Sökning: "Artificiell Neuralt Nätverk"

Visar resultat 1 - 5 av 36 uppsatser innehållade orden Artificiell Neuralt Nätverk.

  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

  2. 2. Image-classification for Brain Tumor using Pre-trained Convolutional Neural Network : Bildklassificering för hjärntumör medhjälp av förtränat konvolutionell tneuralt nätverk

    M1-uppsats, KTH/Hälsoinformatik och logistik

    Författare :Ahmad Osman; Bushra Alsabbagh; [2023]
    Nyckelord :Brain tumor; Deep learning; Convolutional Neural Network CNN ; diagnosis; Image classification; pre-trained models; dataset; economic impact.; Cancer; Hjärntumör; Artificiell intelligens AI ; djupinlärning; konvolutionellt neuralt nätverk CNN ; Diagnostik; Bildklassificering; förtränade modeller; dataset.;

    Sammanfattning : Brain tumor is a disease characterized by uncontrolled growth of abnormal cells inthe brain. The brain is responsible for regulating the functions of all other organs,hence, any atypical growth of cells in the brain can have severe implications for itsfunctions. The number of global mortality in 2020 led by cancerous brains was estimatedat 251,329. LÄS MER

  3. 3. Image-classification for Brain Tumor using Pre-trained Convolutional Neural Network

    Kandidat-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Författare :Bushra Alsabbagh; [2023]
    Nyckelord :Brain tumor; Deep learning; Convolutional Neural Network CNN ; diagnosis; Image classification; pre-trained models; dataset; economic impact.; Cancer; Hjärntumör; Artificiell intelligens AI ; djupinlärning; konvolutionellt neuralt nätverk CNN ; Diagnostik; Bildklassificering; förtränade modeller; dataset.;

    Sammanfattning : Brain tumor is a disease characterized by uncontrolled growth of abnormal cells in the brain. The brain is responsible for regulating the functions of all other organs, hence, any atypical growth of cells in the brain can have severe implications for its functions. LÄS MER

  4. 4. Exploring New Physics Through Collider and Gravitational Wave Measurements with Artificial Neural Networks: the Case Study of QCD-like Technicolor

    Magister-uppsats, Lunds universitet/Fysiska institutionen; Lunds universitet/Teoretisk partikelfysik - Geonomgår omorganisation

    Författare :Ashar Ahmed Kamal; [2023]
    Nyckelord :Artificial Neural Networks; ANN; Beyond the Standard Model; BSM; parameter space scan; Physics and Astronomy;

    Sammanfattning : With physicists actively exploring Beyond the Standard Model (BSM) theories that may fill in the gaps of the Standard Model (SM), a fundamental question arises: which parameters hold physical significance? In this thesis, we present our initial progress towards the development of a model-independent artificial intelligence framework designed for conducting parameter space scans in BSM scenarios. Our framework incorporates several publicly available high-energy physics packages, namely SPheno, HiggsBounds, HiggsSignals, and CosmoTransitions. LÄS MER

  5. 5. Performance comparison of data mining algorithms for imbalanced and high-dimensional data

    Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Författare :Daniel Rubio Adeva; [2023]
    Nyckelord :Data science; neural network; random forest; support vector machine; imbalanced data; average precision; ROC; Datavetenskap; neuralt nätverk; slumpmässig skog; stödvektormaskin; obalanserad data; medelprecision; ROC;

    Sammanfattning : Artificial intelligence techniques, such as artificial neural networks, random forests, or support vector machines, have been used to address a variety of problems in numerous industries. However, in many cases, models have to deal with issues such as imbalanced data or high multi-dimensionality. LÄS MER