Application of Convolutional Neural Network to Predict Anisotropic Effective Thermal Conductivity of Semiconductor Package-Reference-Cited by-同舟云学术

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Application of Convolutional Neural Network to Predict Anisotropic Effective Thermal Conductivity of Semiconductor Package

Published:2022 Issue: Volume:10 Page:51995-52007
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Kim Tae-Hyun¹^ORCID,Park Jeong-Hyeon²^ORCID,Jung Ki Wook³,Kim Jaechoon³,Lee Eun-Ho¹^ORCID

Affiliation:

1. Department of Smart Fab. Technology, Sungkyunkwan University, Suwon, Republic of Korea

2. Department of Mechanical Engineering, Sungkyunkwan University, Suwon, Republic of Korea

3. Division of Test and System Package, Samsung Electronics, Hwaseong, Republic of Korea

Funder

Test and System Package (TSP) Division, Samsung Electronics Company Ltd

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Engineering,General Materials Science,General Computer Science,Electrical and Electronic Engineering

Link

http://xplorestaging.ieee.org/ielx7/6287639/9668973/09774413.pdf?arnumber=9774413

Reference52 articles.

1. Novel Convolutional Neural Network (NCNN) for the Diagnosis of Bearing Defects in Rotary Machinery

2. Convolutional neural network: a review of models, methodologies and applications to object detection

3. A quick PCB thermal calculator to aid system design of exposed pad packages

4. THE EFFECTIVE THERMAL CONDUCTIVITY OF PACKED BEDS OF SPHERES FOR A FINITE CONTACT AREA

5. COMPUTATION OF THE EFFECTIVE CONDUCTIVITY OF UNIDIRECTIONAL FIBROUS COMPOSITES WITH AN INTERFACIAL THERMAL RESISTANCE

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