Results 51 to 60 of about 550,068 (301)
Automatic image equalization and contrast enhancement using Gaussian mixture modeling [PDF]
, 2012 In this paper, we propose an adaptive image equalization algorithm that automatically enhances the contrast in an input image. The algorithm uses the Gaussian mixture model to model the image gray-level distribution, and the intersection points of the ...
Tjahjadi, Tardi +3 more
core +1 more source
Frontiers in Human Neuroscience, 2016 Humans are fast and accurate in categorizing complex natural images. It is, however, unclear what features of visual information are exploited by brain to perceive the images with such speed and accuracy.
Masoud Ghodrati +3 more
doaj +1 more source
Statistics of Deep Generated Images
CoRR, 2017 Here, we explore the low-level statistics of images generated by state-of-the-art deep generative models. First, Variational auto-encoder (VAE~\cite{kingma2013auto}), Wasserstein generative adversarial network (WGAN~\cite{arjovsky2017wasserstein}) and deep convolutional generative adversarial network (DCGAN~\cite{radford2015unsupervised}) are trained ...
Yu Zeng 0001, Huchuan Lu, Ali Borji
openaire +2 more sources
Pediatric Blood &Cancer, EarlyView.ABSTRACT Primary lung carcinomas and bronchial carcinoid tumors (BC) are very rare malignancies in childhood. While typical BC and mucoepidermoid carcinomas are mostly low‐grade, localized tumors with a more favorable prognosis than in adults, necessitating avoidance of overtreatment, adenocarcinomas of the lung are often diagnosed at advanced disease ...
Michael Abele +19 more
wiley +1 more source
Shaping the aesthetical landscape by using image statistics measures
Acta Psychologica, 2022 Aesthetics and evaluation of objects is becoming increasingly important in contemporary society. Although there have been many studies on processes related to computational aesthetic, a clear formalisation and visualization of the aesthetic field is ...
F. Bertacchini, P.S. Pantano, E. Bilotta
doaj +1 more source
Statistical limitations in proton imaging
Physics in Medicine & Biology, 2020 Abstract Proton imaging is a promising technology for proton radiotherapy as it can be used for: (1) direct sampling of the tissue stopping power, (2) input information for multi-modality RSP reconstruction, (3) gold-standard calibration against concurrent techniques, (4) tracking motion and (5) pre-treatment positioning. However, no end-
Collins-Fekete, Charles-Antoine +3 more
openaire +5 more sources
Pediatric Blood &Cancer, EarlyView.ABSTRACT Background 131I‐metaiodobenzylguanidine (131I‐MIBG) radiotherapy is a key treatment for relapsed and refractory (R/R) neuroblastoma (NB). Patients with R/R disease treated in the modern era are increasingly exposed to anti‐GD2 immunotherapy, which exerts selective pressure and may modify both tumor cell state and microenvironment.
Benjamin J. Lerman +7 more
wiley +1 more source
Frontiers in Computational Neuroscience, 2014 The responses of visual neurons in experimental animals have been extensively characterized. To ask whether these responses are consistent with a wholly empirical concept of visual perception, we optimized simple neural networks that respond according ...
Yaniv eMorgenstern +5 more
doaj +1 more source
Pediatric Blood &Cancer, EarlyView.ABSTRACT Background Wilms tumor (WT) treatment imposes a significant time burden on patients and their families. Time toxicity is a patient‐centered metric that quantifies the burden of healthcare interaction. We sought to define time toxicity in the first year after diagnosis of WT and hypothesized that it would increase as tumor stage and treatment ...
Caleb Q. Ashbrook +6 more
wiley +1 more source