Essays about: "Multimodal learning"

Showing result 1 - 5 of 44 essays containing the words Multimodal learning.

  1. 1. Duplicate detection of multimodal and domain-specific trouble reports when having few samples : An evaluation of models using natural language processing, machine learning, and Siamese networks pre-trained on automatically labeled data

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

    Author : Viktor Karlstrand; [2022]
    Keywords : Duplicate detection; Bug reports; Trouble reports; Natural language processing; Information retrieval; Machine learning; Siamese neural network; Transformers; Automated data labeling; Shapley values; Dubblettdetektering; Felrapporter; Buggrapporter; Naturlig språkbehandling; Informationssökning; Maskininlärning; Siamesiska neurala nätverk; Transformatorer; Automatiserad datamärkning; Shapley-värden;

    Abstract : Trouble and bug reports are essential in software maintenance and for identifying faults—a challenging and time-consuming task. In cases when the fault and reports are similar or identical to previous and already resolved ones, the effort can be reduced significantly making the prospect of automatically detecting duplicates very compelling. READ MORE

  2. 2. Hybrid Deep Learning Model for Cellular Network Traffic Prediction : Case Study using Telecom Time Series Data, Satellite Imagery, and Weather Data

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

    Author : Ali Shibli; [2022]
    Keywords : Cellular network traffic; multi-modal; satellite imagery; weather data; LSTM; CNN; time series; Trafic sur les réseaux cellulaires; multimodal; imagerie satellite; données météo; LSTM; CNN; séries temporelles; Förutsägelse av mobilnätstrafik; multimodal modell; satellitbilder; väderdata; LSTM; CNN; tidsseriein;

    Abstract : Cellular network traffic prediction is a critical challenge for communication providers, which is important for use cases such as traffic steering and base station resources management. Traditional prediction methods mostly rely on historical time-series data to predict traffic load, which often fail to model the real world and capture surrounding environment conditions. READ MORE

  3. 3. Pediatric Brain Tumor Type Classification in MR Images Using Deep Learning

    University essay from Linköpings universitet/Institutionen för medicinsk teknik

    Author : Tamara Bianchessi; [2022]
    Keywords : pediatric brain tumors; MR image analysis; deep learning; classification; model explainability;

    Abstract : Brain tumors present the second highest cause of death among pediatric cancers. About 60% are located in the posterior fossa region of the brain; among the most frequent types the ones considered for this project were astrocytomas, medulloblastomas, and ependymomas. READ MORE

  4. 4. News article segmentation using multimodal input : Using Mask R-CNN and sentence transformers

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

    Author : Gustav Henning; [2022]
    Keywords : Historical newspapers; Image segmentation; Multimodal learning; Deep learning; Digital humanities; Mask R-CNN; Historiska tidningar; Bildsegmentering; Multimodal inlärning; Djupinlärning; Digital humaniora; Mask R-CNN;

    Abstract : In this century and the last, serious efforts have been made to digitize the content housed by libraries across the world. In order to open up these volumes to content-based information retrieval, independent elements such as headlines, body text, bylines, images and captions ideally need to be connected semantically as article-level units. READ MORE

  5. 5. Primary stage Lung Cancer Prediction with Natural Language Processing-based Machine Learning

    University essay from KTH/Skolan för kemi, bioteknologi och hälsa (CBH)

    Author : Ahmad Sadek; [2022]
    Keywords : Lung cancer; precision medicine; machine learning; explainable AI; Natural Language Processing NLP; patient stratification; oncology; Lungcancer; precisionsmedicin; maskininlärning; NLP; förklarbar AI; patientstratifiering; onkologi;

    Abstract : Early detection reduces mortality in lung cancer, but it is also considered as a challenge for oncologists and for healthcare systems. In addition, screening modalities like CT-scans come with undesired effects, many suspected patients are wrongly diagnosed with lung cancer. READ MORE