Development of a Testbed for Automatic Target Recognition and Object Change Tracking

Ihita, Gangavarapu Vigneswara; Duddu, Vijay Rao

doi:10.1007/978-3-030-52190-5_14

Cited by 1 publication

(1 citation statement)

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“…Document [52] is based on various operations in image improvement, gray scale transformation, bilateral filtering edge detection, and obtaining license plates from vehicle images. The literature [53] employs MobileNet-SSD based on the deep neural network algorithm to process the frames captured by the onboard sensor for objective recognition. The classification recognition algorithm based on the neural network is a classification method proposed for the simulation of the physiological tissue structure of the human brain.…”

Section: Multisensor Fusion/resultsmentioning

confidence: 99%

[Retracted] Sensor‐Based Environmental Perception Technology for Intelligent Vehicles

et al. 2021

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Environmental perception technology is the basis and premise of intelligent vehicle decision control of intelligent vehicles, a crucial link of intelligent vehicles to realize intelligence, and also the basic guarantee of its safety and intelligence. The accuracy and robustness of the perception algorithm will directly affect or even determine the realization of the upper function of intelligent vehicles. The wrong environmental perception will affect the control of the vehicle, thus causing safety risks. This paper discusses the intelligent vehicle perception technology and introduces the development status and control strategies of several important sensors such as machine vision, laser radar, and millimeter-wave radar. Target detection, target recognition, and multisensor fusion are analyzed in the optimized part of sensor results. The functions of the intelligent vehicle assistance system which has been applied to the ground at present are described, and the lane detection, adaptive cruise control (ACC), and autonomous emergency braking (AEB) are analyzed. Finally, the paper looks forward to the research direction of sense-based intelligent vehicle perception technology, which will play an important role in guiding the development of intelligent vehicles and accelerate the landing process of intelligent vehicles.

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Section: Multisensor Fusion/resultsmentioning

confidence: 99%