Sökning: "Vectorization"

Visar resultat 1 - 5 av 29 uppsatser innehållade ordet Vectorization.

  1. 1. AI Based Methods for Matrix Multiplication in High Resolution Simulations of Radio Access Networks

    Master-uppsats, KTH/Matematisk statistik

    Författare :Marcus Johnson; Herman Forslund; [2023]
    Nyckelord :Product-Quantization; MADDNESS; Radio Access Networks; Channel Estimation; MIMO; Approximate Matrix Multiplication; Pruduktkvantisering; MADDNESS; RAN; MIMO; Approximativa matrismultiplikation;

    Sammanfattning : The increasing demand for mobile data has placed significant strain on radio access networks (RANs), leading to a continuous need for increased network capacity. In keeping with that, a significant advancement in modern RANs is the ability to utilize several receivers and transmitters, to allow for beamforming. LÄS MER

  3. 2. Sentence based risk classifier using NLP and machine learning

    Kandidat-uppsats, Högskolan i Halmstad

    Författare :David Tran; Hugo Starck; [2023]
    Nyckelord :;

    Sammanfattning : This project was inspired by the company Dizparc and has a focus onclassification systems together with certain applications of natural languageprocessing. Classification systems are a very extensively researched areadating back to the latter half of the 1900s with multiple different ways of theproblems presented up until its more modern takes in today’s age. LÄS MER

  4. 3. Analyzing user feedback written inmultiple languages and automatically identifyingrequirements from that feedback

    Master-uppsats, Blekinge Tekniska Högskola/Institutionen för programvaruteknik

    Författare :Bhargav Sakamuri; Rithika Vardhan; [2023]
    Nyckelord :Multi-lingual; NLP; Requirements; Automation; Tweets;

    Sammanfattning : Background. Requirements gathering is the most important and often an errorprone task in the software development cycle. There is no perfect procedure to getthe requirements for the developing product. Every organization employs its way ofextracting requirements, and the most common way is to extract requirements fromuser stories. LÄS MER

  5. 4. Multi-Label Toxic Comment Classification Using Machine Learning: An In-Depth Study

    Master-uppsats, Lunds universitet/Institutionen för datavetenskap

    Författare :Matilda Froste; Mosa Hosseini; [2023]
    Nyckelord :natural language processing; machine learning; offensive speech detection; transformers; multi-label classification; Technology and Engineering;

    Sammanfattning : The classification of toxic comments is a well-researched area with many techniques available. However, effectively managing multi-label categorization still requires a considerable amount of work. LÄS MER

  7. 5. 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

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

    Författare :Viktor Karlstrand; [2022]
    Nyckelord :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;

    Sammanfattning : 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. LÄS MER