| A random forest using a multi-valued decision diagram on an FPGA H Nakahara, A Jinguji, S Sato, T Sasao 2017 IEEE 47th international symposium on multiple-valued logic (ISMVL), 266-271, 2017 | 47 | 2017 |
| FPGA-based training accelerator utilizing sparseness of convolutional neural network H Nakahara, Y Sada, M Shimoda, K Sayama, A Jinguji, S Sato 2019 29th International Conference on Field Programmable Logic and …, 2019 | 28 | 2019 |
| An acceleration of a random forest classification using Altera SDK for OpenCL H Nakahara, A Jinguji, T Fujii, S Sato 2016 International Conference on Field-Programmable Technology (FPT), 289-292, 2016 | 20 | 2016 |
| An FPGA Realization of a Random Forest with k-Means Clustering Using a High-Level Synthesis Design A Jinguji, S Sato, H Nakahara IEICE TRANSACTIONS on Information and Systems 101 (2), 354-362, 2018 | 18 | 2018 |
| An FPGA Realization of OpenPose Based on a Sparse Weight Convolutional Neural Network A Jinguji, T Fujii, S Sato, H Nakahara 2018 International Conference on Field-Programmable Technology (FPT), 310-313, 2018 | 13 | 2018 |
| An FPGA-based fine tuning accelerator for a sparse CNN H Nakahara, A Jinguji, M Shimoda, S Sato Proceedings of the 2019 ACM/SIGDA International Symposium on Field …, 2019 | 11 | 2019 |
| Fast monocular depth estimation on an FPGA Y Sada, N Soga, M Shimoda, A Jinguji, S Sato, H Nakahara 2020 IEEE International Parallel and Distributed Processing Symposium …, 2020 | 7 | 2020 |
| A dataflow pipelining architecture for tile segmentation with a sparse MobileNet on an FPGA Y Sada, M Shimoda, A Jinguji, H Nakahara 2019 International Conference on Field-Programmable Technology (ICFPT), 267-270, 2019 | 7 | 2019 |
| Real-time multi-pedestrian detection in surveillance camera using fpga A Jinguji, Y Sada, H Nakahara 2019 29th International Conference on Field Programmable Logic and …, 2019 | 7 | 2019 |
| Evaluation of convolutional neural network for fast extreme ultraviolet lithography simulation using imec 3 nm node mask patterns H Tanabe, A Jinguji, A Takahashi Journal of Micro/Nanopatterning, Materials, and Metrology 22 (2), 024201-024201, 2023 | 5 | 2023 |
| Accelerating extreme ultraviolet lithography simulation with weakly guiding approximation and source position dependent transmission cross coefficient formula H Tanabe, A Jinguji, A Takahashi Journal of Micro/Nanopatterning, Materials, and Metrology 23 (1), 014201-014201, 2024 | 3 | 2024 |
| A multilayer perceptron training accelerator using systolic array T Senoo, A Jinguji, R Kuramochi, H Nakahara 2021 IEEE Asia Pacific Conference on Circuit and Systems (APCCAS), 77-80, 2021 | 3 | 2021 |
| Weight sparseness for a feature-map-split-cnn toward low-cost embedded fpgas A Jinguji, S Sato, H Nakahara IEICE TRANSACTIONS on Information and Systems 104 (12), 2040-2047, 2021 | 2 | 2021 |
| R2CNN: recurrent residual convolutional neural network on FPGA H Nakahara, Q Zhiqiang, A Jinguji, W Luk Proceedings of the 2020 ACM/SIGDA International Symposium on Field …, 2020 | 2 | 2020 |
| Accelerating EUV lithography simulation with weakly guiding approximation and STCC formula H Tanabe, A Jinguji, A Takahashi International Conference on Extreme Ultraviolet Lithography 2023 12750, 107-114, 2023 | 1 | 2023 |
| Evaluation of CNN for fast EUV lithography simulation using iN3 logic mask patterns H Tanabe, A Jinguji, A Takahashi DTCO and Computational Patterning II 12495, 335-341, 2023 | 1 | 2023 |
| Multilayer Perceptron Training Accelerator Using Systolic Array T Senoo, A Jinguji, R Kuramochi, H Nakahara IEICE TRANSACTIONS on Information and Systems 105 (12), 2048-2056, 2022 | 1 | 2022 |
| Tiny on-chip memory realization of weight sparseness split-CNNs on low-end FPGAs A Jinguji, S Sato, H Nakahara 2020 IEEE 28th Annual International Symposium on Field-Programmable Custom …, 2020 | 1 | 2020 |
| Weakly guiding approximation of a three-<? TeX\break?> dimensional waveguide model for extreme ultraviolet lithography simulation H Tanabe, A Jinguji, A Takahashi Journal of the Optical Society of America A 41 (8), 1491-1499, 2024 | | 2024 |
| Pre-training CNN for fast EUV lithography simulation including M3D effects H Tanabe, A Jinguji, A Takahashi DTCO and Computational Patterning III 12954, 112-117, 2024 | | 2024 |
Hiroki NakaharaProfessor, Tohoku UniversityVerified email at tohoku.ac.jp
