Sökning: "Sparsity"
Visar resultat 1 - 5 av 62 uppsatser innehållade ordet Sparsity.
1. ISAR Imaging Enhancement Without High-Resolution Ground Truth
Master-uppsats, Linköpings universitet/DatorseendeSammanfattning : In synthetic aperture radar (SAR) and inverse synthetic aperture radar (ISAR), an imaging radar emits electromagnetic waves of varying frequencies towards a target and the backscattered waves are collected. By either moving the radar antenna or rotating the target and combining the collected waves, a much longer synthetic aperture can be created. LÄS MER
2. Over-the-Air Federated Learning with Compressed Sensing
Master-uppsats, Linköpings universitet/KommunikationssystemSammanfattning : The rapid progress with machine learning (ML) technology has solved previously unsolved problems, but training these ML models requires ever larger datasets and increasing amounts of computational resources. One potential solution is to enable parallelization of the computations and allow local processing of training data in distributed nodes, such as Federated Learning (FL). LÄS MER
3. Modelling synaptic rewiring in brain-like neural networks for representation learning
Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)Sammanfattning : This research investigated the concept of a sparsity method inspired by the principles of structural plasticity in the brain in order to create a sparse model of the Bayesian Confidence Propagation Neural Networks (BCPNN) during the training phase. This was done by extending the structural plasticity in the implementation of the BCPNN. LÄS MER
4. Trainable Region of Interest Prediction: Hard Attention Framework for Hardware-Efficient Event-Based Computer Vision Neural Networks on Neuromorphic Processors
Master-uppsats, Lunds universitet/Institutionen för elektro- och informationsteknikSammanfattning : Neuromorphic processors are a promising new type of hardware for optimizing neural network computation using biologically-inspired principles. They can effectively leverage information sparsity such as in images from event-based cameras, and are well-adapted to processing event-based data in an energy-efficient fashion. LÄS MER
5. LDPC DropConnect
Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)Sammanfattning : Machine learning is a popular topic that has become a scientific research tool in many fields. Overfitting is a common challenge in machine learning, where the model fits the training data too well and performs poorly on new data. LÄS MER