Essays about: "Semi- Supervised Learning"
Showing result 11 - 15 of 85 essays containing the words Semi- Supervised Learning.
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11. Semi-Supervised Plant Leaf Detection and Stress Recognition
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : One of the main limitations of training deep learning-based object detection models is the availability of large amounts of data annotations. When annotations are scarce, semi-supervised learning provides frameworks to improve object detection performance by utilising unlabelled data. READ MORE
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12. Using Semi-Supervised Learning for Email Classification
University essay from KTH/Matematik (Avd.)Abstract : In this thesis, we investigate the use of self-training, a semi-supervised learning method, to improve binary classification of text documents. This means making use of unlabeled samples, since labeled samples can be expensive to generate. More specifically, we want to classify emails that are retrieved by Skandinaviska Enskilda Banken (SEB). READ MORE
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13. Semi-supervised Sentiment Analysis for Sentence Classification
University essay from Uppsala universitet/Institutionen för lingvistik och filologiAbstract : In our work, we deploy semi-supervised learning methods to perform Sentiment Analysis on a corpus of sentences, meant to be labeled as either happy, neutral, sad, or angry. Sentence-BERT is used to obtain high-dimensional embeddings for the sentences in the training and testing sets, on which three classification methods are applied: the K-Nearest Neighbors classifier (KNN), Label Propagation, and Label Spreading. READ MORE
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14. An Industrial Application of Semi-supervised techniques for automatic surface inspection of stainless steel. : Are pseudo-labeling and consistency regularization effective in a real industrial context?
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : Recent developments in the field of Semi-Supervised Learning are working to avoid the bottleneck of data labeling. This can be achieved by leveraging unlabeled data to limit the amount of labeled data needed for training deep learning models. READ MORE
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15. Defect classification in LPBF images using semi-supervised learning
University essay from Karlstads universitet/Institutionen för matematik och datavetenskap (from 2013); Karlstads universitet/Avdelningen för datavetenskapAbstract : Laser powder bed fusion is an additive manufacturing technique that is capable of building metallic parts by spreading many layers of metal powder over a build surface and using a laser to melt specific sections of the surface. The part is built by melting consecutive layers on top of each other until the design is completed. READ MORE