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Visar resultat 1 - 5 av 226 uppsatser som matchar ovanstående sökkriterier.

1. 1. ML implementation for analyzing and estimating product prices

   Kandidat-uppsats, Karlstads universitet/Institutionen för matematik och datavetenskap (from 2013)

   Författare :Abel Getachew Kenea; Gabriel Fagerslett; [2024]
   Nyckelord :Machine Learning; ML; Regression; Deep Learning; Artificial Neural Network; ANN; TensorFlow; ScikitLearn; CUDA; cuDNN; Estimation; Prediction; AI; Artificial Intelligence; Price Tracking; Price Logging; Price Estimation; Supervised Learning; Random Forest; Decision Trees; Batch Learning; Hyperparameter Tuning; Linear Regression; Multiple Linear Regression; Maskininlärning; Djup lärning; Artificiellt Neuralt Nätverk; Regression; TensorFlow; SciktLearn; ML; ANN; Estimation; Uppskattning; CUDA; cuDNN; AI; Artificiell Intelligens; pris loggning; pris estimation; prisspårning; Batchinlärning; Hyperparameterjustering; Linjär Regression; Multipel Linjär Regression; Supervised Learning; Random Forest; Decision Trees;

   Sammanfattning : 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. LÄS MER

3. 2. En undersökning av metoder förautomatiserad text ochparameterextraktion frånPDF-dokument med NaturalLanguage Processing

   M1-uppsats, KTH/Hälsoinformatik och logistik

   Författare :Alexander Värling; Emil Hultgren; [2024]
   Nyckelord :portable document format; faktura; digitalisering; IT-lösningar; optisk teckenigenkänning; textextraktion; naturlig språkbehandling; generative pre-trained transformer; portable document format; faktura; digitalisering; IT-lösningar; optisk teckenigenkänning; textextraktion; naturlig språkbehandling; generative pre-trained transformer;

   Sammanfattning : I dagens affärsmiljö strävar många organisationer efter att automatisera processen för att hämta information från fakturor. Målet är att göra hanteringen av stora mängder fakturor mer effektiv. Trots detta möter man utmaningar på grund av den varierande strukturen hos fakturor. LÄS MER

4. 3. AI-based image generation: The impact of fine-tuning on fake image detection

   Kandidat-uppsats, Stockholms universitet/Institutionen för data- och systemvetenskap

   Författare :Nick Hagström; Anders Rydberg; [2024]
   Nyckelord :Fake image detection; LoRA; DreamBooth; Stable Diffusion; Image generation;

   Sammanfattning : 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. LÄS MER

5. 4. Design Investigation of Passive Radiators in Loudspeakers

   Master-uppsats, Lunds universitet/Innovation

   Författare :Fabrice Dufberg; Valter Hamberger; [2024]
   Nyckelord :passive radiator; loudspeaker; speaker tuning; Thiele Small parameters; frequency response; Technology and Engineering;

   Sammanfattning : 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. LÄS MER

7. 5. Key Sentence Extraction From CRISPR-Cas9 Articles Using Sentence Transformers

   Master-uppsats, Göteborgs universitet/Institutionen för data- och informationsteknik

   Författare :Sandra Henningsson; Brage Stranden Lae; [2023-11-09]
   Nyckelord :NLP; Transformers; CRISPR; semantic search; keyphrase extraction;

   Sammanfattning : 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. LÄS MER