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In this paper, we explore the use of recent conditional generative adversarial network framework for image to image translation applied to the domain of heterogeneous face sketch synthesis. Since the inception of the adversarial framework in 2014, great success has been noted with several variants till date. Further, we introduce a new dataset for composite sketch images. In particular we explore...
Safety and non-safety application services require a guarantee of network performance, mostly in terms of throughput and packet collision. The current radio propagation path loss models use mean additional attenuation sophisticated fading model and do not consider the obstacle caused due to obstacles of vehicles in LOS of transmitting and receiving vehicles. This affects the attenuation signal at...
Modern control theories such as systems engineering approaches try to solve nonlinear system problems by revelation of causal relationship or co-relationship among the components; most of those approaches focus on control of sophisticatedly modeled white-boxed systems. We suggest an application of actor-critic reinforcement learning approach to control a nonlinear, complex and black-boxed system....
In this paper, we propose a patched-based deep Boltzmann shape priors for visual tracking. The shape priors are generated from deep Boltzmann machine network. The network consists of three layers of hidden and visible units. The generated shapes not only maintain general shapes from a variety of poses, but also entail local modifications with high probability.
The fifth-generation (5G) mobile systems are considered as a promising infrastructure to provide connectivity for massive Internet-of-Things (IoT) devices leading to the fourth industrial revolution (Industry 4.0), i.e., smart manufacturing. The smart manufacturing is characterized by capabilities of digitization, smartization, and connectivity for manufacturing operations and machinery where a huge...
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