In this paper, we propose vehicle detection and classification in a real road environment using modified improved AlexNet. Among the various challenges faced, problem of poor robustness extracting candidate regions through single feature is solved YOLO deep learning series algorithm used to potential further improve speed detection. For this, lightweight network Yolov2-tiny chosen as location n...

Obtaining road surface information to make the vehicle run in best condition can not only reduce energy consumption and loss, but also improve driving safety. In this paper, specific car body was preprocessed as root mean square value, SVM offline training used. The recognition rate of off-road highway reach 98%. Compared with traditional threshold recognition, has better adaptability robustnes...

In recent decades, many government agencies and famous universities are researching the intelligent traffic video monitoring system. According to the tunnel monitoring video, this paper uses the combination of background subtraction method and three frame differencing method for moving vehicle detection , and designs the geometric parameters and combined parameters for vehicle classification, f...

The paper presents a method of terrain classification and path planning for unmanned ground vehicles. The terrain classification is done on imagery that is acquired from UAV (unmanned aerial vehicle) or satellite and is used for UGV (unmanned ground vehicle) path planning thus introducing collaboration capabilities to the system of two. The system complements the UGV on-board navigation system ...