Samankaltainen aineisto
Näytetään aineistoja, joilla on samankaltainen nimeke tai asiasanat.
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Reducing redundancy in the bottleneck representation of autoencoders
Laakom, Firas; Raitoharju, Jenni; Iosifidis, Alexandros; Gabbouj, Moncef (Elsevier, 2024)Autoencoders (AEs) are a type of unsupervised neural networks, which can be used to solve various tasks, e.g., dimensionality reduction, image compression, and image denoising. An AE has two goals: (i) compress the original ... -
A method for anomaly detection in hyperspectral images, using deep convolutional autoencoders
Penttilä, Jeremias (2017)Menetelmä poikkeavuuksien havaitsemiseen hyperspektrikuvista käyttäen syviä konvolutiivisia autoenkoodereita. Poikkeavuuksien havaitseminen kuvista, erityisesti hyperspektraalisista kuvista, on hankalaa. Kun ongelmaan ... -
Data Mining for the Security of Cyber Physical Systems Using Deep-Learning Methods
Nath, Bhagawan; Hämäläinen, Timo; Ezekiel, Soundararajan (Academic Conferences International Ltd, 2022)Cyber Physical Systems (CPSs) have become widely popular in recent years, and their applicability have been growing exponentially. A CPS is an advanced system that incorporates a computation unit along with a hardware unit, ... -
Application of a Knowledge Discovery Process to Study Instances of Capacitated Vehicle Routing Problems
Kärkkäinen, Tommi; Rasku, Jussi (Springer, 2020)Vehicle Routing Problems (VRP) are computationally challenging, constrained optimization problems, which have central role in logistics management. Usually different solvers are being developed and applied for different ... -
Encryption and Generation of Images for Privacy-Preserving Machine Learning in Smart Manufacturing
Terziyan, Vagan; Malyk, Diana; Golovianko, Mariia; Branytskyi, Vladyslav (Elsevier, 2023)Current advances in machine (deep) learning and the exponential growth of data collected by and shared between smart manufacturing processes give a unique opportunity to get extra value from that data. The use of public ...
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