Essays about: "Sparsity"
Showing result 1 - 5 of 61 essays containing the word Sparsity.
-
1. ISAR Imaging Enhancement Without High-Resolution Ground Truth
University essay from Linköpings universitet/DatorseendeAbstract : 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. READ MORE
-
2. Over-the-Air Federated Learning with Compressed Sensing
University essay from Linköpings universitet/KommunikationssystemAbstract : 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). READ MORE
-
3. Modelling synaptic rewiring in brain-like neural networks for representation learning
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : 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. READ MORE
-
4. Trainable Region of Interest Prediction: Hard Attention Framework for Hardware-Efficient Event-Based Computer Vision Neural Networks on Neuromorphic Processors
University essay from Lunds universitet/Institutionen för elektro- och informationsteknikAbstract : 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. READ MORE
-
5. LDPC DropConnect
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : 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. READ MORE