Search for dissertations about: "Support vector machine learning SVM"

Showing result 1 - 5 of 23 swedish dissertations containing the words Support vector machine learning SVM.

2. 1. Voice for Decision Support in Healthcare Applied to Chronic Obstructive Pulmonary Disease Classification : A Machine Learning Approach

   Author : Alper Idrisoglu; Johan Sanmartin Berglund; Blekinge Tekniska Högskola; []
   Keywords : NATURVETENSKAP; NATURAL SCIENCES; Automated decision-support; Classification; Machine Learning; Voice-affecting disorders; Voice dataset; Voice Features; Chronic Obstructive pulmonary disease COPD ; Tillämpad hälsoteknik; Applied Health Technology;

   Abstract : Background: Advancements in machine learning (ML) techniques and voice technology offer the potential to harness voice as a new tool for developing decision-support tools in healthcare for the benefit of both healthcare providers and patients. Motivated by technological breakthroughs and the increasing integration of Artificial Intelligence (AI) and Machine Learning (ML) in healthcare, numerous studies aim to investigate the diagnostic potential of ML algorithms in the context of voice-affecting disorders. READ MORE

4. 2. Visual Representations and Models: From Latent SVM to Deep Learning

   Author : Hossein Azizpour; Stefan Carlsson; Barbara Caputo; KTH; []
   Keywords : TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; Computer Vision; Machine Learning; Artificial Intelligence; Deep Learning; Learning Representation; Deformable Part Models; Discriminative Latent Variable Models; Convolutional Networks; Object Recognition; Object Detection; Computer Science; Datalogi;

   Abstract : Two important components of a visual recognition system are representation and model. Both involves the selection and learning of the features that are indicative for recognition and discarding those features that are uninformative. READ MORE

5. 3. On Deep Machine Learning Based Techniques for Electric Power Systems

   Author : Ebrahim Balouji; Chalmers tekniska högskola; []
   Keywords : TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; Deep Learning; Cable faults; phase locked loop; Flicker; Harmonics and Interharmonics; Reinforcement learning; Voltage Dip; Active Power filter; Machine Learning; Voltage fluctuation; Partial Discharges;

   Abstract : This thesis provides deep machine learning-based solutions to real-time mitigation of power quality disturbances such as flicker, voltage dips, frequency deviations, harmonics, and interharmonics using active power filters (APF). In an APF the processing delays reduce the performance when the disturbance to be mitigated is tima varying. READ MORE

6. 4. Privacy-awareness in the era of Big Data and machine learning

   Author : Xuan-Son Vu; Lili Jiang; Erik Elmroth; Umeå universitet; []
   Keywords : NATURVETENSKAP; NATURAL SCIENCES; Differential Privacy; Machine Learning; Deep Learning; Big Data; datalogi; Computer Science;

   Abstract : Social Network Sites (SNS) such as Facebook and Twitter, have been playing a great role in our lives. On the one hand, they help connect people who would not otherwise be connected before. READ MORE

7. 5. Biomarkers for Diagnosis, Therapy and Prognosis in Colorectal Cancer : a study from databases, machine learning predictions to laboratory confirmations

   Author : Xueli Zhang; Hong Zhang; Xiao-Feng Sun; Dirk Repsilber; Bairong Shen; Mauno Vihinen; Örebro universitet; []
   Keywords : MEDICIN OCH HÄLSOVETENSKAP; MEDICAL AND HEALTH SCIENCES; Biomarkers; diagnosis; therapy response; prognosis; database; machine learning; CRC;

   Abstract : Colorectal cancer (CRC) is one of the leading causes of cancer death worldwide. Early diagnosis and better therapy response have been believed to be associated with better prognosis. CRC biomarkers are considered as precise indicators for the early diagnosis and better therapy response. READ MORE