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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 ...
Development of Novel Deep Learning Methods for Fast-MRI: Anatomical Image Reconstruction to Quantitative Imaging
In medical imaging, the task of estimating interpretable anatomical images from raw scanner data - based on underlying physical principles - is known as an "inverse problem". The solution to such inverse problems can be ...
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 ...
Towards Robust and Scalable Video Surveillance: Cross-modal and Domain Generalizable Person Re-identification
With rapid technological advances, one can easily find video surveillance systems deployed in public places such as malls, airports etc. as well as across private residential areas. These systems play a critical role in ...
Landmark Estimation and Image Synthesis Guidance using Self-Supervised Networks
The exponential rise in the availability of data over the past decade has fuelled research in deep learning. While supervised deep learning models achieve near-human performance using annotated data, it comes with an ...
Theory and Algorithms for sequential non-Gaussian Bayesian filtering and estimation
Seamless integration of dynamical system models with sparse measurements, called as Data Assimilation, is important in many applications like weather forecasting, socio-economics, navigation, and beyond. In order to produce ...
Learning to Perceive Humans From Appearance and Pose
Analyzing humans and their activities takes a central role in computer vision. This requires machine learning models to encapsulate both the diverse poses and appearances exhibited by humans. Estimating the 3D poses of ...
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 ...
Prediction of Dynamical Systems by Constraining the Dynamics on the Observational Manifold
Evolution models of dynamical systems posed as differential equations generally do not include all the factors affecting the system. This leads to a mismatch between the model prediction and the observations. In this work, ...
Migrating VM Workloads to Containers: Issues and Challenges
Modern day enterprises are adopting virtualization to leverage the benefits of improved server utilization through workload consolidation. Server consolidation provides this benefit to enterprise applications as many of ...