Class information for: |
Basic class information |
| Class id | #P | Avg. number of references |
Database coverage of references |
|---|---|---|---|
| 27280 | 233 | 26.2 | 42% |
Hierarchy of classes |
The table includes all classes above and classes immediately below the current class. |
Terms with highest relevance score |
| rank | Term | termType | Chi square | Shr. of publ. in class containing term |
Class's shr. of term's tot. occurrences |
#P with term in class |
|---|---|---|---|---|---|---|
| 1 | TRAFFIC SIGN RECOGNITION | authKW | 2568623 | 12% | 70% | 28 |
| 2 | TRAFFIC SIGN DETECTION | authKW | 1384243 | 6% | 81% | 13 |
| 3 | ROAD SIGN RECOGNITION | authKW | 1321450 | 5% | 92% | 11 |
| 4 | TRAFFIC SIGN RECOGNITION TSR | authKW | 917371 | 3% | 100% | 7 |
| 5 | TRAFFIC SIGN | authKW | 587299 | 5% | 41% | 11 |
| 6 | ROAD SIGN DETECTION | authKW | 419368 | 2% | 80% | 4 |
| 7 | NEUROINFORMAT SENSORY MOTOR SYST | address | 393159 | 1% | 100% | 3 |
| 8 | TRAFFIC SIGNS RECOGNITION | authKW | 393159 | 1% | 100% | 3 |
| 9 | COMPUTER VISION BASED DRIVER ASSISTANCE | authKW | 262106 | 1% | 100% | 2 |
| 10 | INFORMAT PROD SYST IPS | address | 262106 | 1% | 100% | 2 |
Web of Science journal categories |
| Rank | Term | Chi square | Shr. of publ. in class containing term |
Class's shr. of term's tot. occurrences |
#P with term in class |
|---|---|---|---|---|---|
| 1 | Transportation Science & Technology | 8232 | 24% | 0% | 55 |
| 2 | Computer Science, Artificial Intelligence | 3053 | 30% | 0% | 70 |
| 3 | Imaging Science & Photographic Technology | 2029 | 13% | 0% | 31 |
| 4 | Engineering, Civil | 1615 | 23% | 0% | 54 |
| 5 | Remote Sensing | 1092 | 9% | 0% | 22 |
| 6 | Engineering, Electrical & Electronic | 777 | 35% | 0% | 81 |
| 7 | Geography, Physical | 639 | 9% | 0% | 21 |
| 8 | Computer Science, Theory & Methods | 438 | 12% | 0% | 29 |
| 9 | Computer Science, Interdisciplinary Applications | 307 | 10% | 0% | 24 |
| 10 | Computer Science, Cybernetics | 300 | 3% | 0% | 8 |
Address terms |
| Rank | Term | Chi square | Shr. of publ. in class containing term |
Class's shr. of term's tot. occurrences |
#P with term in class |
|---|---|---|---|---|---|
| 1 | NEUROINFORMAT SENSORY MOTOR SYST | 393159 | 1% | 100% | 3 |
| 2 | INFORMAT PROD SYST IPS | 262106 | 1% | 100% | 2 |
| 3 | AUDIO COMP | 131053 | 0% | 100% | 1 |
| 4 | CALIF PATH ATMS | 131053 | 0% | 100% | 1 |
| 5 | DIPARIMENTO FOTOMETRIA | 131053 | 0% | 100% | 1 |
| 6 | ELECT CONTROLS SYST | 131053 | 0% | 100% | 1 |
| 7 | INRETS LCPC 85 | 131053 | 0% | 100% | 1 |
| 8 | MICROSYST MACHINE VISION | 131053 | 0% | 100% | 1 |
| 9 | TEORIA SEAL COMUNICAC | 131053 | 0% | 100% | 1 |
| 10 | WASINGTON STATE TRANSPORTAT TRAC | 131053 | 0% | 100% | 1 |
Journals |
| Rank | Term | Chi square | Shr. of publ. in class containing term |
Class's shr. of term's tot. occurrences |
#P with term in class |
|---|---|---|---|---|---|
| 1 | IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS | 53112 | 12% | 2% | 27 |
| 2 | COMPUTER-AIDED CIVIL AND INFRASTRUCTURE ENGINEERING | 10863 | 3% | 1% | 8 |
| 3 | IET INTELLIGENT TRANSPORT SYSTEMS | 8856 | 3% | 1% | 6 |
| 4 | PHOTOGRAMMETRIC ENGINEERING AND REMOTE SENSING | 6072 | 5% | 0% | 12 |
| 5 | MACHINE VISION AND APPLICATIONS | 4277 | 3% | 1% | 6 |
| 6 | JOURNAL OF COMPUTING IN CIVIL ENGINEERING | 4182 | 3% | 1% | 6 |
| 7 | INTERNATIONAL JOURNAL OF INNOVATIVE COMPUTING INFORMATION AND CONTROL | 3259 | 3% | 0% | 8 |
| 8 | PHOTOGRAMMETRIC RECORD | 2441 | 1% | 1% | 3 |
| 9 | INTEGRATED COMPUTER-AIDED ENGINEERING | 2146 | 1% | 1% | 3 |
| 10 | PARABOLA-MYTH TRADITION AND THE SEARCH FOR MEANING | 2112 | 0% | 2% | 1 |
Author Key Words |
Core articles |
The table includes core articles in the class. The following variables is taken into account for the relevance score of an article in a cluster c: (1) Number of references referring to publications in the class. (2) Share of total number of active references referring to publications in the class. (3) Age of the article. New articles get higher score than old articles. (4) Citation rate, normalized to year. |
| Rank | Reference | # ref. in cl. |
Shr. of ref. in cl. |
Citations |
|---|---|---|---|---|
| 1 | GUDIGAR, A , CHOKKADI, S , RAGHAVENDRA, U , (2016) A REVIEW ON AUTOMATIC DETECTION AND RECOGNITION OF TRAFFIC SIGN.MULTIMEDIA TOOLS AND APPLICATIONS. VOL. 75. ISSUE 1. P. 333 -364 | 32 | 97% | 1 |
| 2 | BERKAYA, SK , GUNDUZ, H , OZSEN, O , AKINLAR, C , GUNAL, S , (2016) ON CIRCULAR TRAFFIC SIGN DETECTION AND RECOGNITION.EXPERT SYSTEMS WITH APPLICATIONS. VOL. 48. ISSUE . P. 67 -75 | 22 | 71% | 3 |
| 3 | BALALI, V , GOLPARVAR-FARD, M , (2016) EVALUATION OF MULTICLASS TRAFFIC SIGN DETECTION AND CLASSIFICATION METHODS FOR US ROADWAY ASSET INVENTORY MANAGEMENT.JOURNAL OF COMPUTING IN CIVIL ENGINEERING. VOL. 30. ISSUE 2. P. - | 22 | 85% | 0 |
| 4 | LIU, CS , CHANG, FL , CHEN, ZX , LIU, DM , (2016) FAST TRAFFIC SIGN RECOGNITION VIA HIGH-CONTRAST REGION EXTRACTION AND EXTENDED SPARSE REPRESENTATION.IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS. VOL. 17. ISSUE 1. P. 79 -92 | 19 | 86% | 1 |
| 5 | WEN, CL , LI, J , LUO, H , YU, YT , CAI, ZP , WANG, HY , WANG, C , (2016) SPATIAL-RELATED TRAFFIC SIGN INSPECTION FOR INVENTORY PURPOSES USING MOBILE LASER SCANNING DATA.IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS. VOL. 17. ISSUE 1. P. 27 -37 | 19 | 76% | 1 |
| 6 | YU, YT , LI, J , WEN, CL , GUAN, HY , LUO, H , WANG, C , (2016) BAG-OF-VISUAL-PHRASES AND HIERARCHICAL DEEP MODELS FOR TRAFFIC SIGN DETECTION AND RECOGNITION IN MOBILE LASER SCANNING DATA.ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING. VOL. 113. ISSUE . P. 106 -123 | 24 | 51% | 2 |
| 7 | WANG, GY , REN, GH , JIANG, LH , QUAN, TF , (2014) HOLE-BASED TRAFFIC SIGN DETECTION METHOD FOR TRAFFIC SIGNS WITH RED RIM.VISUAL COMPUTER. VOL. 30. ISSUE 5. P. 539-551 | 16 | 89% | 1 |
| 8 | AGHDAM, HH , HERAVI, EJ , PUIG, D , (2016) A PRACTICAL APPROACH FOR DETECTION AND CLASSIFICATION OF TRAFFIC SIGNS USING CONVOLUTIONAL NEURAL NETWORKS.ROBOTICS AND AUTONOMOUS SYSTEMS. VOL. 84. ISSUE . P. 97 -112 | 14 | 93% | 0 |
| 9 | PAZHOUMAND-DAR, H , YAGHOOBI, M , (2013) A NEW APPROACH IN ROAD SIGN RECOGNITION BASED ON FAST FRACTAL CODING.NEURAL COMPUTING & APPLICATIONS. VOL. 22. ISSUE 3-4. P. 615 -625 | 13 | 100% | 4 |
| 10 | HU, ZZ , BAI, DF , LI, N , (2016) GENERALIZED SIGN RECOGNITION BASED ON THE GAUSSIAN STATISTICAL COLOR MODEL FOR INTELLIGENT ROAD SIGN INVENTORY.TRANSPORTATION RESEARCH RECORD. VOL. . ISSUE 2596. P. 28 -35 | 12 | 100% | 0 |
Classes with closest relation at Level 1 |