Sökning: "new neural network"

Visar resultat 1 - 5 av 425 uppsatser innehållade orden new neural network.

  1. 1. Predictive Modeling of Pipetting Dynamics. Multivariate Regression Analysis: PLS and ANN for Estimating Density and Volume from Pressure Recordings

    Master-uppsats, Lunds universitet/Avdelningen för Biomedicinsk teknik

    Författare :Lisa Linard Pedersen; [2024]
    Nyckelord :Technology and Engineering;

    Sammanfattning : Thermo Fisher Scientific manufacture automatic pipetting instruments for diagnostic tests. These tests are sensitive to abnormalities and changes in e.g. volume or density could potentially lead to less precision or other issues in the pipetting work flow. LÄS MER

  2. 2. Station-level demand prediction in bike-sharing systems through machine learning and deep learning methods

    Master-uppsats, Lunds universitet/Institutionen för naturgeografi och ekosystemvetenskap

    Författare :Nikolaos Staikos; [2024]
    Nyckelord :Physical Geography; Ecosystem Analysis; Bike-sharing demand; Machine learning; Deep learning; Spatial regression; Graph Convolutional Neural Network; Multiple Linear Regression; Multilayer Perceptron Regressor; Support Vector Machine; Random Forest Regressor; Urban environment; Micro-mobility; Station planning; Geomatics; Earth and Environmental Sciences;

    Sammanfattning : Public Bike-Sharing systems have been employed in many cities around the globe. Shared bikes are an efficient and convenient means of transportation in advanced societies. Nonetheless, station planning and local bike-sharing network effectiveness can be challenging. LÄS MER

  3. 3. Exploring the Depth-Performance Trade-Off : Applying Torch Pruning to YOLOv8 Models for Semantic Segmentation Tasks

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

    Författare :Xinchen Wang; [2024]
    Nyckelord :Deep Learning; Semantic segmentation; Network optimization; Network pruning; Torch Pruning; YOLOv8; Network Depth; Djup lärning; Semantisk segmentering; Nätverksoptimering; Nätverksbeskärning; Fackelbeskärning; YOLOv8; Nätverksdjup;

    Sammanfattning : In order to comprehend the environments from different aspects, a large variety of computer vision methods are developed to detect objects, classify objects or even segment them semantically. Semantic segmentation is growing in significance due to its broad applications in fields such as robotics, environmental understanding for virtual or augmented reality, and autonomous driving. LÄS MER

  4. 4. Decoding the surface code using graph neural networks

    Master-uppsats, Göteborgs universitet / Institutionen för fysik

    Författare :Moritz Lange; [2023-10-17]
    Nyckelord :;

    Sammanfattning : Quantum error correction is essential to achieve fault-tolerant quantum computation in the presence of noisy qubits. Among the most promising approaches to quantum error correction is the surface code, thanks to a scalable two-dimensional architecture, only nearest-neighbor interactions, and a high error threshold. Decoding the surface code, i.e. LÄS MER

  5. 5. Reconstruction of Radio Detector Data using Graph Neural Networks

    Master-uppsats, Uppsala universitet/Högenergifysik

    Författare :Arnau Serra Garet; [2023]
    Nyckelord :;

    Sammanfattning : The current neutrino detectors have been able to detect neutrinos in the range of TeV to 100 PeV, however, ultra high energy (UHE) neutrinos above 100 PeV still remain to be detected. A new neutrino detector, the RNO-G, is currently being constructed in Greenland with the purpose of detecting the first UHE neutrinos using radio antennas capable of measuring the Askaryan pulse generated after a neutrino interaction with the ice molecules. LÄS MER