Essays about: "generative training"
Showing result 1 - 5 of 129 essays containing the words generative training.
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1. Transforming Chess: Investigating Decoder-Only Architecture for Generating Realistic Game-Like Positions
University essay from Umeå universitet/Institutionen för datavetenskapAbstract : Chess is a deep and intricate game, the master of which depends on learning tens of thousands of the patterns that may occur on the board. At Noctie, their mission is to aid this learning process through humanlike chess AI. A prominent challenge lies in curating instructive chess positions for students. READ MORE
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2. AI-based image generation: The impact of fine-tuning on fake image detection
University essay from Stockholms universitet/Institutionen för data- och systemvetenskapAbstract : Machine learning-based image generation models such as Stable Diffusion are now capable of generating synthetic images that are difficult to distinguish from real images, which gives rise to a number of legal and ethical concerns. As a potential measure of mitigation, it is possible to train neural networks to detect the digital artifacts present in the images synthesized by many generative models. READ MORE
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3. Virtual H&E Staining Using PLS Microscopy and Neural Networks
University essay from Lunds universitet/Matematik LTHAbstract : Histopathological examination, crucial in diagnosing diseases such as cancer, traditionally relies on time- and resource-consuming, poorly standardized chemical staining for tissue visualization. This thesis presents a novel digital alternative using generative neural networks and a point light source (PLS) microscope to transform unstained skin tissue images into their stained counterparts. READ MORE
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4. Despeckling Echocardiograms Using Generative Adversarial Networks
University essay from Göteborgs universitet/Institutionen för data- och informationsteknikAbstract : Previous research had shown that generative adversarial networks (GANs) are capable of despeckling echocardiograms (echos) through image-to-image translation in real-time once trained. However, only limited information regarding the quality of denoised echos and explainability of useful GAN components is provided. READ MORE
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5. Approximating Reasoning with Transformer Language Models
University essay from Göteborgs universitet/Institutionen för data- och informationsteknikAbstract : We conduct experiments with BART, a generative language-model architecture, to investigate its capabilities for approximating reasoning by learning from data. For this we use the SimpleLogic dataset, a dataset of satisfiability problems in propositional logic originally created by Zhang et al. (2022). READ MORE
