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  • Ký hiệu PL/XG: 629.283
    Nhan đề: Pedestrian Activity Prediction Based On Semantic Segmentation and Hybrid Of Machines /
DDC 629.283
Tác giả CN Diem, Phuc Tran
Nhan đề Pedestrian Activity Prediction Based On Semantic Segmentation and Hybrid Of Machines / Diem Phuc Tran, Van Dung Hoang, Tri Cong Pham, Chi Mai Luong
Mô tả vật lý 13 p.
Tóm tắt The article presents an advanced driver assistance. system (ADAS) based on a situational recognition solution and provides alert levels in the context of actual traffic. The solution is a process in which a single image is segmented to detect pedestrians position as well as extract features of pedestrian posture to predict the action. The main purpose of this process is to improve accuracy and provide warning levels, which supports autonomous vehicle navigation to avoid collisions the process of the situation prediction and issuing of warning levels consists of two phases: Segmenting in order to definite the located pedestrians and other objects in traffic environment . Judging the situation according to the position and posture of pedestrians in traffic. The accuracy rate of the action prediction is 99.59% and the speed is 5 frames per second
Từ khóa tự do Xe tự hành
Từ khóa tự do Vận hành xe
Từ khóa tự do Autonomous vehicle
Từ khóa tự do Feature extraction
Từ khóa tự do Pedestrian recognition
Từ khóa tự do Semantic segmentation.
Tác giả(bs) CN Chi, Mai Lương
Tác giả(bs) CN Tri, Cong Pham
Tác giả(bs) CN Van, Dung Hoang
Nguồn trích Tạp chí Tin học và Điều khiển học = Journal of Computer Science And Cybernetics 2018Page 113 - 125 Số: 02 Tập: 34
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082 |a629.283
100 |aDiem, Phuc Tran
245 |aPedestrian Activity Prediction Based On Semantic Segmentation and Hybrid Of Machines / |cDiem Phuc Tran, Van Dung Hoang, Tri Cong Pham, Chi Mai Luong
300 |a13 p.
520 |aThe article presents an advanced driver assistance. system (ADAS) based on a situational recognition solution and provides alert levels in the context of actual traffic. The solution is a process in which a single image is segmented to detect pedestrians position as well as extract features of pedestrian posture to predict the action. The main purpose of this process is to improve accuracy and provide warning levels, which supports autonomous vehicle navigation to avoid collisions the process of the situation prediction and issuing of warning levels consists of two phases: Segmenting in order to definite the located pedestrians and other objects in traffic environment . Judging the situation according to the position and posture of pedestrians in traffic. The accuracy rate of the action prediction is 99.59% and the speed is 5 frames per second
653 |aXe tự hành
653 |a Vận hành xe
653 |aAutonomous vehicle
653 |aFeature extraction
653 |aPedestrian recognition
653 |aSemantic segmentation.
700 |aChi, Mai Lương
700 |aTri, Cong Pham
700 |aVan, Dung Hoang
773 |tTạp chí Tin học và Điều khiển học = Journal of Computer Science And Cybernetics |d2018|gPage 113 - 125|v34|i02
890|c0|a0|b0|d0
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