Browsing Department of Computational and Data Sciences (CDS) by thesis submitted date"2021"
Now showing items 1-6 of 6
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Advances in High Dynamic Range Imaging Using Deep Learning
Natural scenes have a wide range of brightness, from dark starry nights to bright sunlit beaches. Our human eyes can perceive such a vast range of illumination through various adaptation techniques, thus allowing us to ... -
Development of Fully Data Driven Novel Methods for Improving the micro-Computed Tomography Image Quality for Digital Rock
The Digital Rock workflow is an emerging framework utilizing advances in imaging technologies and state-of-the-art image processing algorithms to construct digital models of reservoir rocks. These digital models become ... -
Enhancing Blockchain Implementations
Blockchain technology elegantly provides a spectrum of desirable semantic properties, including immutability, authenticity, verifiability, and data integrity. In recent years, implementing blockchains on relational database ... -
Novel Deep Learning Methods for Improving Low-Dose Computed Tomography Perfusion Imaging of Brain
Computed Tomography (CT) Perfusion imaging is a non-invasive medical imaging modality that has also established itself as a fast and economical imaging modality for diagnosing cerebrovascular diseases such as acute ischemia, ... -
Optimizing Matrix Multiplication for the REDEFINE Many-Core Co-processor
Matrix-matrix multiplication is an important operation for many applications and hence it is required to be parallelized optimally for the architecture the applications will run on. REDE- FINE is a many-core co-processor ... -
Static Analysis and Dynamic Monitoring of Program Flow on REDEFINE Manycore Processor
Manycore heterogeneous architectures are becoming the promising choice for high-performance computing applications. Multiple parallel tasks run concurrently across different processor cores sharing the same communication ...