Automatic road sign detecion and classification based on support vector machines and HOG descriptos

10 citations as recorded by crossref.

1. The Method of Classifying Fog Level of Outdoor Video Images Based on Convolutional Neural Networks X. Zhao et al. 10.1007/s12524-021-01387-6
2. Hardware implementation and validation of a traffic road sign detection and identification system R. Hmida et al. 10.1007/s11554-016-0579-x
3. A Review on Progress in Semantic Image Segmentation and Its Application to Medical Images M. Kar et al. 10.1007/s42979-021-00784-5
4. Feature selection using Ant Colony Optimization (ACO) and Road Sign Detection and Recognition (RSDR) system A. Jayaprakash & C. KeziSelvaVijila 10.1016/j.cogsys.2019.04.002
5. Interactive urban route evaluation system for smart electromobility L. Curiel-Ramirez et al. 10.1007/s12008-020-00708-2
6. A Fusion Approach to Detect Traffic Signs Using Registered Color Images and Noisy Airborne LiDAR Data M. Javanmardi et al. 10.3390/app11010309
7. Traffic sign extraction using deep hierarchical feature learning and mobile light detection and ranging (LiDAR) data on rural highways M. Gouda et al. 10.1080/15472450.2022.2074792
8. CIRCULAR TRAFFIC SIGN CLASSIFICATION USING HOG BASED RING PARTITIONED MATCHING A. Soetedjo & I. Somawirata 10.21307/ijssis-2017-232
9. Robust Traffic-Sign Detection and Classification Using Mobile LiDAR Data With Digital Images H. Guan et al. 10.1109/JSTARS.2018.2810143
10. Automatic Segmentation and Shape-Based Classification of Retro-Reflective Traffic Signs from Mobile LiDAR Data B. Riveiro et al. 10.1109/JSTARS.2015.2461680