A comprehensive survey on electronic design automation and graph neural networks: Theory and applications
Driven by Moore's law, the chip design complexity is steadily increasing. Electronic Design
Automation (EDA) has been able to cope with the challenging very large-scale integration …
Automation (EDA) has been able to cope with the challenging very large-scale integration …
Applying gnns to timing estimation at rtl
In the Electronic Design Automation (EDA) flow, signoff checks, such as timing analysis, are
performed only after physical synthesis. Encountered timing violations cause re-iterations of …
performed only after physical synthesis. Encountered timing violations cause re-iterations of …
Lung image segmentation via generative adversarial networks
J Cai, H Zhu, S Liu, Y Qi, R Chen - Frontiers in Physiology, 2024 - frontiersin.org
Introduction Lung image segmentation plays an important role in computer-aid pulmonary
disease diagnosis and treatment. Methods This paper explores the lung CT image …
disease diagnosis and treatment. Methods This paper explores the lung CT image …
Predicting costs of local public bus transport services through machine learning methods
A Amicosante, A Avenali, T D'Alfonso… - Expert Systems with …, 2025 - Elsevier
The present study developed several machine learning-based cost models to predict an
efficient total economic cost per vehicle revenue-mile of urban public bus transport. The …
efficient total economic cost per vehicle revenue-mile of urban public bus transport. The …
Analysis of cost estimation using the web metrics and cost driver in the high performance of web developers
A Salinda Eveline Suniram, J Charles - Automatika: časopis za …, 2023 - hrcak.srce.hr
Sažetak In recent years, many researchers and software industries have given significant
attention to the estimation of software effort. Software effort estimation is a challenge that …
attention to the estimation of software effort. Software effort estimation is a challenge that …
Deep reinforcement learning for optimization at early design stages
Deep Reinforcement Learning for Optimization at Early Design Stages Page 1 43 2168-2364/22©2022
IEEE Copublished by the IEEE CEDA, IEEE CASS, IEEE SSCS, and TTTC January/February …
IEEE Copublished by the IEEE CEDA, IEEE CASS, IEEE SSCS, and TTTC January/February …
Deep Learning-Based Partial Transfer Fault Diagnosis Methodology for Electromechanical Systems
Recently, transfer learning technology has provided valuable solutions to problems that are
present in machinery with industrial applications. Through the use of transfer learning, basic …
present in machinery with industrial applications. Through the use of transfer learning, basic …
SOC design automation with ML-it's time for research
The AI-hype started a few years ago, with advances in object recognition. Soon the EDA
research community made proposals on applying AI in EDA and all major players …
research community made proposals on applying AI in EDA and all major players …
Improved Slow Feature Analysis Algorithm and Its Application in Abnormal Human Behavior Recognition
T Chen, S Gao - Proceedings of the World Conference on Intelligent …, 2023 - Springer
With the development of social economy and the increasing population, human activities are
becoming more and more complex, and various abnormal events have also increased …
becoming more and more complex, and various abnormal events have also increased …
Develo** a Cost of Delay (CoD) framework for the DoD & analyzing the current state of Air Force agile cost estimation
J Goljan - 2021 - scholar.afit.edu
The study has two research objectives. The first research objective develops a proof of
concept for a Cost of Delay (CoD) framework to evaluate the Air Forces Kessel Run Software …
concept for a Cost of Delay (CoD) framework to evaluate the Air Forces Kessel Run Software …