS MER

3. 22. Multilingual Zero-Shot and Few-Shot Causality Detection

   Master-uppsats, Uppsala universitet/Institutionen för lingvistik och filologi

   Författare :Sebastian Michael Reimann; [2021]
   Nyckelord :classification; causality; causal relation; multilingual; cross-lingual; zero-shot; few-shot; bert; xlm-r; laser;

   Sammanfattning : Relations that hold between causes and their effects are fundamental for a wide range of different sectors. Automatically finding sentences that express such relations may for example be of great interest for the economy or political institutions. LÄS MER

4. 23. Learning from Synthetic Data : Towards Effective Domain Adaptation Techniques for Semantic Segmentation of Urban Scenes

   Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

   Författare :Gerard Valls I Ferrer; [2021]
   Nyckelord :Semantic Segmentation; Synthetic Data; Autonomous Driving; Domain Shift; Domain Adaptation; Domain Generalisation; Semantisk Segmentering; Syntetiska Data; Autonom Körning; Domänskift; Domänanpassning; Domängeneralisering;

   Sammanfattning : Semantic segmentation is the task of predicting predefined class labels for each pixel in a given image. It is essential in autonomous driving, but also challenging because training accurate models requires large and diverse datasets, which are difficult to collect due to the high cost of annotating images at pixel-level. LÄS MER

5. 24. Zero/Few-Shot Text Classification : A Study of Practical Aspects and Applications

   Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

   Författare :Jacob Åslund; [2021]
   Nyckelord :zero-shot learning; few-shot learning; text classification; active learning; automated data labeling; interpretable machine learning; deep learning; NLP; NLU; zero-shot learning; few-shot learning; textklassificering; aktiv inlärning; automatiserad datamärkning; tolkningsbar maskininlärning; djupinlärning; NLP; NLU;

   Sammanfattning : SOTA language models have demonstrated remarkable capabilities in tackling NLP tasks they have not been explicitly trained on – given a few demonstrations of the task (few-shot learning), or even none at all (zero-shot learning). The purpose of this Master’s thesis has been to investigate practical aspects and potential applications of zero/few-shot learning in the context of text classification. LÄS MER

7. 25. The Influence of M-BERT and Sizes on the Choice of Transfer Languages in Parsing

   Master-uppsats, Uppsala universitet/Institutionen för lingvistik och filologi

   Författare :Yifei Zhang; [2021]
   Nyckelord :;

   Sammanfattning : In this thesis, we explore the impact of M-BERT and different transfer sizes on the choice of different transfer languages in dependency parsing. In order to investigate our research questions, we conduct a series of experiments on the treebanks in Universal Dependencies with UUParser. LÄS MER