Essays about: "down-sampling"
Showing result 1 - 5 of 10 essays containing the word down-sampling.
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1. Enhancing Neural Network Accuracy on Long-Tailed Datasets through Curriculum Learning and Data Sorting
University essay from KTH/Matematik (Avd.)Abstract : In this paper, a study is conducted to investigate the use of Curriculum Learning as an approach to address accuracy issues in a neural network caused by training on a Long-Tailed dataset. The thesis problem is presented by a Swedish e-commerce company. READ MORE
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2. Enhancement-basedSmall TargetDetection for InfraredImages
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : Infrared small target detection is widely used in fields such as military and security. UNet, which is a classical semantic segmentation method proposed in 2015, has shown excellent performance and robustness. However, U-Net suffers from the problem of losing small targets in deep layers after multiple down-sampling operations. READ MORE
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3. Dealing With Speckle Noise in Deep Neural Network Segmentation of Medical Ultrasound Images
University essay from KTH/Skolan för kemi, bioteknologi och hälsa (CBH)Abstract : Segmentation of ultrasonic images is a common task in healthcare that requires time and attention from healthcare professionals. Automation of medical image segmentation using deep learning solutions is fast growing field and has been shown to be capable of near human performance. READ MORE
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4. GVT-BDNet : Convolutional Neural Network with Global Voxel Transformer Operators for Building Damage Assessment
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : Natural disasters strike anywhere, disrupting local communication and transportation infrastructure, making the process of assessing specific local damage difficult, dangerous, and slow. The goal of Building Damage Assessment (BDA) is to quickly and accurately estimate the location, cause, and severity of the damage to maximize the efficiency of rescuers and saved lives. READ MORE
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5. Data Augmentation in Solving Data Imbalance Problems
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : This project mainly focuses on the various methods of solving data imbalance problems in the Natural Language Processing (NLP) field. Unbalanced text data is a common problem in many tasks especially the classification task, which leads to the model not being able to predict the minority class well. READ MORE