Embedded Compression for Embedded Intelligent Vision & Video System
用于嵌入式智能视觉的嵌入式压缩
基本信息
- 批准号:17J10477
- 负责人:
- 金额:$ 1.09万
- 依托单位:
- 依托单位国家:日本
- 项目类别:Grant-in-Aid for JSPS Fellows
- 财政年份:2017
- 资助国家:日本
- 起止时间:2017-04-26 至 2019-03-31
- 项目状态:已结题
- 来源:
- 关键词:
项目摘要
Nowadays, video coding and computer vision algorithms are widely applied in mobile devices, such as smartphones and wireless sensor networks. While many of these devices are battery powered or even battery-less, a low energy consumption is crucial. In this research, I focus on reducing the dominant energy consumption of DRAM access by embedded compression.DRAM access power is proportional to its volume, so it can be reduced by compressing data before storing them to DRAM and decompressing data after fetched back. Hence, I researched on the embedded compression for embedded video and vision systems.In this year, I mainly focus on reducing the size of deep convolutional neural networks based on pruning, quantization and encoding, and submitted one journal paper.
目前,视频编码和计算机视觉算法广泛应用于智能手机和无线传感器网络等移动的设备中。虽然这些设备中有许多是电池供电的,甚至是无电池的,但低能耗至关重要。在这项研究中,我专注于减少DRAM访问的主要能源消耗嵌入式压缩,DRAM的访问功率成正比的体积,所以它可以通过压缩数据存储到DRAM和解压后取回数据来减少。因此,我研究了嵌入式视频和视觉系统的嵌入式压缩。今年,我主要关注基于修剪,量化和编码的深度卷积神经网络的规模缩小,并提交了一篇期刊论文。
项目成果
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
Low Cost Approximate Multiplier Design using Probability Driven Inexac t Compressors
使用概率驱动不精确压缩机的低成本近似乘法器设计
- DOI:
- 发表时间:2018
- 期刊:
- 影响因子:0
- 作者:Yi Guo;Heming Sun;Li Guo;Shinji Kimura
- 通讯作者:Shinji Kimura
Framework and VLSI Architecture of Measurement-Domain Intra Prediction for Compressively Sensed Visual Contents
- DOI:10.1587/transfun.e100.a.2869
- 发表时间:2017-12
- 期刊:
- 影响因子:0
- 作者:Jian-Bin Zhou;Dajiang Zhou;Li Guo;T. Yoshimura;S. Goto
- 通讯作者:Jian-Bin Zhou;Dajiang Zhou;Li Guo;T. Yoshimura;S. Goto
Measurement-domain intra prediction framework for compressively sensed images
- DOI:10.1109/iscas.2017.8050262
- 发表时间:2017-09
- 期刊:
- 影响因子:0
- 作者:Jian-Bin Zhou;Dajiang Zhou;Li Guo;T. Yoshimura;S. Goto
- 通讯作者:Jian-Bin Zhou;Dajiang Zhou;Li Guo;T. Yoshimura;S. Goto
Lossy Compression for Embedded Computer Vision Systems
- DOI:10.1109/access.2018.2852809
- 发表时间:2018-01-01
- 期刊:
- 影响因子:3.9
- 作者:Guo, Li;Zhou, Dajiang;Goto, Satoshi
- 通讯作者:Goto, Satoshi
Distortion Control and Optimization for Lossy Embedded Compression in Video Codec System
视频编解码系统中有损嵌入式压缩的失真控制和优化
- DOI:10.1587/transfun.e100.a.2416
- 发表时间:2017
- 期刊:
- 影响因子:0
- 作者:Li Guo;Dajiang Zhou;Shinji Kimura;and Satoshi Goto
- 通讯作者:and Satoshi Goto
{{
item.title }}
{{ item.translation_title }}
- DOI:
{{ item.doi }} - 发表时间:
{{ item.publish_year }} - 期刊:
- 影响因子:{{ item.factor }}
- 作者:
{{ item.authors }} - 通讯作者:
{{ item.author }}
数据更新时间:{{ journalArticles.updateTime }}
{{ item.title }}
- 作者:
{{ item.author }}
数据更新时间:{{ monograph.updateTime }}
{{ item.title }}
- 作者:
{{ item.author }}
数据更新时间:{{ sciAawards.updateTime }}
{{ item.title }}
- 作者:
{{ item.author }}
数据更新时间:{{ conferencePapers.updateTime }}
{{ item.title }}
- 作者:
{{ item.author }}
数据更新时间:{{ patent.updateTime }}
郭 栗其他文献
郭 栗的其他文献
{{
item.title }}
{{ item.translation_title }}
- DOI:
{{ item.doi }} - 发表时间:
{{ item.publish_year }} - 期刊:
- 影响因子:{{ item.factor }}
- 作者:
{{ item.authors }} - 通讯作者:
{{ item.author }}
相似海外基金
Development of Low Power Consumption Multiferroic Memory using Experimental and Computational Approaches
使用实验和计算方法开发低功耗多铁存储器
- 批准号:
23KJ0919 - 财政年份:2023
- 资助金额:
$ 1.09万 - 项目类别:
Grant-in-Aid for JSPS Fellows
Microscale enabled advanced flow and heat transfer technologies featuring high performance and low power consumption; Acronym: Micro-FloTec
微尺度实现了高性能、低功耗的先进流动和传热技术;
- 批准号:
EP/Y004973/1 - 财政年份:2023
- 资助金额:
$ 1.09万 - 项目类别:
Research Grant
Micro-FloTec: Microscale enabled advanced flow and heat transfer technologies featuring high performance and low power consumption
Micro-FloTec:Microscale 支持先进的流动和传热技术,具有高性能和低功耗的特点
- 批准号:
EP/X038319/1 - 财政年份:2023
- 资助金额:
$ 1.09万 - 项目类别:
Research Grant
Research and Development of Ultra-Low Power Consumption IoT Systems
超低功耗物联网系统研发
- 批准号:
23K11063 - 财政年份:2023
- 资助金额:
$ 1.09万 - 项目类别:
Grant-in-Aid for Scientific Research (C)
SBIR Phase I: Ultra-low loss beamformer and combiner-first technology for lower power, consumption phased arrays
SBIR 第一阶段:超低损耗波束形成器和组合器优先技术,用于降低功耗、消耗相控阵
- 批准号:
2335496 - 财政年份:2023
- 资助金额:
$ 1.09万 - 项目类别:
Standard Grant
Next-generation memory analysis and evaluation technology using statistical electrical measurement with ultra-low power consumption, short processing time, and low cost
采用统计电学测量的下一代内存分析评估技术,具有超低功耗、处理时间短、成本低的特点
- 批准号:
23K13372 - 财政年份:2023
- 资助金额:
$ 1.09万 - 项目类别:
Grant-in-Aid for Early-Career Scientists
Market assessment of an Spiking Neuron Implementation in Digital Hardware using a Sampling-Based Approach for Reduced Power Consumption
使用基于采样的方法降低功耗,对数字硬件中的尖峰神经元实现进行市场评估
- 批准号:
576556-2022 - 财政年份:2022
- 资助金额:
$ 1.09万 - 项目类别:
Idea to Innovation
Utilizing Run-Time Reconfiguration to Reduce the Static Power Consumption of FPGAs for Mobile Applications
利用运行时重新配置来降低移动应用 FPGA 的静态功耗
- 批准号:
RGPIN-2017-04405 - 财政年份:2022
- 资助金额:
$ 1.09万 - 项目类别:
Discovery Grants Program - Individual
Development and proof of a 4 K cryocooler that achieves both low power consumption and high efficiency
实现低功耗和高效率的 4K 制冷机的开发和验证
- 批准号:
22K04058 - 财政年份:2022
- 资助金额:
$ 1.09万 - 项目类别:
Grant-in-Aid for Scientific Research (C)