14 papers · ranked by Valyu relevance
Chao Pan, S. M. Hossein Tabatabaei Yazdi, S Kasra Tabatabaei, Alvaro G. Hernandez + 2 more
The main obstacles for the practical deployment of DNA-based data storage platforms are the prohibitively high cost of synthetic DNA and the large number of errors introduced during synthesis. In particular, synthetic DNA products contain both individual oligo (fragment) symbol errors as well as missing DNA oligo…
Nisar Wani, Khalid Raza
Computer aided diagnosis is gradually making its way into the domain of medical research and clinical diagnosis. With field of radiology and diagnostic imaging producing petabytes of image data. Machine learning tools, particularly kernel based algorithms seem to be an obvious choice to process and analyze this high…
Bevan L. Cheeseman, Ulrik Günther, Mateusz Susik, Krzysztof Gonciarz + 1 more
Modern microscopy modalities create a data deluge with gigabytes of data generated each second, or terabytes per day. Storing and processing these data is a severe bottleneck. We argue that this is an artifact of the images being represented on pixels. To address the root of the problem, we here propose the Adaptive…
Xingche Guo, Yumou Qiu, Dan Nettleton, Cheng-Ting Yeh + 3 more
High-throughput phenotyping is a modern technology to measure plant traits efficiently and in large scale by imaging systems over the whole growth season. Those images provide rich data for statistical analysis of plant phenotypes. We propose a pipeline to extract and analyze the plant traits for field phenotyping…
Xiongtao Ruan, Matthew Mueller, Gaoxiang Liu, Frederik Görlitz + 12 more
Light sheet microscopy is a powerful technique for high-speed 3D imaging of subcellular dynamics and large biological specimens. However, it often generates datasets ranging from hundreds of gigabytes to petabytes in size for a single experiment. Conventional computational tools process such images far slower than the…
Jeffrey C. Berry, Noah Fahlgren, Alexandria A. Pokorny, Rebecca Bart + 1 more
High-throughput phenotyping has emerged as a powerful method for studying plant biology. Large image-based datasets are generated and analyzed with automated image analysis pipelines. A major challenge associated with these analyses is variation in image quality that can inadvertently bias results. Images are made up…
Sawayama Masataka
This perspective on efficient color processing is based on three key findings from material perception studies. The first finding is that color and luminance are highly redundant in certain materials, particularly in wet or translucent objects with subsurface scattering . For example, there is a strong negative…
Patrick Hüther, Niklas Schandry, Katharina Jandrasits, Ilja Bezrukov + 1 more
Linking plant phenotype to genotype, i.e., identifying genetic determinants of phenotypic traits, is a common goal of both plant breeders and geneticists. While the ever-growing genomic resources and rapid decrease of sequencing costs have led to enormous amounts of genomic data, collecting phenotypic data for large…
Ingo Fruend
The first steps of visual processing are often described as a bank of oriented filters followed by divisive normalization. This approach has been tremendously successful at predicting contrast thresholds in simple visual displays. However, it is unclear to what extent this kind of architecture also supports processing…
Mauro Silberberg, Hernán E. Grecco
Quantitative analysis of high-throughput microscopy images requires robust automated algorithms. Background estimation is usually the first step and has an impact on all subsequent analysis, in particular for foreground detection and calculation of ratiometric quantities. Most methods recover only a single background…
Arjen Alink, Ian Charest
Individuals with an autism spectrum disorder (ASD) diagnosis are often described as having an ‘eye for detail’1. This observation, and the finding that individuals with ASD tend to ‘see the trees before the forest’ when performing the Navon task2, has led to the proposal that ASD is characterized by a bias towards…
Ritam Dutta, Bheem Dutt Joshi, Vineet Kumar, Amira Sharief + 4 more
Despite advancements in remote sensing, satellite imagery is underutilized in conservation research. Multispectral data from various sensors have great potential for mapping landscapes, but distinct spectral and spatial resolution capabilities are crucial for accurately classifying wildlife habitats. Our study aimed to…
Alex S Baldwin, Madeleine Kenwood, Robert F Hess
Boundaries in the visual world can be defined by changes in luminance and texture in the input image. A “contour integration” process joins together local changes into percepts of lines or edges. A previous study tested the integration of contours defined by second-order contrast-modulation. Their contours were placed…
Lydia Kienbaum, Miguel Correa Abondano, Raul Blas, Karl Schmid
Maize cobs are an important component of crop yield that exhibit a high diversity in size, shape and color in native landraces and modern varieties. Various phenotyping approaches were developed to measure maize cob parameters in a high throughput fashion. More recently, deep learning methods like convolutional neural…