Essays about: "transfer learning"
Showing result 11 - 15 of 516 essays containing the words transfer learning.
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11. Ultrasound neural style transfer using domain specific features
University essay from Uppsala universitet/Institutionen för informationsteknologiAbstract : Ultrasound imaging is a widely used fast, low-cost, and non-invasive modality for monitoringfetal development during pregnancy and identifying potential problems or other injuries.However, interpreting the images may be difficult due to the noisy appearance and requiresextensive training of sonographers. READ MORE
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12. Image-classification for Brain Tumor using Pre-trained Convolutional Neural Network
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : Brain tumor is a disease characterized by uncontrolled growth of abnormal cells in the brain. The brain is responsible for regulating the functions of all other organs, hence, any atypical growth of cells in the brain can have severe implications for its functions. READ MORE
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13. Dating of fashion plates (1820-1880) using transfer learning : Recognition of the year of origin of fashion plates
University essay from Jönköping University/Jönköping AI Lab (JAIL)Abstract : Fashion history is an integral subfield of history as a whole. Fashion plates provide important evidence of what fashion once looked like and as such are a valuable window into the lives of the people in ages past. READ MORE
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14. FPGA programming with VHDL : A laboratory for the students in the Switching Theory and Digital Design course
University essay from Högskolan i HalmstadAbstract : This thesis aims to create effective and comprehensive learning materials for students enrolled in the Switching Theory and Digital Design course. The lab is designed to enable students to program an FPGA using VHDL in the Quartus programming environment to control traffic intersections with sensors and traffic signals. READ MORE
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15. Understanding the Robustnessof Self Supervised Representations
University essay from Luleå tekniska universitet/Institutionen för system- och rymdteknikAbstract : This work investigates the robustness of learned representations of self-supervised learn-ing approaches, focusing on distribution shifts in computer vision. Joint embedding architecture and method-based self-supervised learning approaches have shown advancesin learning representations in a label-free manner and efficient knowledge transfer towardreducing human annotation needs. READ MORE