Going deeper with convolutions
We propose a deep convolutional neural network architecture codenamed Inception that achieves the new state of the art for classification and detection in the ImageNet Large-Sca...
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We propose a deep convolutional neural network architecture codenamed Inception that achieves the new state of the art for classification and detection in the ImageNet Large-Sca...
We present ab initio quantum-mechanical molecular-dynamics calculations based on the calculation of the electronic ground state and of the Hellmann-Feynman forces in the local-d...
Content analysis is a widely used qualitative research technique. Rather than being a single method, current applications of content analysis show three distinct approaches: con...
Abstract Proteins are essential to life, and understanding their structure can facilitate a mechanistic understanding of their function. Through an enormous experimental effort ...
Part I: Introduction to Grounded Theory of Anselm Strauss Chapter 1: Inspiration and Background Chapter 2: Theoretical Foundations Chapter 3: Practical Considerations for Gettin...
In this article, we provide guidance for substantive researchers on the use of structural equation modeling in practice for theory testing and development. We present a comprehe...
The difficulties inherent in obtaining consistent and adequate diagnoses for the purposes of research and therapy have been pointed out by a number of authors. Pasamanick<sup>12...
Systematic reviews and meta-analyses have become increasinglyimportant in health care. Clinicians readthem to keep up to date with their field (1, 2), and they areoften used as ...
The criteria included in COREQ, a 32-item checklist, can help researchers to report important aspects of the research team, study methods, context of the study, findings, analys...
Convolutional networks are powerful visual models that yield hierarchies of features. We show that convolutional networks by themselves, trained end-to-end, pixels-to-pixels, ex...