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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 ...
Relating Representations in Deep Learning and the Brain
Deep Neural Networks (DNN) inspired by the human brain have redefined the state-of-the-art performance in AI during the past decade. Much of the research is still trying to understand and explain the function of these ...
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, ...
Adaptive charging techniques for Li-ion battery using Reinforcement Learning
Li-ion batteries have become a promising technology in recent years and are used everywhere from low-end devices like mobile phones to high-end ones like electric vehicles. In most applications, the discharge of a battery ...
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 ...
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 ...
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 ...
Optimization of Traversal Queries on Distributed Graph Stores
In this era of Big Data Analytics, much of the semi-structured data has inherent interconnectivity
between representative entities. These are increasingly being modeled as property graphs
because of the semantic advantages ...
Deep Visual Representations: A study on Augmentation, Visualization, and Robustness
Deep neural networks have resulted in unprecedented performances for various learning tasks. Particularly,
Convolutional Neural Networks (CNNs) are shown to learn representations that can efficiently
discriminate hundreds ...