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Face Recognition in Unconstrained Environment
The goal of computer vision is to provide the ability to machines to understand image data and infer
the useful information from it. The inferences highly depend on the quality of the image data. But in
many real-world ...
Spectrotemporal Processing of Speech Signals Using the Riesz Transform
Speech signals possess a rich time-varying spectral content, which makes their analysis a challenging signal processing problem. Developing methods for accurate speech analysis has a direct impact on applications such as ...
Plasma catalysis of diesel exhaust using industrial wastes: a study on NOX and THC removal
Air pollution, caused by large scale consumption of fossil fuels such as diesel, has been the leading cause of
several adverse environmental effects such as global warming, higher acidity in rainwater, lower yield ...
Techniques for estimating the direction of pointing gestures using depth images in the presence of orientation and distance variations from the depth sensor
A significant part of our daily life is spent interacting with various computing devices, mobile phones, etc. Soon, robots and drones may become common in daily life, as might be virtual reality based interfaces. Currently, ...
Novel Regularized Image Reconstruction Algorithms for Sparse Photoacoustic Tomography
Among all tissue imaging modalities, photo-acoustic tomography (PAT), has been getting increasing attention in the recent past due to the fact that it has high contrast, high penetrability, and has capability of retrieving ...
Probabilistic source-filter model of speech
The human respiratory system plays a crucial role in breathing and swallow
ing. However, it also plays an essential role in speech production, which is
unique to humans. Speech production involves expelling air from the ...
Spatially Adaptive Regularization for Image Restoration
Image restoration/reconstruction refers to the estimation of an underlying image from measurements
generated by imaging devices. This problem is generally ill-posed since the
measurements are corrupted by the physical ...
A Learnable Distillation Approach For Model-agnostic Explainability With Multimodal Applications
Deep neural networks are the most widely used examples of sophisticated mapping functions from feature space to class labels. In the recent years, several high impact decisions in domains such as finance, healthcare, law ...
Modelling, Stabilization Methods and Power Amplification for Power Hardware-in-Loop Simulation with Improved Accuracy
Accurate testing of a device under development, in near to real-life environment, is essential
to the rapid growth of emerging technologies such as distributed generation, renewable energy
sources, electrical storage, ...
Fast and Compact Voltage Equalizer for Satellite Applications
Lithium-ion batteries have now become an essential constituent of the Electrical Power System
of solar-powered satellites due to their high energy density, wider operating temperature range
, and better radiation tolerance. ...