Essays about: "Djupinlärning"

Showing result 11 - 15 of 374 essays containing the word Djupinlärning.

  1. 11. AI/ML Development for RAN Applications : Deep Learning in Log Event Prediction

    University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Author : Yuxin Sun; [2023]
    Keywords : LSTM; Anomaly Detection; Failure Prediction; Log Mining; Deep Learning; LSTM; Anomali Detection; Failure Prediction; Log Mining; Deep Learning;

    Abstract : Since many log tracing application and diagnostic commands are now available on nodes at base station, event log can easily be collected, parsed and structured for network performance analysis. In order to improve In Service Performance of customer network, a sequential machine learning model can be trained, test, and deployed on each node to learn from the past events to predict future crashes or a failure. READ MORE

  3. 12. Extraction of Global Features for enhancing Machine Learning Performance

    University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Author : Abyel Tesfay; [2023]
    Keywords : Machine Learning; Deep Learning; Feature Extraction; Global Features; Time-series data; Bioprocessing; Maskininlärning; Djupinlärning; Funktionsextraktion; Globala Funktioner; Tidsserie data; Biobearbetning;

    Abstract : Data Science plays an essential role in many organizations and industries to become data-driven in their decision-making and workflow, as models can provide relevant input in areas such as social media, the stock market, and manufacturing industries. To train models of quality, data preparation methods such as feature extraction are used to extract relevant features. READ MORE

  4. 13. The Impact of the Retrieval Text Set for Text Sentiment Classification With the Retrieval-Augmented Language Model REALM

    University essay from KTH/Matematik (Inst.)

    Author : Oscar Blommegård; [2023]
    Keywords : The Impact of the Retrieval Text Set for Text Sentiment Classification With the Retrieval-Augmented Language Model REALM; Hämtningsförstärkta språkmodeller; Natural Language Processing; Transformers; Djupinlärning; Textklassificering;

    Abstract : Large Language Models (LLMs) have demonstrated impressive results across various language technology tasks. By training on large corpora of diverse text collections from the internet, these models learn to process text effectively, allowing them to acquire comprehensive world knowledge. READ MORE

  5. 14. Deep Learning-based Regularizers for Cone Beam Computed Tomography Reconstruction

    University essay from KTH/Matematisk statistik

    Author : Sabina Syed; Josefin Stenberg; [2023]
    Keywords : Adversarial Convex Regularization; Computer Vision; Cone Beam Computed Tomography; Convolutional Neural Networks; Deep Learning; Image Reconstruction; Adversarial Convex Regularization; Bildrekonstruktion; Datorseende; Djupinlärning; Faltningsnätverk; Volymtomografi;

    Abstract : Cone Beam Computed Tomography is a technology to visualize the 3D interior anatomy of a patient. It is important for image-guided radiation therapy in cancer treatment. During a scan, iterative methods are often used for the image reconstruction step. READ MORE

  6. 15. Technology Acceptance for AI implementations : A case study in the Defense Industry about 3D Generative Models

    University essay from KTH/Skolan för industriell teknik och management (ITM)

    Author : Michael Arenander; [2023]
    Keywords : Technology Acceptance; Artificial Intelligence; Machine Learning; 3D Generative Models; Innovation; Teknisk Acceptans; Artificiell Intelligens; Maskininlärning; 3D Generativa Modeller; Innovation;

    Abstract : Advancements in Artificial Intelligence (AI), Machine Learning (ML), and Deep Learning (DL) has emerged into 3D object creation processes through the rise of 3D Generative Adversarial Networks (3D GAN). These networks contain 3D generative models capable of analyzing and constructing 3D objects. READ MORE