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pro vyhledávání: '"A, Filev"'
We present CompactFlowNet, the first real-time mobile neural network for optical flow prediction, which involves determining the displacement of each pixel in an initial frame relative to the corresponding pixel in a subsequent frame. Optical flow se
Externí odkaz:
http://arxiv.org/abs/2412.13273
In this paper, we develop a computationally-efficient approach to minimum-time trajectory optimization using input-output data-based models, to produce an end-to-end data-to-control solution to time-optimal planning/control of dynamic systems and hen
Externí odkaz:
http://arxiv.org/abs/2312.05724
Markov chain-based modeling and Koopman operator-based modeling are two popular frameworks for data-driven modeling of dynamical systems. They share notable similarities from a computational and practitioner's perspective, especially for modeling aut
Externí odkaz:
http://arxiv.org/abs/2310.05508
Connected and autonomous vehicles (CAVs) promise next-gen transportation systems with enhanced safety, energy efficiency, and sustainability. One typical control strategy for CAVs is the so-called cooperative adaptive cruise control (CACC) where vehi
Externí odkaz:
http://arxiv.org/abs/2308.02345
Autor:
Ghafourian, Amin, Shui, Huanyi, Upadhyay, Devesh, Gupta, Rajesh, Filev, Dimitar, Bozchalooi, Iman Soltani
Autoencoders have been extensively used in the development of recent anomaly detection techniques. The premise of their application is based on the notion that after training the autoencoder on normal training data, anomalous inputs will exhibit a si
Externí odkaz:
http://arxiv.org/abs/2306.12627
Autonomous driving has received a great deal of attention in the automotive industry and is often seen as the future of transportation. The development of autonomous driving technology has been greatly accelerated by the growth of end-to-end machine
Externí odkaz:
http://arxiv.org/abs/2305.14644
Optimization algorithms are very different from human optimizers. A human being would gain more experiences through problem-solving, which helps her/him in solving a new unseen problem. Yet an optimization algorithm never gains any experiences by sol
Externí odkaz:
http://arxiv.org/abs/2304.04166
Publikováno v:
Agrosystems, Geosciences & Environment, Vol 7, Iss 4, Pp n/a-n/a (2024)
Abstract The viability of modern horticulture heavily relies on adopting sustainable practices. Understanding soil spatial variability on heavy clay soils and its impact on young trees is crucial to design suitable soil and water management strategie
Externí odkaz:
https://doaj.org/article/6584a32ac85e4b07a3b59f5711e7d2ab
This paper introduces the Generalized Action Governor, which is a supervisory scheme for augmenting a nominal closed-loop system with the capability of strictly handling constraints. After presenting its theory for general systems and introducing tai
Externí odkaz:
http://arxiv.org/abs/2211.12628
This paper proposes a novel decision-making framework for autonomous vehicles (AVs), called predictor-corrector potential game (PCPG), composed of a Predictor and a Corrector. To enable human-like reasoning and characterize agent interactions, a rece
Externí odkaz:
http://arxiv.org/abs/2208.02835