Essays about: "One shot learning"
Showing result 1 - 5 of 37 essays containing the words One shot learning.
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1. Bridging Language & Data : Optimizing Text-to-SQL Generation in Large Language Models
University essay from Linköpings universitet/Artificiell intelligens och integrerade datorsystemAbstract : This thesis explores text-to-SQL generation using Large Language Models within a financial context, aiming to assess the efficacy of current benchmarks and techniques. The central investigation revolves around the accuracy of the BIRD-Bench benchmark and the applicability of text-to-SQL models in real-world scenarios. READ MORE
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2. Design and Evaluation of Peptide Binders : In silico evaluation and comparison of generative AI for de novo peptide binder design
University essay from Uppsala universitet/Beräkningsbiologi och bioinformatikAbstract : Peptide binders are short proteins that bind to larger proteins. Due to peptide binders having high specificity and being cheap to synthesize, they are a prime candidate for drug design. Creating new proteins in silico can be divided into three steps: protein backbone generation, sequence design, and computational filtering. READ MORE
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3. Anomaly Detection with Machine Learning using CLIP in a Video Surveillance Context
University essay from Linköpings universitet/DatorseendeAbstract : This thesis explores the application of Contrastive Language-Image Pre-Training (CLIP), a vision-language model, in an automated video surveillance system for anomaly detection. The ability of CLIP to perform zero-shot learning, coupled with its robustness against minor image alterations due to its lack of reliance on pixel-level image analysis, makes it a suitable candidate for this application. READ MORE
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4. Generation of Synthetic Traffic Sign Images using Diffusion Models
University essay from Linköpings universitet/DatorseendeAbstract : In the area of Traffic Sign Recognition (TSR), deep learning models are trained to detect and classify images of traffic signs. The amount of data available to train these models is often limited, and collecting more data is time-consuming and expensive. READ MORE
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5. Privacy Preserving Biometric Multi-factor Authentication
University essay from Lunds universitet/Institutionen för elektro- och informationsteknikAbstract : This thesis investigates the viability of using Fully Homomorphic Encryption and Machine Learning to construct a privacy-preserving biometric multi-factor authentication system. The system is based on the architecture described as ”Model K - Store distributed, compare distributed” in ISO/IEC 24745:2022 and uses the Torus Fully Homomorphic Encryption scheme proposed by Chillotti et al. READ MORE
