ImageNet: A large-scale hierarchical image database
The explosion of image data on the Internet has the potential to foster more sophisticated and robust models and algorithms to index, retrieve, organize and interact with images...
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10,000 publications
Gradient-based learning applied to document recognition
Multilayer neural networks trained with the back-propagation algorithm constitute the best example of a successful gradient based learning technique. Given an appropriate networ...
Global cancer statistics
The global burden of cancer continues to increase largely because of the aging and growth of the world population alongside an increasing adoption of cancer-causing behaviors, p...
The CES-D Scale
The CES-D scale is a short self-report scale designed to measure depressive symptomatology in the general population. The items of the scale are symptoms associated with depress...
Regression Shrinkage and Selection Via the Lasso
SUMMARY We propose a new method for estimation in linear models. The ‘lasso’ minimizes the residual sum of squares subject to the sum of the absolute value of the coefficients b...
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, ...
Prospect Theory: An Analysis of Decision under Risk
This paper presents a critique of expected utility theory as a descriptive model of decision making under risk, and develops an alternative model, called prospect theory. Choice...
A fast and elitist multiobjective genetic algorithm: NSGA-II
Multi-objective evolutionary algorithms (MOEAs) that use non-dominated sorting and sharing have been criticized mainly for: (1) their O(MN/sup 3/) computational complexity (wher...
The Hospital Anxiety and Depression Scale
ABSTRACT– A self‐assessment scale has been developed and found to be a reliable instrument for detecting states of depression and anxiety in the setting of an hospital medical o...