Research Output per year
Fingerprint Fingerprint is based on mining the text of the person's scientific documents to create an index of weighted terms, which defines the key subjects of each individual researcher.
- 4 Similar Profiles
Lighting
Engineering & Materials Science
Particle swarm optimization (PSO)
Engineering & Materials Science
Neural networks
Engineering & Materials Science
Pixels
Engineering & Materials Science
Gabor filters
Engineering & Materials Science
Experiments
Engineering & Materials Science
Electric vehicles
Engineering & Materials Science
Convolution
Engineering & Materials Science
Network
Recent external collaboration on country level. Dive into details by clicking on the dots.
Research Output 2014 2019
Automatic Training Data Generation Method for Pixel-Level Road Lane Segmentation
Pan, X., Wu, Y. & Ogai, H., 2019 Jan 1, Genetic and Evolutionary Computing - Proceedings of the 12th International Conference on Genetic and Evolutionary Computing, 2018. Tseng, S-P., Sui, B., Pan, J-S. & Lin, J. C-W. (eds.). Springer-Verlag, p. 473-481 9 p. (Advances in Intelligent Systems and Computing; vol. 834).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
Pixels
Semantics
Personnel
Neural networks
Experiments
Fast lane detection based on deep convolutional neural network and automatic training data labeling
Pan, X. & Ogai, H., 2019 Mar 1, In : IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences. E102A, 3, p. 566-575 10 p.Research output: Contribution to journal › Article
Lane Detection
Convolution
Labeling
Computer vision
Pixels
1
Citation
(Scopus)
Fast road detection based on a dual-stage structure
Pan, X., Si, W. & Ogai, H., 2017 Feb 18, Proceedings of 2017 9th International Conference on Computer and Automation Engineering, ICCAE 2017. Association for Computing Machinery, Vol. Part F127852. p. 155-162 8 p.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
Hough transforms
Experiments
Real-time daylight modeling method for lighting systems based on RBFNN
Si, W., Pan, X. & Ogai, H., 2017 Feb 18, Proceedings of 2017 9th International Conference on Computer and Automation Engineering, ICCAE 2017. Association for Computing Machinery, Vol. Part F127852. p. 318-325 8 p.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
Lighting
Control systems
Sensors
Energy conservation
A novel lambertian-RBFNN for office light modeling
Si, W., Pan, X., Ogai, H. & Hirai, K., 2016 Jul 1, In : IEICE Transactions on Information and Systems. E99D, 7, p. 1742-1752 11 p.Research output: Contribution to journal › Article
Lighting
Neural networks
Electric lamps
Neurons
Splines