Results 81 to 90 of about 8,972,433 (325)
CVML-Pose: Convolutional VAE Based Multi-Level Network for Object 3D Pose Estimation
IEEE Access, 2023 Most vision-based 3D pose estimation approaches typically rely on knowledge of object’s 3D model, depth measurements, and often require time-consuming iterative refinement to improve accuracy.
Jianyu Zhao +2 more
doaj +1 more source
The Landscape of Modern Machine Learning: A Review of Machine, Distributed and Federated Learning [PDF]
arXiv, 2023 With the advance of the powerful heterogeneous, parallel and distributed computing systems and ever increasing immense amount of data, machine learning has become an indispensable part of cutting-edge technology, scientific research and consumer products. In this study, we present a review of modern machine and deep learning.
arxiv
Double/Debiased Machine Learning for Treatment and Structural Parameters
, 2017 We revisit the classic semiparametric problem of inference on a low dimensional parameter θ_0 in the presence of high-dimensional nuisance parameters η_0.
V. Chernozhukov +6 more
semanticscholar +1 more source
Molecular Oncology, EarlyView.Consensus molecular subtypes (CMS1‐4) have been identified to study colorectal cancer heterogeneity and serve as potential biomarkers. In this study, we developed and evaluated NanoCMSer, a NanoString‐based classifier using 55 genes, optimized for FF and FFPE to facilitate the clinical evaluation of CMS subtyping.
Arezo Torang +10 more
wiley +1 more source
A Variational Beam Model for Failure of Cellular and Truss‐Based Architected Materials
Advanced Engineering Materials, EarlyView., 2023 Herein, a versatile and efficient beam modeling framework is developed to predict the nonlinear response and failure of cellular, truss‐based, and woven architected materials. It enables the exploration of their design space and the optimization of their mechanical behavior in the nonlinear regime. A variational formulation of a beam model is presented
Konstantinos Karapiperis +3 more
wiley +1 more source
Self-supervision advances morphological profiling by unlocking powerful image representations
Scientific ReportsCell Painting is an image-based assay that offers valuable insights into drug mechanisms of action and off-target effects. However, traditional feature extraction tools such as CellProfiler are computationally intensive and require frequent parameter ...
Vladislav Kim +7 more
doaj +1 more source
Parallelization of Machine Learning Algorithms Respectively on Single Machine and Spark [PDF]
arXiv, 2022 With the rapid development of big data technologies, how to dig out useful information from massive data becomes an essential problem. However, using machine learning algorithms to analyze large data may be time-consuming and inefficient on the traditional single machine. To solve these problems, this paper has made some research on the parallelization
arxiv
Machine learning for neuroimaging with scikit-learn [PDF]
Frontiers in Neuroinformatics, 2014 Frontiers in neuroscience, Frontiers Research Foundation, 2013, pp ...
Alexandre Gramfort +16 more
openaire +7 more sources
Machine Learning in Bioelectrocatalysis
Advanced Science, 2023 AbstractAt present, the global energy crisis and environmental pollution coexist, and the demand for sustainable clean energy has been highly concerned. Bioelectrocatalysis that combines the benefits of biocatalysis and electrocatalysis produces high‐value chemicals, clean biofuel, and biodegradable new materials.
Jiamin Huang +5 more
openaire +3 more sources
Molecular Oncology, EarlyView.Large multidimensional digital images of cancer tissue are becoming prolific, but many challenges exist to automatically extract relevant information from them using computational tools. We describe publicly available resources that have been developed jointly by expert and non‐expert computational biologists working together during a virtual hackathon
Sandhya Prabhakaran +16 more
wiley +1 more source