The paper proposes a modification of the pyramid method for constructing algorithms for the difference solution of the d'Alembert equation on a graphics processor in the event of a shortage of video memory. The au...
详细信息
The paper proposes a modification of the pyramid method for constructing algorithms for the difference solution of the d'Alembert equation on a graphics processor in the event of a shortage of video memory. The authors demonstrate the effectiveness of the method on the practical example of dividing the grid area into two sub domains. Acceleration reaches the characteristic for the case of a domain entirely located in the video memory. In the article investigated the effectiveness of using the author's approach depending on the height of the pyramid and showed the boundaries of applicability of the proposed modification.
The proceedings contain 50 papers. The topics discussed include: on high-precision chessboard detection on static scene videos from mobile eye-tracking devices;towards a mobile system for hypertensive outpatients'...
ISBN:
(纸本)9789526865324
The proceedings contain 50 papers. The topics discussed include: on high-precision chessboard detection on static scene videos from mobile eye-tracking devices;towards a mobile system for hypertensive outpatients' treatment adherence improvement;power distribution unit (PDU) for a distributed computing network;analysis of the functioning of a multi-domain transport software-defined network with controlled optical layer;not-holding connections as a characteristic feature of dynamic interactions of elements of technical systems;an algorithm for building an enterprise network topology using widespread data sources;a web of things approach for indoor position monitoring of elderly and impaired people;modular industrial equipment in cyber-physical production system: architecture and integration;a hyper heuristic algorithm for scheduling of fog networks;digital image watermarking using dwt basis matrices;2D SLAM quality evaluation methods;revealing of entities interconnections in system dynamics modelling process by applying multimodal data analysis paradigm;fast and modular regularized topic modelling;and modern methods and algorithms in digital processing of endoscopic images.
Now-a-days roads are monitored by CCTV cameras passively i.e. knowledge is not generated by the CCTV cameras. Human resource constraint i.e. there is very limited posting of the traffic police staff at road crossings ...
详细信息
ISBN:
(纸本)9781538611869
Now-a-days roads are monitored by CCTV cameras passively i.e. knowledge is not generated by the CCTV cameras. Human resource constraint i.e. there is very limited posting of the traffic police staff at road crossings and highway's. In many cases, accidents are reported due to negligence by the road users. Adding to this, even the majority of humans surrounding the accident spot/scene are busy clicking photos and videos unknown of the fact that their little negligence could cost a LIFE. The footage is only seen by the authorities only after a problem has been occurred so as to find the root cause of it. To overcome this, we propose an intelligent system that can make use of the existing CCTV cameras. The proposed system captures video stream, computes the input and the system alerts are generated in real time, which means no additional sensors would be required. U sing camera itself, the plan is to detect accidents in real time and also send alerts to ambulances or medical services; so that appropriate resources needed for saving lives are available in time. Other targets are: to detect vehicles which break the speed limit rules and relay this information to a concerned authority; to monitor restricted roads areas and traffic signal violations, and plan to detect number plates of the violators and find them. Along with this the proposed system will also classify the type of vehicles that run on road, so that further construction of roads can be tailored as per the expected vehicles for smoother traffic flow. In this study we will be taking help of algorithms such as Background Subtraction, Morphological transformations and many other basic concepts to perform the tasks mentioned above. By using technology at its best, the aim is to integrate various factors into one smart system. The project will benefit to reduce cost of road surveillance system and complete automation of road surveillance system.
Demand of multimedia growth, contributes to insufficient bandwidth of network and memory storage device. Therefore data compression is more required for reducing data redundancy to save more hardware space and transmi...
详细信息
ISBN:
(纸本)9781509047611
Demand of multimedia growth, contributes to insufficient bandwidth of network and memory storage device. Therefore data compression is more required for reducing data redundancy to save more hardware space and transmission bandwidth. image compression is one of the main research in the field of imageprocessing. Many techniques are given for image compression. Some of which are discussed in this paper. This paper discusses k-means clustering, 2D-DWT and fuzzy logic based image compression.
This paper is devoted to present technique of the use of imageprocessing for lab-on-a-chip techniques. algorithms and methods for cell detecting, obtaining their parameters and multiparametric cell tracking in lab-on...
详细信息
ISBN:
(纸本)9781509064861
This paper is devoted to present technique of the use of imageprocessing for lab-on-a-chip techniques. algorithms and methods for cell detecting, obtaining their parameters and multiparametric cell tracking in lab-on-a-chip were presented and discussed from the point of real-time detection.
The proceedings contain 105 papers. The special focus in this conference is on Intelligent systems Design and Applications. The topics include: An innovative approach to manage heterogeneous information using relation...
ISBN:
(纸本)9783319534794
The proceedings contain 105 papers. The special focus in this conference is on Intelligent systems Design and Applications. The topics include: An innovative approach to manage heterogeneous information using relational database systems;estimating the number of clusters as a pre-processing step to unsupervised learning;agglomerative and divisive approaches to unsupervised learning in gestalt clusters;improving imputation accuracy in ordinal data using classification;three case studies using agglomerative clustering;a robust and optimally pruned extreme learning machine;investigating the effect of combining text clustering with classification on improving spam email detection;radial basis function neural networks for datasets with missing values;diversification strategies in differential evolution algorithm to solve the protein structure prediction problem;using cluster barycenters for the generalized traveling salesman problem;on pollution attacks in fully connected P2P networks using trusted peers;certification under uncertainties of control methods for multisource elevators;robust and reliable bionic optimization of nonlinear control problems;human detection using biological signals in camera images with privacy aware;nuclei malignancy analysis based on an adaptive bottom-hat filter;test suite prioritization using nature inspired meta-heuristic algorithms;the improvement of an image compression approach using Weber-Fechner law;a minimal rare substructures-based model for graph database indexing;multibiometrics enhancement using quality measurement in score level fusion;effects of random sampling on SVM hyper-parameter tuning and training a spiking neural network to generate online handwriting movements.
Keypoint detection is a basic step in many computer vision algorithms aimed at recognition of objects, automatic navigation, medicine and other application fields. Successful implementation of higher level image analy...
详细信息
ISBN:
(纸本)9781509063451
Keypoint detection is a basic step in many computer vision algorithms aimed at recognition of objects, automatic navigation, medicine and other application fields. Successful implementation of higher level image analysis tasks, however, is conditioned by reliable detection of characteristic image local regions termed keypoints. A large number of keypoint detection algorithms has been proposed and verified. The main part of this work is devoted to description of an original keypoint detection algorithm that incorporates depth information computed from stereovision cameras or other depth sensing devices. It was shown that filtering out keypoints that are context dependent, e.g. located on object boundaries can improve the matching performance of the keypoints which is the basis for object recognition tasks. This improvement was shown quantitatively by comparing the proposed algorithm to the widely accepted SIFT keypoint detector algorithm. Our study is motivated by a development of a system aimed at aiding the visually impaired in space perception and object identification.
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.
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%.
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.
暂无评论