Sökning: "Djupinlärning"
Visar resultat 1 - 5 av 321 uppsatser innehållade ordet Djupinlärning.
1. Towards Realistic Datasets forClassification of VPN Traffic : The Effects of Background Noise on Website Fingerprinting Attacks
Kandidat-uppsats, Karlstads universitet/Institutionen för matematik och datavetenskap (from 2013)Sammanfattning : Virtual Private Networks (VPNs) is a booming business with significant margins once a solid user base has been established and big VPN providers are putting considerable amounts of money into marketing. However, there exists Website Fingerprinting (WF) attacks that are able to correctly predict which website a user is visiting based on web traffic even though it is going through a VPN tunnel. LÄS MER
2. Maximizing the performance of point cloud 4D panoptic segmentation using AutoML technique
Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)Sammanfattning : Environment perception is crucial to autonomous driving. Panoptic segmentation and objects tracking are two challenging tasks, and the combination of both, namely 4D panoptic segmentation draws researchers’ attention recently. LÄS MER
3. Deep Ring Artifact Reduction in Photon-Counting CT
Master-uppsats, KTH/FysikSammanfattning : Ring artifacts are a common problem with the use of photon-counting detectors and commercial deployment rests on being able to compensate for them. Deep learning has been proposed as a candidate for tackling the inefficiency or high cost of traditional techniques. LÄS MER
4. A deep learning based side-channel analysis of an FPGA implementation of Saber
Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)Sammanfattning : In 2016, NIST started a post quantum cryptography (PQC) standardization project in response to the rapid development of quantum algorithms which break many public-key cryptographic schemes. As the project nears its end, it is necessary to assess the resistance of its finalists to side-channel attacks. LÄS MER
5. Artificial Neural Networks and Inductive Biases for Multi-Instance Multi-Modal Tabular Data : A Case Study for Default Probability Estimation in Small-to-Medium Enterprise Lending
Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)Sammanfattning : The success of artificial neural networks in homogeneous data domains such as images, textual data, and audio and other signals has had considerable impact on Machine Learning and science in general. The domain of heterogeneous tabular data, while arguably much more common, remains much less explored with regards to artificial neural networks and deep learning. LÄS MER
