Ensemble Learning strategy in modeling of future generation nanoscale devices using Machine Learning-Reference-Cited by-同舟云学术

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Ensemble Learning strategy in modeling of future generation nanoscale devices using Machine Learning

Published:2023-04-07 Issue: Volume: Page:
ISSN:
Container-title:2023 IEEE Devices for Integrated Circuit (DevIC)
language:
Short-container-title:

Author:

Ghoshhajra Rachita¹,Biswas Kalyan²,Sultana Mahamuda³,Sarkar Angsuman⁴

Affiliation:

1. MCKV Institute of Engineering,CSE Department,Liluah,WB,India

2. MCKV Institute of Engineering,ECE Department,Liluah,WB,India

3. Guru Nanak Institute of Technology,CSE Department,Sodepur, Kolkata

4. Kalyani Govt. Engineering College,ECE Department,Kalyani,WB,India

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10134754/10134560/10134917.pdf?arnumber=10134917

Reference23 articles.

1. Data Evaluation and Enhancement for Quality Improvement of Machine Learning

2. Efficiency Enhancement of Machine Learning Approaches through the Impact of Preprocessing Techniques

3. Data Augmentation Techniques For Expanding The Dataset In The Task Of Image Processing

4. Data augmentation for improving deep learning in image classification problem

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1. Machine learning to optimize nonlinear conductive performance of composites for self‐adaptive electromagnetic shielding;Polymer Composites;2024-08-21

2. Multiscale Modeling and Data-Driven Approaches for Energy Efficiency Prediction in Computing;2023 5th International Conference on Inventive Research in Computing Applications (ICIRCA);2023-08-03

3. A Comprehensive Technique Based on Machine Learning for Device and Circuit Modeling of Gate-All-Around Nanosheet Transistors;IEEE Open Journal of Nanotechnology;2023

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