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Artificial Intelligence (Latest Articles)

 

Latest indexed articles for 'Artificial Intelligence'

Articles 91 to 100 of 200:

Statistical models of sets of curves and surfaces based on currents.

15 Jul 2009 Computing, visualizing and interpreting statistics on shapes like curves or surfaces is a real challenge with many applications ranging from medical image analysis to computer graphics. Modeling such geometrical primitives with currents avoids to ...
rec_pub_19679507-statistical-models-sets-curves-surfaces-based-currents.htm


Incorporating rich background knowledge for gene named entity classification and recognition.

15 Jul 2009 BACKGROUND: Gene named entity classification and recognition are crucial preliminary steps of text mining in biomedical literature. Machine learning based methods have been used in this area with great success. In most state-of-the-art systems, ...
rec_pub_19615051-incorporating-rich-background-knowledge-gene-named-entity.htm


Foundations for a new science of learning.

15 Jul 2009 Human learning is distinguished by the range and complexity of skills that can be learned and the degree of abstraction that can be achieved compared with those of other species. Homo sapiens is also the only species that has developed formal ways ...
rec_pub_19608908-foundations-new-science-learning.htm


Constrained non-rigid registration for use in image-guided adaptive radiotherapy.

14 Jul 2009 A constrained non-rigid registration (CNRR) algorithm for use in prostate image-guided adaptive radiotherapy is presented in a coherent mathematical framework. The registration algorithm is based on a global rigid transformation combined with a ...
rec_pub_19682945-constrained-non-rigid-registration-use-image-guided-adaptive.htm


Aceto-white temporal pattern classification using k-NN to identify precancerous cervical lesion in colposcopic images.

13 Jul 2009 After Pap smear test, colposcopy is the most used technique to diagnose cervical cancer due to its higher sensitivity and specificity. One of the most promising approaches to improve the colposcopic test is the use of the aceto-white temporal ...
rec_pub_19608162-aceto-white-temporal-pattern-classification-using-k-nn-identify.htm


Automated Arabidopsis plant root cell segmentation based on SVM classification and region merging.

12 Jul 2009 To obtain development information of individual plant cells, it is necessary to perform in vivo imaging of the specimen under study, through time-lapse confocal microscopy. Automation of cell detection/marking process is important to provide ...
rec_pub_19604506-automated-arabidopsis-plant-root-cell-segmentation-based-svm.htm


Segmented-memory recurrent neural networks.

12 Jul 2009 Conventional recurrent neural networks (RNNs) have difficulties in learning long-term dependencies. To tackle this problem, we propose an architecture called segmented-memory recurrent neural network (SMRNN). A symbolic sequence is broken into ...
rec_pub_19605323-segmented-memory-recurrent-neural-networks.htm


Automated voxel-based 3D cortical thickness measurement in a combined Lagrangian-Eulerian PDE approach using partial volume maps.

8 Jul 2009 Accurate cortical thickness estimation is important for the study of many neurodegenerative diseases. Many approaches have been previously proposed, which can be broadly categorised as mesh-based and voxel-based. While the mesh-based approaches can ...
rec_pub_19648050-automated-voxel-based-3d-cortical-thickness-measurement-combined.htm


BAM learning of nonlinearly separable tasks by using an asymmetrical output function and reinforcement learning.

8 Jul 2009 Most bidirectional associative memory (BAM) networks use a symmetrical output function for dual fixed-point behavior. In this paper, we show that by introducing an asymmetry parameter into a recently introduced chaotic BAM output function, prior ...
rec_pub_19596635-bam-learning-nonlinearly-separable-tasks-using-asymmetrical-output.htm


Model selection criteria for image restoration.

8 Jul 2009 In this brief, the image restoration problem is approached as a learning system problem, in which a model is to be selected and parameters are estimated. Although the parameters which correspond to the restored image can easily be obtained, their ...
rec_pub_19596633-model-selection-criteria-image-restoration.htm

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