The problem of histogram thresholding is tackled using a modular expert network. The modular expert network is a network of expert modules modulated by a gating network. The expert modules incorporate individual experts’ opinions on the thresholding problem. The difficult task of integration of conflicting experts’ opinions is achieved through a training of the gating network using backpropagat...

Existing multimedia applications are developed by media production specialists, usually delivered on read–only storage medium (CD–ROM, Videodiscs), exhibit huge initial startup cost, do not provide any intelligent control, require specialized hardware and/or software, modification and upgrades are expensive and time consuming, and are suitable for stable and often generic subject matters. This ...

Part of speech taggers generally perform well on homogeneous data sets, but their performance often varies considerably across different genres. In this paper we investigate the adaptation of POS taggers to individual genres by creating POS tagging experts. We use topic modeling to determine genres automatically and then build a tagging expert for each genre. We use Latent Dirichlet Allocation ...

We present a framework for liver surgery training with the focus on therapy decision making, tumor resection and ablation planning based on patient individual data. In this framework we combine state of the art planning facilities with components for training of oncologic liver surgery planning. Guide’n’Support , Intervention-StrategySets, and Comparison-to-Experts-Plan functionality are implem...

This study assessed the intracultural knowledge of the use of medicinal plants in an urban-rural community in an Atlantic forest fragment in northeastern Brazil. We examined the importance of native and exotic species and the effects of gender and age on that knowledge. We also compared data obtained from different groups of informants (local experts and general community). We conducted 194 int...

Using biodiversity management within New Zealand's agricultural landscape as a case study, we apply ‘boundary science’ approaches to overcome two persistent deficiencies in environmental decision-making: ‘evidence disparity’, the discrepancy between evidence desired and generated, complacency’, where is not sought or used, out of date, incomplete biased. Specifically, assess how recent innovati...

In this paper, we explore a geo-spatial learning-to-rank framework for identifying local experts. Three of the key features of the proposed approach are: (i) a learning-based framework for integrating multiple factors impacting local expertise that leverages the fine-grained GPS coordinates of millions of social media users; (ii) a location-sensitive random walk that propagates crowd knowledge ...

The mixtures-of-experts (ME) methodology provides a tool of classii-cation when experts of logistic regression models or Bernoulli models are mixed according to a set of local weights. We show that the Vapnik-Chervonenkis (VC) dimension of the mixtures-of-experts architecture is bounded below by the number of experts m, and is bounded above by O(m 4 s 2), where s is the dimension of the input. ...