JP2021507345A5 - - Google Patents
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- JP2021507345A5 JP2021507345A5 JP2020530640A JP2020530640A JP2021507345A5 JP 2021507345 A5 JP2021507345 A5 JP 2021507345A5 JP 2020530640 A JP2020530640 A JP 2020530640A JP 2020530640 A JP2020530640 A JP 2020530640A JP 2021507345 A5 JP2021507345 A5 JP 2021507345A5
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- kernel
- pattern
- complementary
- sparse
- sample
- Prior art date
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- 238000000034 method Methods 0.000 claims description 8
- 230000000295 complement effect Effects 0.000 claims 18
- 239000011159 matrix material Substances 0.000 claims 15
- 238000013527 convolutional neural network Methods 0.000 claims 7
- 238000007500 overflow downdraw method Methods 0.000 claims 6
- 230000004927 fusion Effects 0.000 claims 4
- 238000004590 computer program Methods 0.000 claims 2
- 230000004044 response Effects 0.000 claims 2
- 238000004891 communication Methods 0.000 description 5
- 238000005516 engineering process Methods 0.000 description 3
- 230000002093 peripheral effect Effects 0.000 description 2
- 230000003068 static effect Effects 0.000 description 2
- 230000001360 synchronised effect Effects 0.000 description 2
- RYGMFSIKBFXOCR-UHFFFAOYSA-N Copper Chemical compound [Cu] RYGMFSIKBFXOCR-UHFFFAOYSA-N 0.000 description 1
- 230000001413 cellular effect Effects 0.000 description 1
- 229910052802 copper Inorganic materials 0.000 description 1
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- 230000009977 dual effect Effects 0.000 description 1
- 238000000802 evaporation-induced self-assembly Methods 0.000 description 1
- 239000000835 fiber Substances 0.000 description 1
- 230000006870 function Effects 0.000 description 1
- 230000005055 memory storage Effects 0.000 description 1
- 239000004065 semiconductor Substances 0.000 description 1
- 239000007787 solid Substances 0.000 description 1
Applications Claiming Priority (3)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| US15/841,480 | 2017-12-14 | ||
| US15/841,480 US10740659B2 (en) | 2017-12-14 | 2017-12-14 | Fusing sparse kernels to approximate a full kernel of a convolutional neural network |
| PCT/IB2018/059993 WO2019116291A1 (en) | 2017-12-14 | 2018-12-13 | Fusing sparse kernels to approximate a full kernel of a convolutional neural network |
Publications (3)
| Publication Number | Publication Date |
|---|---|
| JP2021507345A JP2021507345A (ja) | 2021-02-22 |
| JP2021507345A5 true JP2021507345A5 (https=) | 2021-07-26 |
| JP7179850B2 JP7179850B2 (ja) | 2022-11-29 |
Family
ID=66814568
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| JP2020530640A Active JP7179850B2 (ja) | 2017-12-14 | 2018-12-13 | 畳み込みニューラル・ネットワークの完全なカーネルを近似するためのスパース・カーネルの融合 |
Country Status (6)
| Country | Link |
|---|---|
| US (1) | US10740659B2 (https=) |
| JP (1) | JP7179850B2 (https=) |
| CN (1) | CN111344720A (https=) |
| DE (1) | DE112018006377T5 (https=) |
| GB (1) | GB2583623A (https=) |
| WO (1) | WO2019116291A1 (https=) |
Families Citing this family (11)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| KR102548718B1 (ko) * | 2017-06-07 | 2023-06-28 | 삼성전자주식회사 | 전자 장치 및 그 제어 방법 |
| US12393829B2 (en) * | 2019-07-25 | 2025-08-19 | Samsung Electronics Co., Ltd. | Methods and systems with convolutional neural network (CNN) performance |
| US11144290B2 (en) | 2019-09-13 | 2021-10-12 | Huawei Technologies Co., Ltd. | Method and apparatus for enabling autonomous acceleration of dataflow AI applications |
| US12265911B2 (en) * | 2020-02-06 | 2025-04-01 | Google Llc | Neural network layers with a controlled degree of spatial invariance |
| US12554987B2 (en) * | 2020-02-14 | 2026-02-17 | Northeastern University | Computer-implemented methods and systems for DNN weight pruning for real-time execution on mobile devices |
| US11379951B2 (en) * | 2020-03-25 | 2022-07-05 | Nintendo Co., Ltd. | Systems and methods for machine learned image conversion |
| US11494875B2 (en) | 2020-03-25 | 2022-11-08 | Nintendo Co., Ltd. | Systems and methods for machine learned image conversion |
| US12585928B2 (en) | 2020-10-05 | 2026-03-24 | Numenta, Inc. | Hardware architecture for introducing activation sparsity in neural network |
| CN113344199B (zh) * | 2021-06-17 | 2024-05-03 | 阿波罗智联(北京)科技有限公司 | 用于训练可分离卷积网络的方法、路侧设备及云控平台 |
| US20230004352A1 (en) * | 2021-07-04 | 2023-01-05 | Numenta, Inc. | Hardware architecture for processing tensors with complementary sparsity |
| US20250138820A1 (en) * | 2023-10-26 | 2025-05-01 | Etched.ai, Inc. | Model-specific asic compilation using fused kernel replacement |
Family Cites Families (12)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US9424513B2 (en) * | 2011-11-09 | 2016-08-23 | Qualcomm Incorporated | Methods and apparatus for neural component memory transfer of a referenced pattern by including neurons to output a pattern substantially the same as the referenced pattern |
| CN104077612B (zh) * | 2014-07-15 | 2017-09-22 | 中国科学院合肥物质科学研究院 | 一种基于多特征稀疏表示技术的害虫图像识别方法 |
| US9652817B2 (en) | 2015-03-12 | 2017-05-16 | Samsung Electronics Co., Ltd. | Automated compute kernel fusion, resizing, and interleave |
| CN105046193B (zh) * | 2015-06-05 | 2018-07-10 | 上海大学 | 一种基于融合稀疏表示矩阵的人体动作识别方法 |
| US9741107B2 (en) * | 2015-06-05 | 2017-08-22 | Sony Corporation | Full reference image quality assessment based on convolutional neural network |
| US9972063B2 (en) | 2015-07-30 | 2018-05-15 | International Business Machines Corporation | Pipelined approach to fused kernels for optimization of machine learning workloads on graphical processing units |
| US10380479B2 (en) | 2015-10-08 | 2019-08-13 | International Business Machines Corporation | Acceleration of convolutional neural network training using stochastic perforation |
| US9904874B2 (en) | 2015-11-05 | 2018-02-27 | Microsoft Technology Licensing, Llc | Hardware-efficient deep convolutional neural networks |
| CN108701210B (zh) | 2016-02-02 | 2021-08-17 | 北京市商汤科技开发有限公司 | 用于cnn网络适配和对象在线追踪的方法和系统 |
| US10181188B2 (en) * | 2016-02-19 | 2019-01-15 | International Business Machines Corporation | Structure-preserving composite model for skin lesion segmentation |
| US10832136B2 (en) | 2016-05-18 | 2020-11-10 | Nec Corporation | Passive pruning of filters in a convolutional neural network |
| CN107330463B (zh) | 2017-06-29 | 2020-12-08 | 南京信息工程大学 | 基于cnn多特征联合和多核稀疏表示的车型识别方法 |
-
2017
- 2017-12-14 US US15/841,480 patent/US10740659B2/en not_active Expired - Fee Related
-
2018
- 2018-12-13 WO PCT/IB2018/059993 patent/WO2019116291A1/en not_active Ceased
- 2018-12-13 JP JP2020530640A patent/JP7179850B2/ja active Active
- 2018-12-13 CN CN201880072812.3A patent/CN111344720A/zh active Pending
- 2018-12-13 DE DE112018006377.1T patent/DE112018006377T5/de active Pending
- 2018-12-13 GB GB2010475.8A patent/GB2583623A/en not_active Withdrawn
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