首页|Study Data from University of Sidi Mohamed Ben Abdellah Update Understanding of Intelligent Systems (FCOSH: A novel single-head FCOS for faster object detection in autonomous-driving systems)
Study Data from University of Sidi Mohamed Ben Abdellah Update Understanding of Intelligent Systems (FCOSH: A novel single-head FCOS for faster object detection in autonomous-driving systems)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-Fresh data on intelligent systems are presented in a new report. According to news reporting from Fez, Morocco, by New sRx journalists, research stated, "In autonomous driving systems, object detecti on plays a pivotal role by facilitating their ability to perceive the surroundin g road environment effectively." The news correspondents obtained a quote from the research from University of Si di Mohamed Ben Abdellah: "Object detection's foremost challenge pertains to its real-time operational capabilities. Achieving this necessitates reducing the det ectors' computational complexity while preserving their accuracy. Nevertheless, most of the approach in object detection involves dividing image processing over multiple heads, each tasked with detecting objects at particular scales. Even t hough this approach improves detection accuracy, it adds an extra computational burden. In this study, our objective is to assess the feasibility of employing a single head within the originally multi-headed architecture of the FCOS detecto r. In response to the challenges posed by this significant modification, we prop ose a set of straightforward solutions, resulting in the development of a novel Fully Convolutional One-Stage with a Single Head (FCOSH) detector."
University of Sidi Mohamed Ben AbdellahFezMoroccoAfricaIntelligent SystemsMachine Learning
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