Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
Results
Showing 1 to 4 of 4 for “"Convolutional Autoencoders"”.
-
Characterization of electroluminescence signals from nuclear recoil events in the dual-phase argon Time Projection Chamber of the Red experiment with Convolutional Autoencoders
… analysis method. Specifically, I implemented a convolutional autoencoder (CAE) to classify electroluminescence signals recorded by silicon photomultipliers at cryogenic temperatures. By leveraging machine learning, the CAE efficiently identified patterns in experimental data, offering a novel, …
-
Efficient Multi-Objective NeuroEvolution in Computer Vision and Applications for Threat Identification
… This thesis leverages state-of-the-art convolutional autoencoders and semantic seg- mentation (Chapter 2) to develop effective multi-objective AutoML strategies for neural architecture search. These strategies are designed for threat detection and provide in- sights into some …
-
Clustering and dimensionality reduction for time-series service monitoring data
… as the initial dataset) produced with Deep and Convolutional AutoEncoders. The experiments disclose that the reconstructed dataset with Deep AutoEncoder is the most performing. Later, we propose an ensemble-based DR approach to effectively handle the high-dimensionality of the E2E dataset. The …
-
Efficient Edge Intelligence in the Era of Big Data
… leverage Deep Learning (DL), more specifically, Convolutional Autoencoder (CAE), to learn a sparse representation of the vital big data. The minimized energy need, even taking into consideration the CAE-induced overhead, is tremendously lower than the original energy need. Further, compared with …