Essays about: "annotering"
Showing result 1 - 5 of 33 essays containing the word annotering.
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1. Analyzing the performance of active learning strategies on machine learning problems
University essay from Uppsala universitet/Avdelningen för systemteknikAbstract : Digitalisation within industries is rapidly advancing and data possibilities are growing daily. Machine learning models need a large amount of data that are well-annotated for good performance. To get well-annotated data, an expert is needed, which is expensive, and the annotation itself could be very time-consuming. READ MORE
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2. Active learning for text classification in cyber security
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : In the domain of cyber security, machine learning promises advanced threat detection. However, the volume of available unlabeled data poses challenges for efficient data management. This study investigates the potential for active learning, a subset of interactive machine learning, to reduce the effort required for manual data labelling. READ MORE
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3. Self-learning for 3D segmentation of medical images from single and few-slice annotation
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : Training deep-learning networks to segment a particular region of interest (ROI) in 3D medical acquisitions (also called volumes) usually requires annotating a lot of data upstream because of the predominant fully supervised nature of the existing stateof-the-art models. To alleviate this annotation burden for medical experts and the associated cost, leveraging self-learning models, whose strength lies in their ability to be trained with unlabeled data, is a natural and straightforward approach. READ MORE
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4. A novel nomenclature for the identification of ground truth in medical imaging data : Design, implementation and integration in a large knowledge database
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : The annotation of medical images is a critical task for many downstream applications. However, the lack of a unified annotation nomenclature has resulted in inconsistency and ambiguity in the storage and use of such data. In this thesis, we propose and evaluate a novel annotation nomenclature for medical images. READ MORE
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5. An End-to-End Native Language Identification Model without the Need for Manual Annotation
University essay from Uppsala universitet/Institutionen för lingvistik och filologiAbstract : Native language identification (NLI) is a classification task which identifies the mother tongue of a language learner based on spoken or written material. The task gained popularity when it was featured in the 2017 BEA-12-workshop and since then many applications have been successfully found for NLI - ranging from language learning to authorship identification and forensic science. READ MORE
