Artificial Life and Computational Intelligence
Third Australasian Conference, ACALCI 2017, Geelong, VIC, Australia, January 31 – February 2, 2017, Proceedings
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**hu Li
Artificial Intelligence
Computation by Abstract Devices
Pattern Recognition
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Chapter and Conference Paper
Image Encryption Algorithms Based on Non-uniform Second-Order Reversible Cellular Automata with Balanced Rules
In this paper, we propose an image encryption algorithm based on non-uniform second-order reversible cellular automata (CA) which consist of two-state cells and use the Moore neighborhood. Different from othe...
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Chapter and Conference Paper
Benchmarking and Evaluating MATLAB Derivative-Free Optimisers for Single-Objective Applications
MATLAB® builds in a number of derivative-free optimisers (DFOs), conveniently providing tools beyond conventional optimisation means. However, with the increase of available DFOs and being compounded by the fa...
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Chapter and Conference Paper
A Potential-Based Density Estimation Method for Clustering Using Decision Graph
Clustering is an important unsupervised machine learning method which has played an important role in various fields. As suggested by Alex Rodriguez et al. in a paper published in Science in 2014, the 2D decision...
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Chapter and Conference Paper
LSLS: A Novel Scaffolding Method Based on Path Extension
While aiming to determine orientations and orders of fragmented contigs, scaffolding is an essential step of assembly pipelines and can make assembly results more complete. Most existing scaffolding tools adop...
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Chapter and Conference Paper
Smooth Multi-instance Learning for Object Detection
The problem of object localization is one of the key problems in computer vision applications. Recently, multiple-instance learning (MIL) is a kind of machine learning framework which receiving a set of insta...
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Chapter and Conference Paper
Research on Multi-UAV Loading Multi-type Sensors Cooperative Reconnaissance Task Planning Based on Genetic Algorithm
Unmanned Aerial Vehicle (UAV) has been playing an increasingly important role in modern military fields recently. The multi-UAV cooperative reconnaissance mission planning is one of the task allocation and res...
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Chapter and Conference Paper
Dependent Source Separation with Nonparametric Non-Gaussianity Measure
Separating statistically dependent source signals from their linear mixtures is a challenging problem in signal processing society. Firstly, we show that maximization of the non-Gaussianity (NG) measure among ...
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Chapter and Conference Paper
Univariate Gaussian Model for Multimodal Inseparable Problems
It has been widely perceived that a univariate Gaussian model for evolutionary search can be used to solve separable problems only. This paper explores whether and how the univariate Gaussian model may also be...
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Chapter and Conference Paper
Protein-Protein Binding Affinity Prediction Based on Wavelet Package Transform and Two-Layer Support Vector Machines
Precisely inferring the affinities of protein-protein interaction is essential for evaluating different methods of protein-protein docking and their outputs and also opens a door to inferring real status of ce...
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Book and Conference Proceedings
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Chapter and Conference Paper
Face Recognition via Domain Adaptation and Manifold Distance Metric Learning
A novel approach for face recognition via domain adaptation and manifold distance metric learning is presented in this paper. Recently, unconstrained face recognition is becoming a research hot in computer vis...
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Chapter and Conference Paper
A Unified Deep Neural Network for Scene Text Detection
Scene text detection is important and valuable for text recognition in natural scenes, but it is still a very challenging problem. In this paper, we propose a unified deep neural network for scene text detecti...
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Chapter and Conference Paper
Discriminative Motif Elicitation via Maximization of Statistical Overpresentation
The Fisher Exact Test score (FETS) and its variants are based on the hypergeometric distribution. It’s very natural to describe the enrichment level of TF binding site (TFBS) by it. And several widely used me...
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Chapter and Conference Paper
Learning Convolutional Ranking-Score Function by Query Preference Regularization
Ranking score plays an important role in the system of content-based retrieval. Given a query, the database items are ranked according to the ranking scores in a descending order, and the top-ranked items are ...
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Chapter and Conference Paper
A High and Efficient Sparse and Compressed Sensing-Based Security Approach for Biometric Protection
We propose a highly efficient sparse code with compressive sensing security algorithm based on the Dual-tree Complex Wavelet Transform (DT-CWT) and Hadamard measurement matrix in this paper for biometric prot...
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Chapter and Conference Paper
Extending the Delaunay Triangulation Based Density Measurement to Many-Objective Optimization
This paper investigates the scalability of the Delaunay triangulation (DT) based diversity preservation technique for solving many-objective optimization problems (MaOPs). Following the NSGA-II algorithm, the ...
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Chapter and Conference Paper
Image Recognition Using Local Features Based NNSC Model
Non-negative sparse coding (NNSC) model can extract efficiently image features and has been used widely in image processing. However, in terms of the image feature classification, the recognition precision of ...
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Chapter and Conference Paper
Research on Feature Selection and Predicting ALS Disease Progression
Amyotrophic lateral sclerosis (ALS) is a rapidly progressive, invariably fatal neurological disease that attacks the nerve cells responsible for controlling voluntary muscles. The disease belongs to a group o...
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Chapter and Conference Paper
A New Adaptive Firefly Algorithm for Solving Optimization Problems
Firefly algorithm (FA) is an efficient optimization technique, which has been widely used to solve various engineering problems. However, FA is sensitive to its control parameters. Recently, a memetic FA (call...
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Chapter and Conference Paper
Similarity Matrix Construction Methods in Sparse Subspace Clustering Algorithm for Hyperspectral Imagery Clustering
The clustering of hyperspectral images is a challenging task because of the high dimensionality of the data. The sparse subspace clustering (SSC) algorithm is one of the popular used clustering algorithm for h...
