Essays about: "feature extractor"
Showing result 1 - 5 of 27 essays containing the words feature extractor.
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1. A Comparison of Convolutional Neural Networks used in Melanoma Detection : With transfer learning on the PAD-UFES-20 and ISIC datasets
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : Skin cancer is one of the most common forms of cancer, of which melanoma is the most lethal. Early detection is critical to long term survival rates. The use of machine learning to detect melanoma shows promising results in detecting malignant forms. READ MORE
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2. Multi-modal Models for Product Similarity : Comparative evaluation of unimodal and multi-modal architectures for product similarity prediction and product retrieval
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : With the rapid growth of e-commerce, enabling effective product recommendation systems and improving product search for shoppers plays a crucial role in driving customer satisfaction. Traditional product retrieval approaches have mainly relied on unimodal models focusing on text data. READ MORE
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3. Human pose estimation in low-resolution images
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : This project explores the understudied, yet important, case of human pose estimation in low-resolution images. This is done in the use-case of images with football players of known scale in the image. Human pose estimation can mainly be done in two different ways, the bottom-up method and the top-down method. READ MORE
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4. Speaker verification: Advantages and limitations of a biologically inspired feature extractor
University essay from Lunds universitet/Institutionen för elektro- och informationsteknikAbstract : Speaker verification is the process of verifying the identity of a person based on voice. This process usually encompasses the following steps: The speech signal is mapped into features using a feature extractor, these features are then classified using a post processor. READ MORE
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5. Narrow Pretraining of Deep Neural Networks : Exploring Autoencoder Pretraining for Anomaly Detection on Limited Datasets in Non-Natural Image Domains
University essay from Linköpings universitet/Medie- och Informationsteknik; Linköpings universitet/Tekniska fakultetenAbstract : Anomaly detection is the process of detecting samples in a dataset that are atypical or abnormal. Anomaly detection can for example be of great use in an industrial setting, where faults in the manufactured products need to be detected at an early stage. READ MORE