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Showing result 1 - 5 of 8 essays matching the above criteria.
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1. Modeling and Simulation of a Remote Controlled Weapon Station
University essay from KTH/Matematik (Avd.)Abstract : Understanding how a system behaves when exposed to different scenarios is key when improvingand developing complex structures. The amount of different approaches is immense and variesfrom case to case. READ MORE
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2. Feature extraction from MEG data using self-supervised learning : Investigating contrastive representation learning methods to f ind informative representations
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : Modern day society is vastly complex, with information and data constantly being posted, shared, and collected everywhere. There is often an abundance of massive amounts of unlabeled data that can not be leveraged in a supervised machine learning context. READ MORE
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3. A Novel Shoeprint Enhancement method for Forensic Evidence Using Sparse Representation method.
University essay from Blekinge Tekniska Högskola/Institutionen för tillämpad signalbehandlingAbstract : Shoeprints are often recovered at crime scenes and are the most abundant form of evidence at a crime scene, and in some cases, it is proved to be as accurate as fingerprints. The basis for shoeprint impression evidence is determining the source of a shoeprint impression recovered from a crime scene. READ MORE
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4. Architecture Designfor Compressed Sensing-Based Low Power Systems
University essay from KTH/Skolan för informations- och kommunikationsteknik (ICT)Abstract : In the Internet of Things scenario, a desirable feature of wireless sensors is the energy autonomy. However, the transmitter stage needs a great amount of energy to modulate and transmit the interested information. READ MORE
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5. Statistical Parametric Mapping of fMRI data using Spectral Graph Wavelets
University essay from Medicinsk informatik; Tekniska högskolanAbstract : In typical statistical parametric mapping (SPM) of fMRI data, the functional data are pre-smoothed using a Gaussian kernel to reduce noise at the cost of losing spatial specificity. Wavelet approaches have been incorporated in such analysis by enabling an efficient representation of the underlying brain activity through spatial transformation of the original, un-smoothed data; a successful framework is the wavelet-based statistical parametric mapping (WSPM) which enables integrated wavelet processing and spatial statistical testing. READ MORE
