Conservation planning and conflict resolution require careful monitoring and analysis of wildlife. Video traps, in combination with AI-based analytic tools, are an excellent example of noninvasive technology used successfully ...

Deep learning neural networks have revolutionized the elds of Computer Vision, Robotics, Artifi cial Intelligence. However, these State of the art algorithms come at a high computational cost, huge memory requirements and ...

Recent advancement in deep learning techniques has opened doors for wide variety of applications. With growing interests in deep learning and geometry, lots of computer vision problems have been tackled using deep learning. ...

We use Mean Shift clustering in the latent space of an auto-encoder to have a better representation of the data and a more structured latent space. Instead of just using the mode of the distribution calculated using kernel ...

Disentangling higher level generative factors as disjoint latent dimensions offer several benefits such as ease of deriving invariant representations, targeted data augmentation with style transfer, better interpretability ...

In machine learning, disentangling factors of variation lead to robust latent space representations and improve the efficacy of various downstream tasks like classification, prediction etc. Disentangling representations ...

One of the major problems faced with advanced driver assistance systems is to correctly estimate Driver's situation awareness. We detect and track other vehicles and use that to predict if an accident will occur. We propose ...

The prediction of multi-agent behavior is crucial for the development of advanced human-robot interactive systems, particularly in domains like self-driving cars. Existing trajectory forecasting methods often lack the ...

Convolutional Neural Networks are trained using a gradient descent back propagation technique which trains weights in each layer for the sole goal of minimizing training error. Hence, the resulting weights cannot be ...

We addressed the problem of jointly selecting communications and vehicular planning strategies with the goal of optimizing the driving utility like the speed of the car. Much related work assumes the communications channels ...