ã€Global Science and Technology Report】On May 18th, the global record of KITTI, the world's authoritative machine vision algorithm evaluation platform, was refreshed. Alibaba, a technology company from China, has increased the accuracy of its vehicle testing to 90.46%. Vehicle inspection is considered to be a key technology for implementing unmanned driving and is extremely challenging. (The Ai Baba iDST team won the KITTI ranking with the accuracy of 90.46%) It is understood that this major technological breakthrough was completed by the team led by Hua Xiansheng, a researcher of visual computing at Alibaba.com. They proposed a multi-task deep neural network based on regional fusion decision-making and context correlation for vehicle detection tasks in complex scenarios, focusing on solving multiple perspectives, multiple attitudes, and vehicle occlusion issues. In the network structure design, the team used deconvolution operations to improve the recall rate of small targets. At the same time, the team spliced ​​multi-layer features to fuse low-level local information and high-level semantic information, which improved the accuracy of frame positioning. In the training process, it also draws on the confrontation training model in GAN (Generation Counter-Network). Hua Xiansheng said, "Now we have integrated this technology into Alibaba Cloud ET and applied it in the city brain. It can help the city brain to accurately understand traffic information and quickly make global judgments." Hua Xiansheng is an international authoritative scholar in the field of visual identification and search. He was elected IEEE Fellow (IEEE Fellow) and ACM Outstanding Scientist of the American Computer Association. The city brain is a project initiated by 13 companies, including Alibaba Cloud, in conjunction with the Hangzhou Municipal Government. It aims to build a city-level artificial intelligence hub to enable cities to interact with humans in a friendly manner. This analysis video is the key to the city's brain to obtain information. Take traffic management as an example. Through this technology, the city’s brain can sense the running status and trajectory of vehicles under complex road conditions through ordinary cameras, and analyze these data in real time. Based on this, a variety of intelligent traffic optimizations are performed. On the scale of video data processing, it is rare in the world. Continuous hard work in the field of visual computing is part of the Alibaba NASA program. The program focuses on core areas such as machine learning, chips, IoT, operating systems, and biometrics. They hope to solve the difficulties of 10 years and 20 years. Previously, significant progress has been made in light quantum computers, full-immersion liquid cooling servers, and so on. KITTI is currently the world's largest computer vision algorithm evaluation data set under autopilot scenarios and can be used to evaluate the performance of computer vision technologies such as target detection in complex real environments. KITTI contains real image data collected from scenes such as urban areas, rural areas, and highways. There are a large number of small targets, underexposure and overexposure, multiple perspective changes, and various occlusion conditions.
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