Essays about: "new score method"
Showing result 1 - 5 of 109 essays containing the words new score method.
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1. Uncertainty Quantification in Deep Learning for Breast Cancer Classification in Point-of-Care Ultrasound Imaging
University essay from Lunds universitet/Matematik LTHAbstract : Breast cancer is the most common type of cancer worldwide with an estimate of 2.3 million new cases in 2020, and the number one cause of cancer-related deaths in women. READ MORE
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2. Data Augmentation: Enhancing Named Entity Recognition Performance on Swedish Medical Texts
University essay from Göteborgs universitet/Institutionen för data- och informationsteknikAbstract : Named Entity Recognition (NER) refers to the task of locating relevant information within text sequences. Within the medical domain, it can benefit applications such as de-identifying patient records or extracting valuable data for other downstream tasks. READ MORE
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3. Demand Forecasting of Automobile Spare Parts after the End-of-Production - A review of demand forecasting models
University essay from Göteborgs universitet/Graduate SchoolAbstract : Demand forecasting of spare parts plays a crucial role in automobile industry where it generally requires a significant attention in controlling inventory. It is possible to maintain an optimal stock level when there is a continues supply at the Original Equipment Manufacturers (OEMs). READ MORE
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4. Performance metrics and velocity influence for point cloud registration in autonomous vehicles
University essay from KTH/Skolan för industriell teknik och management (ITM)Abstract : Autonomous vehicles are currently under study and one of the critical parts is the localization of the vehicle in the environment. Different localization methods have been studied over the years, such as the GPS sensor, commonly fused with other sensors such as the IMU. READ MORE
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5. Towards gradient faithfulness and beyond
University essay from Högskolan i Halmstad/Akademin för informationsteknologiAbstract : The riveting interplay of industrialization, informalization, and exponential technological growth of recent years has shifted the attention from classical machine learning techniques to more sophisticated deep learning approaches; yet its intrinsic black-box nature has been impeding its widespread adoption in transparency-critical operations. In this rapidly evolving landscape, where the symbiotic relationship between research and practical applications has never been more interwoven, the contribution of this paper is twofold: advancing gradient faithfulness of CAM methods and exploring new frontiers beyond it. READ MORE