Essays about: "Fine Tuning"
Showing result 1 - 5 of 211 essays containing the words Fine Tuning.
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1. ML implementation for analyzing and estimating product prices
University essay from Karlstads universitet/Institutionen för matematik och datavetenskap (from 2013)Abstract : Efficient price management is crucial for companies with many different products to keep track of, leading to the common practice of price logging. Today, these prices are often adjusted manually, but setting prices manually can be labor-intensive and prone to human error. 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. Design Investigation of Passive Radiators in Loudspeakers
University essay from Lunds universitet/InnovationAbstract : Passive radiators are components that can be integrated into loudspeakers to amplify the bass frequencies. To ensure good sound quality, the passive radiator, the speaker driver, and the loudspeaker enclosure must all be well-dimensioned and fine-tuned in relation to each other. READ MORE
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4. Key Sentence Extraction From CRISPR-Cas9 Articles Using Sentence Transformers
University essay from Göteborgs universitet/Institutionen för data- och informationsteknikAbstract : The annotation of CRISPR-related articles and extraction of key content has traditionally relied on manual efforts. Manual annotation is error-prone and timeconsuming. This thesis presents an alternative approach using transfer learning and pre-trained models based on the Transformer architecture. READ MORE
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5. The Impact of Deep Neural Network Pruning on the Hyperparameter Performance Space: An Empirical Study
University essay from Göteborgs universitet/Institutionen för data- och informationsteknikAbstract : With the continued growth of deep learning models in terms of size and computational requirements, the need for efficient models for deployment on resource-constrained devices becomes crucial. Structured pruning has emerged as a proven method to speed up models and reduce computational requirements. READ MORE