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Early ornithischian dinosaurs: the Triassic record
Abstract Ornithischian dinosaurs are one of the most taxonomically diverse dinosaur clades during the Mesozoic, yet their origin and early diversification remain virtually unknown. In recent years,Expand
Sketch-based image retrieval via Siamese convolutional neural network
TLDR
A novel convolutional neural network based on Siamese network for SBIR is proposed, which is to pull output feature vectors closer for input sketch-image pairs that are labeled as similar, and push them away if irrelevant. Expand
An adaptive routing protocol in underwater sparse acoustic sensor networks
TLDR
Experimental results verified that the AHH-VBF routing protocol outperforms HH-V BF protocol, naive Flooding and RDBF in terms of energy efficiency, end-to-end delay and data delivery ratio. Expand
PLncDB: plant long non-coding RNA database
TLDR
Plant long non-coding RNA database provides a comprehensive genomic view of Arabidopsis lncRNAs for the plant research community and will be regularly updated with new plant genome when available so as to greatly facilitate future investigations on plant lnc RNAs. Expand
An Eigenvector-Based Approach for Multidimensional Frequency Estimation With Improved Identifiability
  • Jun Liu, X. Liu
  • Mathematics, Computer Science
  • IEEE Transactions on Signal Processing
  • 1 December 2006
TLDR
Theoretical analysis and simulation results demonstrate the IMDF algorithm's competitive performance compared to the Crameacuter-Rao bound (CRB) and its significantly improved identifiability over existing algebraic approaches. Expand
Can k-NN imputation improve the performance of C4.5 with small software project data sets? A comparative evaluation
TLDR
A common machine learning technique that can tolerate missing values, namely C4.5, to predict cost using six real world software project databases is investigated and it is found that the k-NN imputation can improve the prediction accuracy of C 4.5. Expand
Image Segmentation Using a Local GMM in a Variational Framework
  • Jun Liu, Haili Zhang
  • Mathematics, Computer Science
  • Journal of Mathematical Imaging and Vision
  • 1 June 2013
TLDR
A new variational framework to solve the Gaussian mixture model (GMM) based methods for image segmentation by employing the convex relaxation approach, which can achieve promising segmentation performance for images degraded by intensity inhomogeneity and noise. Expand
First-Order Perturbation Analysis of Singular Vectors in Singular Value Decomposition
  • Jun Liu, X. Liu, Xiaoli Ma
  • Mathematics, Computer Science
  • IEEE/SP 14th Workshop on Statistical Signal…
  • 1 July 2008
TLDR
It is shown that not only the noise sub space, but also the signal subspace, contribute to the first-order perturbation of the singular vectors. Expand
The disease and gene annotations (DGA): an annotation resource for human disease
TLDR
Disease and Gene Annotations database (DGA) is a collaborative effort aiming to provide a comprehensive and integrative annotation of the human genes in disease network context by integrating computable controlled vocabulary of the Disease Ontology, NCBI Gene Reference Into Function, and molecular interaction network. Expand
Distance-based clustering of CGH data
TLDR
The results show that the correlation of neighboring genomic intervals should be considered in the structural analysis of CGH datasets, and the combination of sim with top-down clustering emerged as the best approach. Expand
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