The tomato (Lycopersicon esculentum) is an herbaceous, usually sprawling plant which belong to Solanaceae or nightshade family. Genetic evidence shows that the progenitors of tomatoes were herbaceous green plants with...
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ISBN:
(纸本)9781424453306
The tomato (Lycopersicon esculentum) is an herbaceous, usually sprawling plant which belong to Solanaceae or nightshade family. Genetic evidence shows that the progenitors of tomatoes were herbaceous green plants with small green *** are a great many (around 7500) tomato varieties grown for various purposes. Their identifications had been studied using various laboratory methods. The morphological and genetical characteristics were employed to classify different tomato cultivars. However, the presence of wide morphological varieties through evolution among various tomato cultivars made it more complex and difficult to classify them. Petioles plays a very crucial role in determining the characteristics of a tomato plant. The number of petioles present, their angle with the leaf stalk or their distance from the stalk represent genetical characteristics which differentiate various cultivars of tomato. This article proposed various methods to find the number of petioles present in a tomato leaf using an image analysis based approach.
This paper proposes an efficient biometrics system based on palmprint. Palmprint ROI is transformed using proposed local edge pattern (LEP). Corner like features are extracted from the enhanced palmprint images as the...
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ISBN:
(纸本)9788132216025;9788132216018
This paper proposes an efficient biometrics system based on palmprint. Palmprint ROI is transformed using proposed local edge pattern (LEP). Corner like features are extracted from the enhanced palmprint images as they are stable and highly discriminative. It has also proposed a distance measure that uses some geometrical and statistical constraints to track corner feature points between two palmprint ROI's. The performance of the proposed system is tested on publicly available PolyU database consisting of 7,752 and CASIA database consisting of 5,239 hand images. The feature extraction as well as matching capabilities of the proposed system are optimized and it is found to perform with CRR of 99.97% with ERR of 0.66% for PolyU and CRR of 100% with ERR of 0.24% on CASIA databases respectively.
In Complex Event Processing (CEP), we deal with how to search through a sequence of incoming events to find a specified and desired pattern. CEP has a broad use in today enterprise. It can act on sent and/or received ...
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ISBN:
(纸本)9781424453306
In Complex Event Processing (CEP), we deal with how to search through a sequence of incoming events to find a specified and desired pattern. CEP has a broad use in today enterprise. It can act on sent and/or received events. The result can generate other events that can be used in different layers of an enterprise system. Growing number of areas dealing with arisen events like Business Activity Monitoring (BAM), Fraud detection and intrusion detection makes CEP a hot topic for researchers. Generating efficient high-performance patterns is the issue which has been addressed in this paper. The pattern can be made from any query given by user. The user defined query is CQL (Continuous Query Language) which is relevant for time series data. NFA (Non-deterministic Finite Automaton) is used for modeling patterns although it has some defects which are addressed The focus of this paper is on developing a rule modeling engine and taking into account the role of historical data to make efficient patterns. We developed some algorithms for each component of proposed model. The results are optimized patterns produced based on historical data and queries given by user. Finally we show that these techniques can be efficient when we deal with high volume event-base data.
Image denoising is an important step in the field of image processing. Presence of noise can lead to various obstacles in the way of proper analysis of images to extract information from it like misinterpretation of d...
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ISBN:
(纸本)9781509061068
Image denoising is an important step in the field of image processing. Presence of noise can lead to various obstacles in the way of proper analysis of images to extract information from it like misinterpretation of data, loss in the usability of the image etc. Denoised images are used in various applications such as in medical diagnosis, ultrasound imaging, satellite imaging, patternrecognition etc. Different image denoising techniques are already in existence that uses different filters to remove noise. Fuzzy logic is a softcomputing technique that allows for approximations and partial truths. The benefit of using fuzzy logic for denoising purpose is to increase the tractability, robustness and effectiveness of the existing traditional denoising methods. This paper presents a novel fuzzy based method for removal of speckle noise, which mostly affects ultrasound and SAR images.
The paper deals with the extraction of features for statistical patternrecognition. Bayes probability of correct classification is adopted as the extraction criterion. The problem with complete probabilistic informat...
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ISBN:
(纸本)9783540695721
The paper deals with the extraction of features for statistical patternrecognition. Bayes probability of correct classification is adopted as the extraction criterion. The problem with complete probabilistic information is discussed and next the Bayes-optirnal feature extraction procedure for the supervised classfication is presented in detail. As method of solution of optimal feature extraction a genetic algorithm is proposed. Several computer experiments for wide spectrum of cases were made and their results demonstrating capability of proposed approach to solve feature extraction problem are presented.
The article examines web mining application in university library search engine. It primarily researches the technology that is personal usage records track in web usage mining. It also discusses how to establish a un...
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This paper is concerned with motion patternrecognition using built-in accelerometers inside of modern mobile devices - smartphones. More and more people are using these devices nowadays without using its full potenti...
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ISBN:
(纸本)9783642330179
This paper is concerned with motion patternrecognition using built-in accelerometers inside of modern mobile devices - smartphones. More and more people are using these devices nowadays without using its full potential for user motion recognition and evaluation. As accelerometer magnitude level comparison is not sufficient for motion patternrecognition morlet wavelet based recognition algorithm is introduced and tested as well as its device implementation is described and tested. Set of basic motion patterns walking, running and shaking with the device is tested and evaluated.
This book constitutes the refereed proceedings of the 5th internationalconference on Information Processing, ICIP 2011, held in Bangalore, India, in August 2011. The 86 revised full papers presented were carefully re...
ISBN:
(数字)9783642227868
ISBN:
(纸本)9783642227851
This book constitutes the refereed proceedings of the 5th internationalconference on Information Processing, ICIP 2011, held in Bangalore, India, in August 2011. The 86 revised full papers presented were carefully reviewed and selected from 514 submissions. The papers are organized in topical sections on data mining; Web mining; artificial intelligence; softcomputing; software engineering; computer communication networks; wireless networks; distributed systems and storage networks; signal processing; image processing and patternrecognition.
This study presents an effective approach to the hitherto little addressed problem of feature assessment and selection for patternrecognition in imprecisely supervised environments. Unlike in classical supervised env...
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This study presents an effective approach to the hitherto little addressed problem of feature assessment and selection for patternrecognition in imprecisely supervised environments. Unlike in classical supervised environments wherein the representative training samples have crisp class labels, here the samples have fuzzy memberships in several of the different pattern classes in the environment. The new methodology reported here is an outgrowth of a recently developed tool CORPS - Class Overlap Region Partitioning Scheme initially designed for operation in supervised environments and extended later for operation in imperfectly supervised environments. The emphasis here has been the development of a computationally efficient scheme capable of evaluating as rapidly as practical a large number of features individually as to their discrimination potential based on which a smaller subset may be selected, if so desired, for more detailed evaluation in different combinations by other tools.
recognition of human sketches is one of the most interesting and difficult issues in image recognition. Recently, deep convolutional neural networks (DCNNs) have been successfully applied to various image recognition ...
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ISBN:
(纸本)9781509049172
recognition of human sketches is one of the most interesting and difficult issues in image recognition. Recently, deep convolutional neural networks (DCNNs) have been successfully applied to various image recognition tasks. Though the DCNN is a very powerful method, the high computational effort required to tune its hyperparameters represents a critical problem. In this paper, we propose a novel method called evolutionary deep learning (evoDL) that uses a genetic algorithm in order to obtain effective deep learning networks. The generalization ability of the network structure obtained using the proposed method is confirmed by a computer experiment.
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