Essays about: "Pipeline development"
Showing result 6 - 10 of 149 essays containing the words Pipeline development.
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6. Development and testing of in-house automatized spatial omics data analysis tool : NIPMAP (Niche-Phenotype Mapping)
University essay from Högskolan i Skövde/Institutionen för biovetenskapAbstract : The functional and anatomical characteristics of cancer cells vary among patients. Additionally, therapeutic approaches display varying responses in different individuals and cancer types due to the anatomical and functional complexity of tumor. READ MORE
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7. Development of a Complete Minuscule Microscope: Embedding Data Pipeline and Machine Learning Segmentation
University essay from KTH/Tillämpad fysikAbstract : Cell culture is a fundamental procedure in many laboratories and precedes much research performed under the microscope. Despite the significance of this procedural stage, the monitoring of cells throughout growth is impossible due to the absence of equipment and methodological approaches. READ MORE
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8. Fine-tuning a BERT-based NER Model for Positive Energy Districts
University essay from Högskolan Dalarna/Institutionen för information och teknikAbstract : This research presents an innovative approach to extracting information from Positive Energy Districts (PEDs), urban areas generating surplus energy. PEDs are integral to the European Commission's SET Plan, tackling housing challenges arising from population growth. READ MORE
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9. Context-aware Swedish Lexical Simplification : Using pre-trained language models to propose contextually fitting synonyms
University essay from Linköpings universitet/Institutionen för datavetenskapAbstract : This thesis presents the development and evaluation of context-aware Lexical Simplification (LS) systems for the Swedish language. In total three versions of LS models, LäsBERT, LäsBERT-baseline, and LäsGPT, were created and evaluated on a newly constructed Swedish LS evaluation dataset. READ MORE
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10. Big Data Visualization in Extended Reality
University essay from Lunds universitet/Institutionen för designvetenskaperAbstract : Effectively utilizing Big Data can be a challenge for many companies. Due to its volume, many aspects of the data processing pipeline such as storage, retrieval and usage may quickly become problematic. For example, it could be difficult identifying the relevant metrics when analyzing a service failure. READ MORE