2 citations · 4 across the 4 of their papers we have counts for
4 papers
Bandwidth-Adaptive Feature Sharing for Cooperative LIDAR Object Detection
Ehsan Emad Marvasti, Arash Raftari, Amir Emad Marvasti +1
Situational awareness as a necessity in the connected and autonomous vehicles (CAV) domain is the subject of a significant number of researches in recent years. The driver's safety…
Cooperative LIDAR Object Detection via Feature Sharing in Deep Networks
Ehsan Emad Marvasti, Arash Raftari, Amir Emad Marvasti +3
The recent advancements in communication and computational systems has led to significant improvement of situational awareness in connected and autonomous vehicles. Computationally…
Maximum Probability Theorem: A Framework for Probabilistic Learning
Amir Emad Marvasti, Ehsan Emad Marvasti, Ulas Bagci +1
We present a theoretical framework of probabilistic learning derived by Maximum Probability (MP) Theorem shown in the current paper. In this probabilistic framework, a model is def…
Rediscovering Deep Neural Networks Through Finite-State Distributions
Amir Emad Marvasti, Ehsan Emad Marvasti, George Atia +1
We propose a new way of thinking about deep neural networks, in which the linear and non-linear components of the network are naturally derived and justified in terms of principles…