11 papers · ranked by Valyu relevance
Max F. Burg, Santiago A. Cadena, George H. Denfield, Edgar Y. Walker + 3 more
Deep convolutional neural networks (CNNs) have emerged as the state of the art for predicting neural activity in visual cortex. While such models outperform classical linear-nonlinear and wavelet-based representations, we currently do not know what computations they approximate. Here, we tested divisive normalization…
Xu Pan, Luis Gonzalo Sánchez Giraldo, Elif Kartal, Odelia Schwartz
We studied a local normalization paradigm, namely weighted normalization, that better reflects the current understanding of the brain. Specifically, the normalization weight is trainable, and has a more realistic surround pool selection. Weighted normalization outperformed other normalizations in image classification…
H. Sebastian Seung
Normalization is a fundamental operation in image processing. Convolutional nets have evolved to include a large number of normalizations (29; 64; 65), and this architectural shift has proved essential for robust computer vision (27; 6; 48). Studies of biological vision, in contrast, have invoked just one or a few…
Zeming Fang, Ilona Bloem, Catherine Olsson, Wei Ji Ma + 1 more
An influential account of neuronal responses in primary visual cortex is the normalized energy model. This model is often implemented as a two-stage computation. The first stage is the extraction of contrast energy, whereby a complex cell computes the squared and summed outputs of a pair of linear filters in quadrature…
Saman Sarraf, Ghassem Tofighi
Over the past decade, machine learning techniques and in particular predictive modeling and pattern recognition in biomedical sciences, from drug delivery systems to medical imaging, have become one of the most important methods of assisting researchers in gaining a deeper understanding of issues in their entirety and…
Yu Zhang, Loïc Tetrel, Bertrand Thirion, Pierre Bellec
A key goal in neuroscience is to understand brain mechanisms of cognitive functions. An emerging approach is “brain decoding”, which consists of inferring a set of experimental conditions performed by a participant, using pattern classification of brain activity. Few works so far have attempted to train a brain…
Yang Shen, Julia Wang, Saket Navlakha
A fundamental challenge at the interface of machine learning and neuroscience is to uncover computational principles that are shared between artificial and biological neural networks. In deep learning, normalization methods, such as batch normalization, weight normalization, and their many variants, help to stabilize…
Maik Wolfram-Schauerte, Thomas Vogel, Laura Achauer, Sara Maria Fälth Savitski + 3 more
Bulk cell type deconvolution aims to estimate cell type composition from bulk transcriptomic data. So-called pseudobulk simulation, where single-cell RNA-seq data is aggregated to bulk-like expression profiles, represents a central concept in training and testing of deconvolution tools. However, deconvolution methods…
Md. Aminur Rab Ratul, Mohammad Hamed Mozaffari, Enea Parimbelli, WonSook Lee
Skin cancer is a crucial public health issue and by far the most usual kind of cancer specifically in the region of North America. It is estimated that in 2019, only because of melanoma nearly 7,230 people will die, and 192,310 cases of malignant melanoma will be diagnosed. Nonetheless, nearly all types of skin lesions…
Md. Aminur Rab Ratul, M. Hamed Mozaffari, Won-Sook Lee, Enea Parimbelli
The prediction of skin lesions is a challenging task even for experienced dermatologists due to a little contrast between surrounding skin and lesions, the visual resemblance between skin lesions, fuddled lesion border, etc. An automated computer-aided detection system with given images can help clinicians to prognosis…
Peter Kirchweger, Lev Melnikovsky, Shahar Seifer, Michael Elbaum
Cryo-electron tomography is an expanding technology for the study of macromolecules, viruses, and cells. It is often applied to specimens that are too large or heterogeneous for methods based on 2D image averaging such as single particle analysis, e.g., intracellular membranes or organelles. Current practice records a…