The proceedings contain 51 papers. The special focus in this conference is on Computational Intelligence. The topics include: Towards Real-Time Fleet-Event-Handling for the Dynamic Vehicle Routing Problem;performance ...
ISBN:
(纸本)9789897582745
The proceedings contain 51 papers. The special focus in this conference is on Computational Intelligence. The topics include: Towards Real-Time Fleet-Event-Handling for the Dynamic Vehicle Routing Problem;performance of Complex-Valued Multilayer Perceptrons Largely Depends on Learning Methods;efficient Implementation of Self-Organizing Map for Sparse Input Data;a Fuzzy Logic Approach to Improve Phone Segmentation A Case Study of the Dutch Language;the Behavior of Deep Statistical Comparison Approach for Different Criteria of Comparing Distributions;determining Firing Strengths Through a Novel Similarity Measure to Enhance Uncertainty Handling in Non-singleton Fuzzy Logic systems;enhanced Symbolic Regression Through Local Variable Transformations;towards the Enrichment of Arabic WordNet with Big Corpora;R-FCN Object Detection Ensemble based on Object Resolution and image Quality;Depth Value Pre-processing for Accurate Transfer Learning based RGB-D Object Recognition;Self-learning Smart Cameras Harnessing the Generalization Capability of XCS;entorhinal Grid Cells May Facilitate Pattern Separation in the Hippocampus;higher Order Neural Units for Efficient Adaptive Control of Weakly Nonlinear systems;CNN Patch–Based Voting for Fingerprint Liveness Detection;environment Recognition based on images using Bag-of-Words;emotion Recognition from Speech using Representation Learning in Extreme Learning Machines;neural Network Inverse Model for Quality Monitoring Application to a High Quality Lackering Process;parallelization of Real-time Control algorithms on Multi-core Architectures using Ant Colony Optimization;ant Colony Optimization Approaches for the Tree t-Spanner Problem;hierarchy Influenced Differential Evolution: A Motor Operation Inspired Approach;towards a Better Understanding of Deep Neural Networks Representations using Deep Generative Networks;comparing Small Population Genetic algorithms over Changing Landscapes.
As one kind of popular application in computer vision, image clustering has attracted many attentions. Some machine learning algorithms have been widely employed, such as K-Means, Non-negative Matrix Factorization (NM...
详细信息
As one kind of popular application in computer vision, image clustering has attracted many attentions. Some machine learning algorithms have been widely employed, such as K-Means, Non-negative Matrix Factorization (NMF), Graph regularized Non-negative Matrix Factorization (GNMF) and Locally Consistent Concept Factorization (LCCF). These methods possess respective strength and weakness. The common problem existing in these clustering algorithms is that they only use one kind of feature. However, different kinds of features complement each other and can be used to improve performance results. In this paper, in order to make use of the complementarity between different features, we propose an image representation method based on multi-features. Clustering results on several benchmark image data sets show that the proposed scheme outperforms some classical methods.
As a powerful technique, sparse coding was adopted by several researchers in different approaches. Particularly in imageprocessing, it has attracted a considerable attention. It can be widely used for representation,...
详细信息
As a powerful technique, sparse coding was adopted by several researchers in different approaches. Particularly in imageprocessing, it has attracted a considerable attention. It can be widely used for representation, compression, denoising and separation of all type of signal. Recent works have confirmed that the use of a predefined dictionary is less efficient than a dictionary from training data. According to this idea, this paper proposes a new technique based on wavelet network to create a dictionary to ameliorate the representation and classification of image using sparse coding technique.
Dermatological Diseases are one of the biggest medical issues in 21st century due to it's highly complex and expensive diagnosis with difficulties and subjectivity of human interpretation. In cases of fatal diseas...
详细信息
ISBN:
(纸本)9781538619599
Dermatological Diseases are one of the biggest medical issues in 21st century due to it's highly complex and expensive diagnosis with difficulties and subjectivity of human interpretation. In cases of fatal diseases like Melanoma diagnosis in early stages play a vital role in determining the probability of getting cured. We believe that the application of automated methods will help in early diagnosis especially with the set of images with variety of diagnosis. Hence, in this article we present a completely automated system of dermatological disease recognition through lesion images, a machine intervention in contrast to conventional medical personnel based detection. Our model is designed into three phases compromising of data collection and augmentation, designing model and finally prediction. We have used multiple AI algorithms like Convolutional Neural Network and Support Vector Machine and amalgamated it with imageprocessing tools to form a better structure, leading to higher accuracy of 95.3%.
Multichannel synthetic aperture radar (MSAR) systems are essential for applications such as ground moving target indication (GMTI), interferometric SAR (InSAR), and high-resolution wide-swath (HRWS) imaging. In this p...
详细信息
Multichannel synthetic aperture radar (MSAR) systems are essential for applications such as ground moving target indication (GMTI), interferometric SAR (InSAR), and high-resolution wide-swath (HRWS) imaging. In this paper, we analyze and compare MSAR image reconstruction algorithms. Previously, image reconstruction for MSAR has relied heavily on frequency domain matched filtering. Time domain image reconstruction algorithms have several attractive qualities, but their use has been limited due to a high computational burden. In this paper, we utilize digital beamforming and the phase center approximation to develop a fast time domain (fast factorized back-projection, FFBP) algorithm for MSAR. We present two FFBP implementations for MSAR and perform a comparative study between MSAR imaging algorithms. The numerical results confirm the feasibility of the proposed FFBP algorithms for MSAR.
Autonomous vehicles operating in dynamic environments rely on precise localization. In this paper we present a novel approach for cooperative localization of vehicular systems and an infrastructure RADAR which is resi...
详细信息
ISBN:
(纸本)9780996452700
Autonomous vehicles operating in dynamic environments rely on precise localization. In this paper we present a novel approach for cooperative localization of vehicular systems and an infrastructure RADAR which is resilient against outliers generated from the RADAR. The problem of cooperative localization is represented as a factor graph, where interrelated topologies ( including that of outliers) are added as constraint factor between vehicle states. Corresponding probabilities for multiple topologies between states of the two vehicles are calculated using the Probability Data Association Filter and assigned to the respective edges in the graph. Simulation results indicate that this technique has significant benefits in the context of improving the resilience against outliers while optimizing joint state estimates. The methodology presented in this paper has the potential to provide a robust and flexible framework for cooperative localization in the presence of clutter, obscuration and targets entering and leaving the field of view.
The proceedings contain 69 papers. The special focus in this conference is on Advances in Information and Communication Technology. The topics include: Multimodal based clouds computing systems for healthcare and risk...
ISBN:
(纸本)9783319490724
The proceedings contain 69 papers. The special focus in this conference is on Advances in Information and Communication Technology. The topics include: Multimodal based clouds computing systems for healthcare and risk forecasting based on subjective analysis;telematics and advanced transportation services;toward affective speech-to-speech translation;a computer vision based machine for walnuts sorting using robot operating system;a fpga based two level optimized local filter designfor high speed imageprocessing applications;a frequency dependent investigation of complex shear modulus estimation;a method to enhance the remote sensing images based on the local approach using kmeans algorithm;a method for clustering and identifying http automated software communication;a new neuro-fuzzy inference system for insurance forecasting;a new schema to identify s-farnesyl cysteine prenylation sites with substrate motifs;a novel framework based on deep learning and unmanned aerial vehicles to assess the quality of rice fields;a semi-supervised learning method for hybrid filtering;a study on fitness representation in genetic programming;an evaluation of hand pyramid structure for hand representation based on kernels;an exploratory study on students’ performance classification using hybrid of decision tree and naïve bayes approaches;an iterative method to solve boundary value problems with irregular boundary conditions;classifying human body postures by a support vector machine with two simple features;comparing modified pso algorithms for mrs in unknown environment exploration and estimation localization in wireless sensor network based on multi-objective grey wolf optimizer.
The 2D non-separable linear canonical transform (2D-NS-LCT) can model a range of various paraxial optical systems. Digital algorithms to evaluate the 2D-NS-LCTs are important in modeling the light field propagations a...
详细信息
ISBN:
(数字)9781510609686
ISBN:
(纸本)9781510609679;9781510609686
The 2D non-separable linear canonical transform (2D-NS-LCT) can model a range of various paraxial optical systems. Digital algorithms to evaluate the 2D-NS-LCTs are important in modeling the light field propagations and also of interest in many digital signal processing applications. In [Zhao 14] we have reported that a given 2D input image with rectangular shape/boundary, in general, results in a parallelogram output sampling grid (generally in an affine coordinates rather than in a Cartesian coordinates) thus limiting the further calculations, e.g. inverse transform. One possible solution is to use the interpolation techniques;however, it reduces the speed and accuracy of the numerical approximations. To alleviate this problem, in this paper, some constraints are derived under which the output samples are located in the Cartesian coordinates. Therefore, no interpolation operation is required and thus the calculation error can be significantly eliminated.
暂无评论