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1.
ABSTRACTThis paper proposes the multiple-hypotheses image segmentation and feed-forward neural network classifier for food recognition to improve the performance. Initially, the food or meal image is given as input. Then, the segmentation is applied to identify the regions, where a particular food item is located using salient region detection, multi-scale segmentation, and fast rejection. Then, the features of every food item are extracted by the global feature and local feature extraction. After the features are obtained, the classification is performed for each segmented region using a feed-forward neural network model. Finally, the calorie value is computed with the aid of (i) food volume and (ii) calorie and nutrition measure based on mass value. The experimental results and performance evaluation are validated. The outcome of the proposed method attains 0.947 for Macro Average Accuracy (MAA) and 0.959 for Standard Accuracy (SA), which provides better classification performance. 相似文献
2.
Many models of spoken word recognition posit the existence of lexical and sublexical representations, with excitatory and inhibitory mechanisms used to affect the activation levels of such representations. Bottom-up evidence provides excitatory input, and inhibition from phonetically similar representations leads to lexical competition. In such a system, long words should produce stronger lexical activation than short words, for 2 reasons: Long words provide more bottom-up evidence than short words, and short words are subject to greater inhibition due to the existence of more similar words. Four experiments provide evidence for this view. In addition, reaction-time-based partitioning of the data shows that long words generate greater activation that is available both earlier and for a longer time than is the case for short words. As a result, lexical influences on phoneme identification are extremely robust for long words but are quite fragile and condition-dependent for short words. Models of word recognition must consider words of all lengths to capture the true dynamics of lexical activation. (PsycINFO Database Record (c) 2010 APA, all rights reserved) 相似文献
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Reading requires the orchestration of visual, attentional, language-related, and oculomotor processing constraints. This study replicates previous effects of frequency, predictability, and length of fixated words on fixation durations in natural reading and demonstrates new effects of these variables related to 144 sentences. Such evidence for distributed processing of words across fixation durations challenges psycholinguistic immediacy-of-processing and eye-mind assumptions. Most of the time the mind processes several words in parallel at different perceptual and cognitive levels. Eye movements can help to unravel these processes. (PsycINFO Database Record (c) 2010 APA, all rights reserved) 相似文献
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孙耀华 《石油地球物理勘探》2003,38(1):17-21
地震勘探技术应用可以分为以二维地震研究构造为主的地震勘探初级阶段、以地震地层学为主的地震勘探中级阶段、以三维地震油藏静态描述为主的地震勘探高级阶段、以地震储层研究为主的开发地震妆级阶段和以四维地震进行油藏监测为主的开发地震高级阶段。针对5个不同阶段的地质条件和地质任务,选择使用合理的地震勘探技术是有效提高勘探开发效益的重要途径。焉耆盆地的勘探开发体现了以地震勘探为主的思路,在勘探开发过程中重视了针对不同勘探开发阶段和不同的地质 地震技术,因此,在早期勘探开发中取得了很好的经济效益。 相似文献
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Why are human observers particularly sensitive to human movement? Seven experiments examined the roles of visual experience and motor processes in human movement perception by comparing visual sensitivities to point-light displays of familiar, unusual, and impossible gaits across gait-speed and identity discrimination tasks. In both tasks, visual sensitivity to physically possible gaits was superior to visual sensitivity to physically impossible gaits, supporting perception-action coupling theories of human movement perception. Visual experience influenced walker-identity perception but not gait-speed discrimination. Thus, both motor experience and visual experience define visual sensitivity to human movement. An ecological perspective can be used to define the conditions necessary for experience-dependent sensitivity to human movement. (PsycINFO Database Record (c) 2010 APA, all rights reserved) 相似文献
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In this article, we describe a knowledge-based controlled platform using program supervision techniques. This platform eases
the creation and the configuration of video surveillance systems. Several issues need to be addressed to provide a correct
system configuration: (1) to choose, among a library of programs, those which are best satisfying a given user request, (2)
to assign a correct value for each program parameter, (3) to evaluate performances and to guarantee a performance rate which
is satisfactory regarding end-user requirements. This platform is composed of three main components: the library of programs,
the knowledge base and the control component. The knowledge is either given by experts or learnt by the system. The control
is generic in the sense that it is independent of any application. To validate this platform, we have built and evaluated
six video surveillance systems which are featured with three properties: adaptability, reliability and real-time processing. 相似文献
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