Sökning: "Learning Brain"

Visar resultat 1 - 5 av 251 uppsatser innehållade orden Learning Brain.

1. 1. Optical Communication using Nanowires and Molecular Memory Systems

   Master-uppsats, Lunds universitet/Fysiska institutionen; Lunds universitet/Synkrotronljusfysik

   Författare :Thomas Kjellberg Jensen; [2024]
   Nyckelord :neuromorphic computing; nanowire; molecular dye; DASA photoswitch; OBIC; Physics and Astronomy;

   Sammanfattning : Neuromorphic computational networks, inspired by biological neural networks, provide a possible way of lowering computational energy cost, while at the same time allowing for much more sophisticated devices capable of real-time inferences and learning. Since simulating artificial neural networks on conventional computers is particularly inefficient, the development of neuromorphic devices is strongly motivated as the reliance on AI-models increases. LÄS MER

3. 2. Image-classification for Brain Tumor using Pre-trained Convolutional Neural Network : Bildklassificering för hjärntumör medhjälp av förtränat konvolutionell tneuralt nätverk

   M1-uppsats, KTH/Hälsoinformatik och logistik

   Författare :Ahmad Osman; Bushra Alsabbagh; [2023]
   Nyckelord :Brain tumor; Deep learning; Convolutional Neural Network CNN ; diagnosis; Image classification; pre-trained models; dataset; economic impact.; Cancer; Hjärntumör; Artificiell intelligens AI ; djupinlärning; konvolutionellt neuralt nätverk CNN ; Diagnostik; Bildklassificering; förtränade modeller; dataset.;

   Sammanfattning : Brain tumor is a disease characterized by uncontrolled growth of abnormal cells inthe 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 itsfunctions. The number of global mortality in 2020 led by cancerous brains was estimatedat 251,329. LÄS MER

4. 3. Image-classification for Brain Tumor using Pre-trained Convolutional Neural Network

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

   Författare :Bushra Alsabbagh; [2023]
   Nyckelord :Brain tumor; Deep learning; Convolutional Neural Network CNN ; diagnosis; Image classification; pre-trained models; dataset; economic impact.; Cancer; Hjärntumör; Artificiell intelligens AI ; djupinlärning; konvolutionellt neuralt nätverk CNN ; Diagnostik; Bildklassificering; förtränade modeller; dataset.;

   Sammanfattning : 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. LÄS MER

5. 4. Comparison of Hebbian Learning and Backpropagation for Image Classification in Convolutional Neural Networks

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

   Författare :Teodor Morfeldt Gadler; [2023]
   Nyckelord :;

   Sammanfattning : Current commonly used image recognition convolutional neural networks share some similarities with the human brain. However, the differences are many and the well established backpropagation learning algorithm is not biologically plausible. LÄS MER

7. 5. Evaluating Brain-Inspired Machine Learning Models for Time Series Forecasting: A Comparative Study on Dynamical Memory in Reservoir Computing and Neural Networks

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

   Författare :Eddie Nevander Hellström; Johan Slettengren; [2023]
   Nyckelord :;

   Sammanfattning : Brain-inspired computing is a promising research field, with potential to encouragebreakthroughs within machine learning and enable us to solve complex problems in a moreefficient way. This study aims to compare the performance of brain-like machine learningalgorithms for time series forecasting. LÄS MER