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Deep Learning in Computer Vision: Studies in Neuro-image Segmentation and Satellite Image Super-resolution
Single image super-resolution (SR) has been a topic of great interest in the computer vision
and deep learning community and has found applications in many areas including quality
enhancement of satellite images. As the ...
Epistasis Detection and Phenotype Prediction in GWAS Using Machine Learning Methods
Genome-wide association studies (GWAS) are used to find the association between genetic variants, Single Nucleotide Polymorphisms (SNPs), and phenotypic traits or diseases in a population. The number of GWAS has increased ...
Optimizing the Interval-centric Distributed Computing Model for Temporal Graph Algorithms
Graphs with temporal characteristics are increasingly becoming prominent. Their vertices, edges and attributes are annotated with a lifespan, allowing one to add or remove vertices and edges. Such graphs can grow to millions ...
Reliable and Efficient Application Scheduling on Edge, Fog and Cloud
Cloud computing has emerged in the last decade as a popular distributed computing service
offered by commercial providers. Public Clouds offer pay-as-you-go access to elastic resources
that can be acquired and released ...
Efficient and Resilient Stream Processing in Distributed Shared Environment
Internet of Things (IoT) deployments comprising of sensors and actuators collect observational
data and provide continuous streams of data, often called streaming data or fast data. Smart
Cities use such IoT technologies ...
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 ...
Characterization of Divergence resulting from Workload, Memory and Control-Flow behavior in GPGPU Applications
GPGPUs have emerged as high-performance computing platforms and are used for boosting
the performance of general non-graphics applications from various scientifi c domains. These
applications span varied areas like social ...
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, ...
Algorithms for Estimating Integrals in High Dimensional Spaces
Sampling, estimation and integration in high dimensional continuous spaces is required in diverse areas ranging from modeling multi-particle physical systems and optimization to inference from data. When the number of ...
Understanding spontaneous emission in the strong coupling regime of an emitter and absorbing matter
This thesis proposes a partition of optical states into radiative and non-radiative parts when an emitter is proximal to resonant absorbing nanostructures. The conventional partition is valid only for the weak coupling ...