Construction Approach

14,000,000 Leading Edge Experts on the ideXlab platform

Scan Science and Technology

Contact Leading Edge Experts & Companies

Scan Science and Technology

Contact Leading Edge Experts & Companies

The Experts below are selected from a list of 549342 Experts worldwide ranked by ideXlab platform

Jocelyn Chanussot - One of the best experts on this subject based on the ideXlab platform.

  • hyperspectral image segmentation using a new spectral unmixing based binary partition tree representation
    IEEE Transactions on Image Processing, 2014
    Co-Authors: Miguel Angel Veganzones, Guillaume Tochon, Mauro Dallamura, Jocelyn Chanussot
    Abstract:

    The binary partition tree (BPT) is a hierarchical region-based representation of an image in a tree structure. The BPT allows users to explore the image at different segmentation scales. Often, the tree is pruned to get a more compact representation and so the remaining nodes conform an optimal partition for some given task. Here, we propose a novel BPT Construction Approach and pruning strategy for hyperspectral images based on spectral unmixing concepts. Linear spectral unmixing consists of finding the spectral signatures of the materials present in the image (endmembers) and their fractional abundances within each pixel. The proposed methodology exploits the local unmixing of the regions to find the partition achieving a global minimum reConstruction error. Results are presented on real hyperspectral data sets with different contexts and resolutions.

  • Hyperspectral image segmentation using a new spectral mixture-based binary partition tree representation
    2013
    Co-Authors: Miguel Angel Veganzones, Guillaume Tochon, Mauro Dalla Mura, Jocelyn Chanussot
    Abstract:

    The Binary Partition Tree (BPT) is a hierarchical region-based representation of an image in a tree structure. BPT allows users to explore the image at different segmentation scales, from fine partitions close to the leaves to coarser partitions close to the root. Often, the tree is pruned so the leaves of the resulting pruned tree conform an optimal partition given some optimality criterion. Here, we propose a novel BPT Construction Approach and pruning strategy for hyperspectral images based on spectral unmixing concepts. The proposed methodology exploits the local unmixing of the regions to find the partition achieving a global minimum reConstruction error. We successfully tested the proposed Approach on the well-known Cuprite hyperspectral image collected by NASA Jet Propulsion Laboratory's Airborne Visible/Infrared Imaging Spectrometer (AVIRIS). This scene is considered as a standard benchmark to validate spectral unmixing algorithms.

Lisa Feldman Barrett - One of the best experts on this subject based on the ideXlab platform.

  • considering ptsd from the perspective of brain processes a psychological Construction Approach
    Journal of Traumatic Stress, 2011
    Co-Authors: Michael K Suvak, Lisa Feldman Barrett
    Abstract:

    Posttraumatic stress disorder (PTSD) is a complex psychiatric disorder that involves symptoms from various domains that appear to be produced by the combination of several mechanisms. The authors contend that existing neural accounts fail to provide a viable model that explains the emergence and maintenance of PTSD and the associated heterogeneity in the expression of this disorder (cf. Garfinkel & Liberzon, 2009). They introduce a psychological Construction Approach as a novel framework to probe the brain basis of PTSD, where distributed networks within the human brain are thought to correspond to the basic psychological ingredients of the mind. The authors posit that it is the combination of these ingredients that produces the heterogeneous symptom clusters in PTSD. Their goal is show that a Constructionist Approach has significant heuristic value in understanding the emergence and maintenance of PTSD symptoms, and leads to different and perhaps more useful conjectures about the origins and maintenance of the syndrome than the traditional hyperreactive fear account.

  • variety is the spice of life a psychological Construction Approach to understanding variability in emotion
    Cognition & Emotion, 2009
    Co-Authors: Lisa Feldman Barrett
    Abstract:

    There is remarkable variety in emotional life. Not all mental states referred to by the same word (e.g., “fear”) look alike, feel alike, or have the same neurophysiological signature. Variability has been observed within individuals over time, across individuals from the same culture, and of course across cultures. In this paper, I outline an Approach to understanding the richness and diversity of emotional life. This model, called the conceptual act model, is not only well suited to explaining individual differences in the frequency and quality of emotion, but it also suggests the counter-intuitive view that the variety in emotional life extends past the boundaries of events that are conventionally called “emotion” to other classes of psychological events that people call by different names, such as “cognitions”. As a result, the conceptual act model is a unifying account of the broad variety of mental states that constitute the human mind.

Paul Van Dooren - One of the best experts on this subject based on the ideXlab platform.

Miguel Angel Veganzones - One of the best experts on this subject based on the ideXlab platform.

  • hyperspectral image segmentation using a new spectral unmixing based binary partition tree representation
    IEEE Transactions on Image Processing, 2014
    Co-Authors: Miguel Angel Veganzones, Guillaume Tochon, Mauro Dallamura, Jocelyn Chanussot
    Abstract:

    The binary partition tree (BPT) is a hierarchical region-based representation of an image in a tree structure. The BPT allows users to explore the image at different segmentation scales. Often, the tree is pruned to get a more compact representation and so the remaining nodes conform an optimal partition for some given task. Here, we propose a novel BPT Construction Approach and pruning strategy for hyperspectral images based on spectral unmixing concepts. Linear spectral unmixing consists of finding the spectral signatures of the materials present in the image (endmembers) and their fractional abundances within each pixel. The proposed methodology exploits the local unmixing of the regions to find the partition achieving a global minimum reConstruction error. Results are presented on real hyperspectral data sets with different contexts and resolutions.

  • Hyperspectral image segmentation using a new spectral mixture-based binary partition tree representation
    2013
    Co-Authors: Miguel Angel Veganzones, Guillaume Tochon, Mauro Dalla Mura, Jocelyn Chanussot
    Abstract:

    The Binary Partition Tree (BPT) is a hierarchical region-based representation of an image in a tree structure. BPT allows users to explore the image at different segmentation scales, from fine partitions close to the leaves to coarser partitions close to the root. Often, the tree is pruned so the leaves of the resulting pruned tree conform an optimal partition given some optimality criterion. Here, we propose a novel BPT Construction Approach and pruning strategy for hyperspectral images based on spectral unmixing concepts. The proposed methodology exploits the local unmixing of the regions to find the partition achieving a global minimum reConstruction error. We successfully tested the proposed Approach on the well-known Cuprite hyperspectral image collected by NASA Jet Propulsion Laboratory's Airborne Visible/Infrared Imaging Spectrometer (AVIRIS). This scene is considered as a standard benchmark to validate spectral unmixing algorithms.

Peter Benner - One of the best experts on this subject based on the ideXlab platform.

Construction Approach - 15 days free trial to Access Experts & Abstracts