Learning a Mixture of Deep Networks for Single Image Super-Resolution

Single image super-resolution (SR) is an ill-posed problem which aims to recover high-resolution (HR) images from their low-resolution (LR) observations. The crux of this problem lies in learning the complex mapping between low-resolution patches and the corresponding high-resolution patches. Prior arts have used either a mixture of simple regression models or a single non-linear neural network for this propose. This paper proposes the method of learning a mixture of SR inference modules in a unified framework to tackle this problem. Specifically, a number of SR inference modules specialized in different image local patterns are first independently applied on the LR image to obtain various HR estimates, and the resultant HR estimates are adaptively aggregated to form the final HR image. By selecting neural networks as the SR inference module, the whole procedure can be incorporated into a unified network and be optimized jointly. Extensive experiments are conducted to investigate the relation between restoration performance and different network architectures. Compared with other current image SR approaches, our proposed method achieves state-of-the-arts restoration results on a wide range of images consistently while allowing more flexible design choices. The source codes are available in http://www.ifp.illinois.edu/~dingliu2/accv2016

A High-Density Linkage Map of the Ancestral Diploid Strawberry, Fragaria iinumae, Constructed with Single Nucleotide Polymorphism Markers from the IStraw90 Array and Genotyping by Sequencing

Fragaria iinumae Makino is recognized as an ancestor of the octoploid strawberry species, which includes the cultivated strawberry, Fragaria ×ananassa Duchesne ex Rozier. Here we report the construction of the first high-density linkage map for F. iinumae. The F. iinumae linkage map (Fii map) is based on two high-throughput techniques of single nucleotide polymorphism (SNP) genotyping: the IStraw90 Array (hereafter “Array”), and genotyping by sequencing (GBS). The F2 generation mapping population was derived by selfing F. iinumae hybrid F1D, the product of a cross between two divergent F. iinumae accessions collected from Hokkaido, Japan. The Fii map consists of seven linkage groups (LGs) and has an overall length of 451.7 cM as defined by 496 loci populated by 4173 markers: 3280 from the Array and 893 from GBS. Comparisons with two versions of the Fragaria vesca ssp. vesca L. ‘Hawaii 4’ pseudo-chromosome (PC) assemblies reveal substantial conservation of synteny and colinearity, yet identified differences that point to possible genomic divergences between F. iinumae and F. vesca, and/or to F. vesca genomic assembly errors. The Fii map provides a basis for anchoring a F. iinumae genome assembly as a prerequisite for constructing a second diploid reference genome for Fragaria