PROTEIN MEASUREMENT WITH THE FOLIN PHENOL REAGENT
Since 1922 when Wu proposed the use of the Folin phenol reagent for the measurement of proteins (l), a number of modified analytical procedures ut.ilizing this reagent have been...
Publications
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1,042 publications
Deep Residual Learning for Image Recognition
Actualmente diversas investigaciones se han enfocado en analizar a partir de videos de alta velocidad, características de las descargas eléctricas atmosféricas con el fin de adq...
Long Short-Term Memory
Learning to store information over extended time intervals by recurrent backpropagation takes a very long time, mostly because of insufficient, decaying error backflow. We brief...
Particle swarm optimization
The base isolation design usually used the historical well-known earthquake records as an input ground motion. Through the adjustment on each variables of the structure system, ...
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...
CONFIDENCE LIMITS ON PHYLOGENIES: AN APPROACH USING THE BOOTSTRAP
The recently-developed statistical method known as the "bootstrap" can be used to place confidence intervals on phylogenies. It involves resampling points from one's own data, w...
Basics of qualitative research : techniques and procedures for developing grounded theory
Part I: Introduction to Grounded Theory of Anselm Strauss Chapter 1: Inspiration and Background Chapter 2: Theoretical Foundations Chapter 3: Practical Considerations for Gettin...
An Inventory for Measuring Depression
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...
MEGA X: Molecular Evolutionary Genetics Analysis across Computing Platforms
The Molecular Evolutionary Genetics Analysis (Mega) software implements many analytical methods and tools for phylogenomics and phylomedicine. Here, we report a transformation o...
Fully convolutional networks for semantic segmentation
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...
Rich Feature Hierarchies for Accurate Object Detection and Semantic Segmentation
Object detection performance, as measured on the canonical PASCAL VOC dataset, has plateaued in the last few years. The best-performing methods are complex ensemble systems that...
Rethinking the Inception Architecture for Computer Vision
Convolutional networks are at the core of most state of-the-art computer vision solutions for a wide variety of tasks. Since 2014 very deep convolutional networks started to bec...