Name
Affiliation
Papers
MASAYUKI SHIMODA
Tokyo Institute of Technology, Tokyo, Japan
17
Collaborators
Citations 
PageRank 
12
8
6.45
Referers 
Referees 
References 
41
77
29
Title
Citations
PageRank
Year
Fpga-Based Inter-Layer Pipelined Accelerators For Filter-Wise Weight-Balanced Sparse Fully Convolutional Networks With Overlapped Tiling10.432021
Fast Monocular Depth Estimation on an FPGA00.342020
Sentei: Filter-Wise Pruning With Distillation Towards Efficient Sparse Convolutional Neural Network Accelerators00.342020
Guinness: A Gui Based Binarized Deep Neural Network Framework For Software Programmers00.342019
An FPGA-based Fine Tuning Accelerator for a Sparse CNN.10.352019
Filter-Wise Pruning Approach to FPGA Implementation of Fully Convolutional Network for Semantic Segmentation.20.532019
Power Efficient Object Detector With An Event-Driven Camera For Moving Object Surveillance On An Fpga00.342019
FPGA-Based Training Accelerator Utilizing Sparseness of Convolutional Neural Network10.362019
A Dataflow Pipelining Architecture for Tile Segmentation with a Sparse MobileNet on an FPGA00.342019
An FPGA Implementation of Real-Time Object Detection with a Thermal Camera00.342019
FPGA-based Accurate Pedestrian Detection with Thermal Camera for Surveillance System00.342019
Many Universal Convolution Cores for Ensemble Sparse Convolutional Neural Networks00.342019
A Tri-State Weight Convolutional Neural Network for an FPGA: Applied to YOLOv2 Object Detector00.342018
A Demonstration of FPGA-Based You Only Look Once Version2 (YOLOv2)00.342018
Power Efficient Object Detector With An Event-Driven Camera On An Fpga00.342018
Demonstration of Object Detection for Event-Driven Cameras on FPGAs and GPUs00.342018
All binarized convolutional neural network and its implementation on an FPGA30.722017