The proceedings contain 47 papers. The special focus in this conference is on Pattern Recognition, signal, Image processing, Data Mining, Clustering and Intelligent Information Systems. The topics include: A comparati...
ISBN:
(纸本)9783319017778
The proceedings contain 47 papers. The special focus in this conference is on Pattern Recognition, signal, Image processing, Data Mining, Clustering and Intelligent Information Systems. The topics include: A comparative study on feature selection for retinal vessel segmentation using ant colony system;human skin segmentation in color images using Gaussian color model;an improved local statistics filter for denoising of SAR images;multisession video packet scheduling;mathematical morphology based fovea center detection using retinal fundus images;image restoration based on scene adaptive patch in-painting for tampered natural scenes;an impact of complex hybrid color space in image segmentation;natural color image enhancement based on modified multiscale retinex algorithm and performance evaluation using wavelet energy;multiple moving object recognitions in video based on log Gabor-PCA approach;gradual transition detection based on fuzzy logic using visual attention model;weighted optimization of various parameters for droplet routing in digital microfluidic biochips;phoneme-based recognizer to assist reading the holy Quran;a secure two party hierarchical clustering approach for vertically partitioned data set with accuracy measure;classification approach based on rough mereology;boosting text classification through stemming of composite words;sentiment analysis through machinelearning;indexing large class handwritten character database;text classification of Kannada webpages using various pre-processing agents;a novel agglomerative hierarchical approach for clustering in medical databases and mutagenicity analysis based on rough set theory and formal concept analysis.
June 26 to 29,2015,Beijing,China The Sixth internationalconference on Swarm Intelligence and the Second BRICS Congress on Computational Intelligence(ICSICCI'2015)(http://***)will be jointly held in Beijing,China,...
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June 26 to 29,2015,Beijing,China The Sixth internationalconference on Swarm Intelligence and the Second BRICS Congress on Computational Intelligence(ICSICCI'2015)(http://***)will be jointly held in Beijing,China,from June 26 to 29,*** theme of the ICSI-CCI'2015is"SERVING OUR SOCIETY And LIFE WITH INTELLIGENCE".With the advent of big
Various studies related to machinelearning have been performed. In this study, we focus on reinforcement learning, which is one of the methods used in machinelearning. In conventional reinforcement leaning, the rewa...
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ISBN:
(纸本)9781479931842
Various studies related to machinelearning have been performed. In this study, we focus on reinforcement learning, which is one of the methods used in machinelearning. In conventional reinforcement leaning, the reward function is difficult to design, because it is complex and laborious and it requires expert knowledge. In previous studies, the robot learned from outside itself, not autonomously. To solve this problem, we propose a method of robot learning through interactions with humans using sensor input, and the reward is also generated through interactions with humans but does not require additional tasks to be performed by the human. Therefore, in this method, expert knowledge is not required, and anyone can teach the robot. Our experiment confirmed that robot learning is possible through the proposed method.
The proceedings contain 68 papers. The topics discussed include: comparison on different random basis generator of a single-pixel camera;lossless data hiding with genetic-based hybrid prediction;the implementation of ...
ISBN:
(纸本)9781479931842
The proceedings contain 68 papers. The topics discussed include: comparison on different random basis generator of a single-pixel camera;lossless data hiding with genetic-based hybrid prediction;the implementation of OBD-II vehicle diagnosis system integrated with cloud computation technology;a collaborative representation based two-phase face recognition algorithm;image thresholding-based switching filter for salt & pepper noise removal;detecting robbery and violent scenarios;a novel feature extraction algorithm based on joint learning;an improved two-phase sparse representation method for traffic sign recognition;dynamic vehicle full-view driver assistance system in vehicular networks;a visual inspection system for prescription drugs in press through package;and compact multi-dimensional LBP features for improved texture retrieval.
The proceedings contain 56 papers. The topics discussed include: computer aided design of UAV navigation complexes with given characteristics;computer-aided design of cleanrooms for navigation complex electronic eleme...
ISBN:
(纸本)9781479933068
The proceedings contain 56 papers. The topics discussed include: computer aided design of UAV navigation complexes with given characteristics;computer-aided design of cleanrooms for navigation complex electronic elements manufacturing;flying wing design for solar rechargeable aircraft;balloon-parachute system of aerospace pilotless aircraft;forecasting the demand for UAV using different neural networks topology;ground control station power supply control system;data processing in exploitation system of unmanned aerial vehicles radioelectronic equipment;phase Doppler signal filtering in two-wave laser Doppler anemometer;convergence properties of an online learning algorithm in neural network models of complex systems;and structural identification of unmanned supercavitation vehicle based on incomplete experimental data.
A methodology to automatically detect moving objects in a scene using static cameras is proposed. Using Multiple Kernel Representations, we aim to incorporate multiple information sources in the process, and employing...
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ISBN:
(纸本)9789898565419
A methodology to automatically detect moving objects in a scene using static cameras is proposed. Using Multiple Kernel Representations, we aim to incorporate multiple information sources in the process, and employing a relevance analysis, each source is automatically weighted. A tuned Kmeans technique is employed to group pixels as static or moving objects. Moreover, the proposed methodology is tested for the classification of abbandoned objects. Attained results over real-world datasets, show how our approach is stable using the same parameters for all experiments.
The supply of the engineers who keep our modern society ticking is dependent on the attitudes of high school students towards tertiary engineering education. This supply has been reducing in recent years, which has le...
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This paper describes the automatic music composition system and automatic music evaluation system. The system composes short pieces of music by choosing some factors in music, such as pitch interval. timbre, tempo, rh...
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ISBN:
(纸本)9783642352850
This paper describes the automatic music composition system and automatic music evaluation system. The system composes short pieces of music by choosing some factors in music, such as pitch interval. timbre, tempo, rhythm. The most important features of the composition system include using the concept of mode, and density. mode control the pitch interval and densyty control the rhythm of music. We use Neural Network algorithm for automatic evaluation system of music. especially we used Back Propagation algorithm for objectification of user's taste.
In this paper, the projective non-negative matrix factorization (PNMF) with Bregman divergence is applied into the musical instrument classification. A novel supervised learning algorithm for automatic classification ...
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EEG signals usually were contaminated with unwanted artefacts that may hide some valuable information in the signals. In this paper, we implemented wavelet based image processing techniques known as 1-D Double Density...
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EEG signals usually were contaminated with unwanted artefacts that may hide some valuable information in the signals. In this paper, we implemented wavelet based image processing techniques known as 1-D Double Density and 1-D Double Density Complex for denoising EEG signals at various windows size. The performances of these methods were compared and evaluated by calculating the Root Mean Square Error （RMSE）. The minimum RMSE was achieved at the threshold value of 20. The 1-D Double Density Complex was outperformed 1-D Double Density and was effective in EEG signals denoising.
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