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VoxelMatters1d
Sparc3D introduces next-gen high-resolution 3D model generation
Explore how Sparc3D transforms 2D images into detailed 3D models with AI-powered efficiency and precision. Discover more.
IEEE18d
Fuzzy Multivariate Variational Mode Decomposition With Applications in EEG Analysis
This article introduces a novel extension of the multivariate variational mode decomposition (MVMD) method, termed fuzzy MVMD (FMVMD), designed to enhance alignment information extraction. In contrast ...
IEEE22d
An Elliptic Kernel Unsupervised Autoencoder—Graph Convolutional Network Ensemble Model for Hyperspectral Unmixing - IEEE Xplore
Spectral unmixing is an important technique in remote sensing for analyzing hyperspectral images to identify endmembers and estimate fractional abundance maps. Over the past few decades, significant ...
ascopubs.org28d
A transfer-learned hierarchical variational autoencoder model for computational design of anticancer peptides. | Journal of Clinical Oncology - ASCO Publications
A transfer-learned hierarchical variational autoencoder model for computational design of anticancer peptides. Hossein Abbasi, Mahdi Malekpour, Shahin Yaghoobi, Sina Abdous, Mohammad Hossein Rohban, ...
Frontiers1mon
Integrating multi-source monitoring data and deep convolutional autoencoder technology for slope failure pattern recognition - Frontiers
Integrating multi-source monitoring data and deep convolutional autoencoder technology for slope failure pattern ... H., Chung, M., Cho, S., Kim, H., Kim, M., et al. (2018). “Squeezed convolutional ...
C&EN1mon
Transformation-Free Generation of a Quasi-Diabatic Representation from the State-Average Orbital-Optimized Variational Quantum Eigensolver - ACS Publications
In the present work, we examine how the recent quantum-computing algorithm known as the state-average orbital-optimized variational quantum eigensolver (SA-OO-VQE), viewed within the context of ...