2018 IEEE Symposium on VLSI Technology最新文献_第2页

Ultrahigh-Sensitive and CMOS Compatible ISFET Developed in BEOL of Industrial UTBB FDSOI 在工业UTBB FDSOI的BEOL中开发了超高灵敏度和CMOS兼容的ISFET

2018 IEEE Symposium on VLSI Technology Pub Date : 2018-06-01 DOI: 10.1109/VLSIT.2018.8510686

G. Ayele, S. Monfray, S. Ecoffey, F. Boeuf, R. Bon, J. Cloarec, D. Drouin, A. Souifi

引用次数: 5

Improving Performance, Power, and Area by Optimizing Gear Ratio of Gate-Metal Pitches in Sub-10nm Node CMOS Designs 通过优化亚10nm节点CMOS栅极-金属节的齿轮传动比来提高性能、功率和面积

2018 IEEE Symposium on VLSI Technology Pub Date : 2018-06-01 DOI: 10.1109/VLSIT.2018.8510670

Y. Ban, Xuelian Zhu, J. Petykiewicz, J. Zeng

引用次数: 3

Si/SiGe superlattice I/O finFETs in a vertically-stacked Gate-All-Around horizontal Nanowire Technology 垂直堆叠栅极-全方位水平纳米线技术中的Si/SiGe超晶格I/O finfet

2018 IEEE Symposium on VLSI Technology Pub Date : 2018-06-01 DOI: 10.1109/VLSIT.2018.8510654

G. Hellings, H. Mertens, A. Subirats, E. Simoen, T. Schram, L. Ragnarsson, Marko Simicic, S.-H. Chen, B. Parvais, D. Boudier, B. Crețu, J. Machillot, V. Peña, S. Sun, N. Yoshida, N. Kim, A. Mocuta, D. Linten, N. Horiguchi

引用次数: 11

Next-generation Fundus Camera with Full Color Image Acquisition in 0-lx Visible Light by 1.12-micron Square Pixel, 4K, 30-fps BSI CMOS Image Sensor with Advanced NIR Multi-spectral Imaging System 采用1.12微米平方像素、4K、30帧/秒的BSI CMOS图像传感器和先进的近红外多光谱成像系统，实现0-lx可见光全彩色图像采集的下一代眼底相机

2018 IEEE Symposium on VLSI Technology Pub Date : 2018-06-01 DOI: 10.1109/VLSIT.2018.8510698

H. Sumi, H. Takehara, Shunsuke Miyazaki, Daiki Shirahige, K. Sasagawa, T. Tokuda, Yoshihiro Watanabe, N. Kishi, J. Ohta, M. Ishikawa

{"title":"Next-generation Fundus Camera with Full Color Image Acquisition in 0-lx Visible Light by 1.12-micron Square Pixel, 4K, 30-fps BSI CMOS Image Sensor with Advanced NIR Multi-spectral Imaging System","authors":"H. Sumi, H. Takehara, Shunsuke Miyazaki, Daiki Shirahige, K. Sasagawa, T. Tokuda, Yoshihiro Watanabe, N. Kishi, J. Ohta, M. Ishikawa","doi":"10.1109/VLSIT.2018.8510698","DOIUrl":"https://doi.org/10.1109/VLSIT.2018.8510698","url":null,"abstract":"This paper presents a near-infrared (NIR) multi-spectral imaging system, which can be applied to a CMOS image sensor with fine pixels. Using the multi-spectral technology, NIR1: near 800 nm, NIR2: 870 nm, and NIR3: 940 nm in the NIR wavelength were acquired for a target image. Using this image sensor and imaging system and with the application of interpolation and color correction processing, a color image is reproduced by only multi-NIR signal without visible light (0 lx). We also developed a next-generation fundus camera, which employed this multi-spectral imaging system with a multi-NIR LED illuminator. This multi-NIR LED illumination system, which was also developed, is designed to emit light with high efficiency despite its size of 2.3 mm square in size. We applied this NIR multi-spectral camera module with the multi-NIR LED illuminator to the next-generation fundus camera; the retinal pigment appears progressively more transparent, revealing the underlying choroid.","PeriodicalId":6561,"journal":{"name":"2018 IEEE Symposium on VLSI Technology","volume":"275 1","pages":"163-164"},"PeriodicalIF":0.0,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84555025","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 5

Embedded STT-MRAM in 28-nm FDSOI Logic Process for Industrial MCU/IoT Application 用于工业MCU/物联网应用的28nm FDSOI逻辑工艺中的嵌入式STT-MRAM

2018 IEEE Symposium on VLSI Technology Pub Date : 2018-06-01 DOI: 10.1109/VLSIT.2018.8510623

Yong Kyu Lee, Yoonjong Song, Joochan Kim, Sechung Oh, B. Bae, SangHumn Lee, Junghyuk Lee, U. Pi, B. Seo, H. Jung, Kilho Lee, Hyunchul Shin, H. Jung, Mark Pyo, A. Antonyan, Daesop Lee, Sohee Hwang, D. Jang, Yongsung Ji, Seungbae Lee, Jung-Pil Lim, K. Koh, K. Hwang, H. Hong, K. Park, G. Jeong, J. Yoon, E. Jung

引用次数: 43

A Near- & Short-Wave IR Tunable InGaAs Nanomembrane PhotoFET on Flexible Substrate for Lightweight and Wide-Angle Imaging Applications 用于轻量化和广角成像应用的柔性衬底上的近短波红外可调谐InGaAs纳米膜光电场效应晶体管

2018 IEEE Symposium on VLSI Technology Pub Date : 2018-06-01 DOI: 10.1109/VLSIT.2018.8510702

Yida Li, A. Alian, Li Huang, K. Ang, D. Lin, D. Mocuta, N. Collaert, A. Thean

引用次数: 1

Shaping circuit environment to face the thermal challenge Innovative technologies from low to high power electronics 从低功率到高功率电子产品的创新技术

2018 IEEE Symposium on VLSI Technology Pub Date : 2018-06-01 DOI: 10.1109/VLSIT.2018.8510677

P. Coudrain, J. Colonna, L. Collin, R. Prieto, L. Fréchette, J. Barrau, G. Savelli, P. Vivet, Q. Struss, J. Widiez, K. Vladimirova, K. Triantopoulos, H. Beckrich-Ros, M. Vilarrubí, G. Laguna, H. Azarkish, M. Shirazi, J. Michailos

引用次数: 1

Response Speed of Negative Capacitance FinFETs 负电容finfet的响应速度

2018 IEEE Symposium on VLSI Technology Pub Date : 2018-06-01 DOI: 10.1109/VLSIT.2018.8510626

D. Kwon, Y. Liao, Yen-Kai Lin, J. Duarte, K. Chatterjee, A. Tan, A. Yadav, C. Hu, Z. Krivokapic, S. Salahuddin

引用次数: 28

8LPP Logic Platform Technology for Cost-Effective High Volume Manufacturing 8LPP逻辑平台技术，用于高成本效益的大批量生产

2018 IEEE Symposium on VLSI Technology Pub Date : 2018-06-01 DOI: 10.1109/VLSIT.2018.8510673

H. Rhee, Ilryong Kim, Jaehun Jeong, Nakjin Son, Heebum Hong, Sungil Cho, Yongsoon Park, Dongwoo Kim, Yunki Choi, Jeonghoon Ahn, S. Kang, K. Yeo, Jungtae Kim, Euncheol Lee, J. Youn, J. Yoon

引用次数: 8

An Energy Efficient FinFET-based Field Programmable Synapse Array (FPSA) Feasible for One-shot Learning on EDGE AI 一种基于finfet的现场可编程突触阵列(FPSA)，可用于EDGE AI的一次学习

2018 IEEE Symposium on VLSI Technology Pub Date : 2018-06-01 DOI: 10.1109/VLSIT.2018.8510706

J. L. Kuo, H. W. Chen, E. Hsieh, S. Chung, T. P. Chen, S. A. Huang, J. Chen, O. Cheng

{"title":"An Energy Efficient FinFET-based Field Programmable Synapse Array (FPSA) Feasible for One-shot Learning on EDGE AI","authors":"J. L. Kuo, H. W. Chen, E. Hsieh, S. Chung, T. P. Chen, S. A. Huang, J. Chen, O. Cheng","doi":"10.1109/VLSIT.2018.8510706","DOIUrl":"https://doi.org/10.1109/VLSIT.2018.8510706","url":null,"abstract":"A pure logic 14nm FinFET with capabilities of linearly tunable Vth and excellent retention has been implemented as synapses in neuromorphic system. For the first time, a Field Programmable Synapse Array (FPSA) has been adopted to replace conventional R-based memory Synapse Array (RSA). Thanks to the wide range of Vt-tuning ability, 200X on/off ratio, and the ultra-small variability, 12%, results showed that the training power and SN ratio of FPSA are 10 times and 50 times smaller than those of the RSA, respectively. Two applications were demonstrated on FPSA array for one-shot learning applications. First, FPSA is used to detect handwritten digits of MNIST dataset. \"Learned it by once\" can be achieved in this task. Furthermore, FPSA has been applied to recognize goldfish in Cifar 100 dataset after learned the other 4 fish species. With the assistance from one-shot learning, results show the machine learned it faster and better on EDGE. This demonstrates the feasibility of FPSA for low-power and cost-effective synapse-based one-shot learning applications in the AIoT era.","PeriodicalId":6561,"journal":{"name":"2018 IEEE Symposium on VLSI Technology","volume":"69 1-3 1","pages":"29-30"},"PeriodicalIF":0.0,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77934584","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1