Essays about: "SemiSupervised Learning."

Showing result 1 - 5 of 10 essays containing the words SemiSupervised Learning..

1. 1. Meta-Pseudo Labelled Multi-View 3D Shape Recognition

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

   Author : Fehmi Ayberk Uçkun; [2023]
   Keywords : 3D shape recognition; 3D object classification; 3D shape retrieval; 3D object retrieval; Automatic labelling; Semi-supervised learning; Pseudo labelling; Meta Pseudo Labelling; Multi-View Convolutional Neural Networks; Shape descriptors; Multi-view representations; Deeplearning; 3D-formigenkänning; 3D-objektklassificering; 3D-formhämtning; Hämtning av 3D-objekt; Automatisk märkning; Halv-vägledd lärning; Pseudomärkning; Meta Pseudo-märkning; Multi-View Faltningsnät; Formbeskrivningar; Multi-view representation; Djupinlärning;

   Abstract : The field of computer vision has long pursued the challenge of understanding the three-dimensional world. This endeavour is further fuelled by the increasing demand for technologies that rely on accurate perception of the 3D environment such as autonomous driving and augmented reality. READ MORE

3. 2. Semi-Supervised Head Detection for Low Resolution Images

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

   Author : Annie Biby Rapheal; [2023]
   Keywords : Object detection; Semi Supervised Learning; Head detection; Objektdetektion; Semisupervised Learning; Huvuddetektion;

   Abstract : Object detection is a widely researched and applied field in computer vision. Deep learning models have successfully been used for object detection over the years. The performance of State of the art (SOTA) object detection deep learning models is dependent on the number of labeled images. READ MORE

4. 3. Network Graph AnalysisCategorizing Private Individuals and Private Firms in a Bank

   University essay from Uppsala universitet/Institutionen för informationsteknologi

   Author : Tayyeba Muhammad Khan; [2022]
   Keywords : ;

   Abstract : This study deals with classifying private individuals and private firmsthrough transaction data of a financial institution. Private firm(Enskild Firma) in Sweden is difficult to distinguish from privateindividual through transactions as it is owned by a sole trader who hasa small business. READ MORE

5. 4. Matching Sticky Notes Using Latent Representations

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

   Author : Javier García San Vicent; [2022]
   Keywords : Pattern matching; Image matching; Image recognition; Representation learning; Unsupervised learning; Semisupervised learning; Siamese architecture; Deep learning; Transfer learning; Mönstermatchning; Bildmatchning; Bildigenkänning; Representationsinlärning; Oövervakat lärande; Halvövervakat lärande; Siamesisk arkitektur; Djup lärning; Överfört lärande;

   Abstract : his project addresses the issue of accurately identifying repeated images of sticky notes. Due to environmental conditions and the 3D location of the camera, different pictures taken of sticky notes may look distinct enough to be hard to determine if they belong to the same note. READ MORE

6. 5. Deep Active Learning for Image Classification using Different Sampling Strategies

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

   Author : Shahin Saleh; [2021]
   Keywords : Convolutional Neural Network; Deep Active Learning; Deep Learning; Image Classification; Sampling Strategies; SemiSupervised Learning.; Bildklassificering; Faltningsnätverk; Deep Active Learning; Djupinlärning; Semiövervakat lärande; Urvalsstrategier.;

   Abstract : Convolutional Neural Networks (CNNs) have been proved to deliver great results in the area of computer vision, however, one fundamental bottleneck with CNNs is the fact that it is heavily dependant on the ground truth, that is, labeled training data. A labeled dataset is a group of samples that have been tagged with one or more labels. READ MORE