Machine Learning-Based Manufacturing Cost Prediction from 2D Engineering Drawings via Geometric Features

Documenti analoghi

• Rapid Discovery of Graphene Nanocrystals Using DFT and Bayesian Optimization with Neural Network Kernel
  di: Özönder, Şener, et al.
  Pubblicazione: (2022)
• Attention to Order: Transformers Discover Phase Transitions via Learnability
  di: Özönder, Şener
  Pubblicazione: (2025)
• Unveiling the Design Rules for Tunable Emission in Graphene Quantum Dots: A High-Throughput TDDFT and Machine Learning Perspective
  di: Özdemir, Mustafa Çoşkun, et al.
  Pubblicazione: (2024)
• Electronic Phase Transformations and Energy Gap Variations in Uniaxial and Biaxial Strained Monolayer VS$_2$ TMDs: A Comprehensive DFT and Beyond-DFT Study
  di: Orhan, Oguzhan, et al.
  Pubblicazione: (2023)
• The impact of COVID‐19 pandemic on pediatric traumatic injury and demographic presentations to a university emergency department
  di: Mehmet Arikan, et al.
  Pubblicazione: (2024)