Sökning: "artificiellt neuralt nätverk"

Visar resultat 1 - 5 av 50 uppsatser innehållade orden artificiellt 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

  3. 2. Modelling Long Term Memory in the Bayesian Confidence Neural Network Model

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

    Författare :Charu Karn; Samir Samahunov; [2023]
    Nyckelord :;

    Sammanfattning : Memory is a fascinating and complex part of human life. Understanding memory and simulating itthrough modelling can help society take steps towards understanding health issues such asAlzheimer's, dementia and amnesia. LÄS MER

  4. 3. The data-driven CyberSpine : Modeling the Epidural Electrical Stimulation using Finite Element Model and Artificial Neural Networks

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

    Författare :Yu Qin; [2023]
    Nyckelord :Spinal Cord Injury; Epidural Electrical Stimulation; Computational Neuroscience; Finite Element Model; Artificial Intelligence; Optimal Transport; EMG; Muscle Activation; Ryggmärgsskada; Epidural Elektrisk Stimulering; Beräkningsneurovetenskap; Finita Elementmodellen; Artificiell Intelligens; Optimal Transport; EMG; Muskelaktivering;

    Sammanfattning : Every year, 250,000 people worldwide suffer a spinal cord injury (SCI) that leaves them with chronic paraplegia - permanent loss of ability to move their legs. SCI interrupts axons passing along the spinal cord, thereby isolating motor neurons from brain inputs. To date, there are no effective treatments that can reconnect these interrupted axons. LÄS MER

  5. 4. Deep neural networks for food waste analysis and classification : Subtraction-based methods for the case of data scarcity

    Uppsats för yrkesexamina på avancerad nivå, Uppsala universitet/Signaler och system

    Författare :David Brunell; [2022]
    Nyckelord :Siamese network; convolutional neural network;

    Sammanfattning : Machine learning generally requires large amounts of data, however data is often limited. On the whole the amount of data needed grows with the complexity of the problem to be solved. Utilising transfer learning, data augmentation and problem reduction, acceptable performance can be achieved with limited data for a multitude of tasks. LÄS MER

  7. 5. Data-Driven Motion Planning : With Application for Heavy Duty Vehicles

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

    Författare :Oscar Palfelt; [2022]
    Nyckelord :Motion planning; Deep learning; Autonomous driving; Nonuniform sampling; Rörelseplanering; Djupinlärning; Autonom körning; Ojämn provtagning;

    Sammanfattning : Motion planning consists of finding a feasible path of an object between an initial state and a goal state, and commonly constitutes a sub-system of a larger autonomous system. Motion planners that utilize sampling-based algorithms create an implicit representation of the search space via sampling said search space. LÄS MER