Batch Normalization (BN) is a milestone technique in the development of deep learning, enabling various networks to train. However, normalizing along the batch dimension introduces problems — BN’s error increases rapidly when the batch size becomes smaller, caused by inaccurate batch statistics estimation. This limits BN’s usage for training larger models and transferring features to computer v...

Training state-of-the-art, deep neural networks is computationally expensive. One way to reduce the training time is to normalize the activities of the neurons. A recently introduced technique called batch normalization uses the distribution of the summed input to a neuron over a mini-batch of training cases to compute a mean and variance which are then used to normalize the summed input to tha...

Captured images arise through interaction between objects of interest and illuminating light sources. If the latter are unevenly distributed, or are too strong or too weak, the image can have low contrast either locally or globally, impeding its interpretation and reducing its usefulness. In practice, control of illumination conditions is challenging, and not always possible. Thus, we propose a...

We describe a comprehensive framework for performing rapid and automatic non-label based nonlinear spatial normalizations. The approach adopted minimizes the residual squared diierence between an image and a template of the same modality. In order to reduce the number of parameters to be tted, the nonlinear warps are described by a linear combination of low spatial frequency basis functions. Th...

Normalization means to adjust microarray data for effects which arise from variation in the technology rather than from biological differences between the RNA samples or between the printed probes. This paper describes normalization methods based on the fact that dye balance typically varies with spot intensity and with spatial position on the array. Print-tip loess normalization provides a wel...

The aim of this research is to create and to normalize the marital infidelity predictor test. The method used in this study is post-event and it uses the survey technique. The statistical population consists of women residents in Tehran and for investigating the subject and determining the technical characteristics of the questionnaire, 200 individuals are selected, through cluster sampling, wh...

The technology of handwritten Chinese character recognition (HCCR) has seen significant advances in the last two decades owing to the effectiveness of many techniques, especially those for character shape normalization and feature extraction. This chapter reviews the major methods of normalization and feature extraction and evaluates their performance experimentally. The normalization methods i...

MOTIVATION Our goal was to develop a normalization technique that yields results similar to cyclic loess normalization and with speed comparable to quantile normalization. RESULTS Fastlo yields normalized values similar to cyclic loess and quantile normalization and is fast; it is at least an order of magnitude faster than cyclic loess and approaches the speed of quantile normalization. Furth...