Design and evaluation of bulk data transfer extensions for the NFComms framework
- Bradshaw, Karen L, Irwin, Barry V W, Pennefather, Sean
- Authors: Bradshaw, Karen L , Irwin, Barry V W , Pennefather, Sean
- Date: 2019
- Subjects: To be catalogued
- Language: English
- Type: text , article
- Identifier: http://hdl.handle.net/10962/430369 , vital:72686 , https://hdl.handle.net/10520/EJC-1d75c01e79
- Description: We present the design and implementation of an indirect messaging extension for the existing NFComms framework that provides communication between a network flow processor and host CPU. This extension addresses the bulk throughput limitations of the framework and is intended to work in conjunction with existing communication mediums. Testing of the framework extensions shows an increase in throughput performance of up to 268 that of the current direct message passing framework at the cost of increased single message latency of up to 2. This trade-off is considered acceptable as the proposed extensions are intended for bulk data transfer only while the existing message passing functionality of the framework is preserved and can be used in situations where low latency is required for small messages.
- Full Text:
- Date Issued: 2019
- Authors: Bradshaw, Karen L , Irwin, Barry V W , Pennefather, Sean
- Date: 2019
- Subjects: To be catalogued
- Language: English
- Type: text , article
- Identifier: http://hdl.handle.net/10962/430369 , vital:72686 , https://hdl.handle.net/10520/EJC-1d75c01e79
- Description: We present the design and implementation of an indirect messaging extension for the existing NFComms framework that provides communication between a network flow processor and host CPU. This extension addresses the bulk throughput limitations of the framework and is intended to work in conjunction with existing communication mediums. Testing of the framework extensions shows an increase in throughput performance of up to 268 that of the current direct message passing framework at the cost of increased single message latency of up to 2. This trade-off is considered acceptable as the proposed extensions are intended for bulk data transfer only while the existing message passing functionality of the framework is preserved and can be used in situations where low latency is required for small messages.
- Full Text:
- Date Issued: 2019
Improved palmprint segmentation for robust identification and verification
- Brown, Dane L, Bradshaw, Karen L
- Authors: Brown, Dane L , Bradshaw, Karen L
- Date: 2019
- Subjects: To be catalogued
- Language: English
- Type: text , article
- Identifier: http://hdl.handle.net/10962/460576 , vital:75966 , xlink:href="https://doi.org/10.1109/SITIS.2019.00013"
- Description: This paper introduces an improved approach to palmprint segmentation. The approach enables both contact and contactless palmprints to be segmented regardless of constraining finger positions or whether fingers are even depicted within the image. It is compared with related systems, as well as more comprehensive identification tests, that show consistent results across other datasets. Experiments include contact and contactless palmprint images. The proposed system achieves highly accurate classification results, and highlights the importance of effective image segmentation. The proposed system is practical as it is effective with small or large amounts of training data.
- Full Text:
- Date Issued: 2019
- Authors: Brown, Dane L , Bradshaw, Karen L
- Date: 2019
- Subjects: To be catalogued
- Language: English
- Type: text , article
- Identifier: http://hdl.handle.net/10962/460576 , vital:75966 , xlink:href="https://doi.org/10.1109/SITIS.2019.00013"
- Description: This paper introduces an improved approach to palmprint segmentation. The approach enables both contact and contactless palmprints to be segmented regardless of constraining finger positions or whether fingers are even depicted within the image. It is compared with related systems, as well as more comprehensive identification tests, that show consistent results across other datasets. Experiments include contact and contactless palmprint images. The proposed system achieves highly accurate classification results, and highlights the importance of effective image segmentation. The proposed system is practical as it is effective with small or large amounts of training data.
- Full Text:
- Date Issued: 2019
Linking scales and disciplines: an interdisciplinary cross-scale approach to supporting climate-relevant ecosystem management
- Berger, Christian, Bieri, Mari, Bradshaw, Karen L, Brümmer, Christian, Clemen, Thomas, Hickler, Thomas, Kutsch, Werner Leo, Lenfers, Ulfia A, Martens, Carola, Midgley, Guy F, Mukwashi, Kanisios, Odipo, Victor, Scheiter, Simon, Schmullius, Christiane, Baade, Jussi, du Toit, Justin C, Scholes, Robert J, Smit, Izak P, Stevens, Nicola, Twine, Wayne
- Authors: Berger, Christian , Bieri, Mari , Bradshaw, Karen L , Brümmer, Christian , Clemen, Thomas , Hickler, Thomas , Kutsch, Werner Leo , Lenfers, Ulfia A , Martens, Carola , Midgley, Guy F , Mukwashi, Kanisios , Odipo, Victor , Scheiter, Simon , Schmullius, Christiane , Baade, Jussi , du Toit, Justin C , Scholes, Robert J , Smit, Izak P , Stevens, Nicola , Twine, Wayne
- Date: 2019
- Subjects: To be catalogued
- Language: English
- Type: text , article
- Identifier: http://hdl.handle.net/10962/460589 , vital:75967 , xlink:href="https://doi.org/10.1007/s10584-019-02544-0"
- Description: Southern Africa is particularly sensitive to climate change, due to both ecological and socio-economic factors, with rural land users among the most vulnerable groups. The provision of information to support climate-relevant decision-making requires an understanding of the projected impacts of change and complex feedbacks within the local ecosystems, as well as local demands on ecosystem services. In this paper, we address the limitation of current approaches for developing management relevant socio-ecological information on the projected impacts of climate change and human activities. We emphasise the need for linking disciplines and approaches by expounding the methodology followed in our two consecutive projects. These projects combine disciplines and levels of measurements from the leaf level (ecophysiology) to the local landscape level (flux measurements) and from the local household level (socio-economic surveys) to the regional level (remote sensing), feeding into a variety of models at multiple scales. Interdisciplinary, multi-scaled, and integrated socio-ecological approaches, as proposed here, are needed to compliment reductionist and linear, scale-specific approaches. Decision support systems are used to integrate and communicate the data and models to the local decision-makers.
- Full Text:
- Date Issued: 2019
- Authors: Berger, Christian , Bieri, Mari , Bradshaw, Karen L , Brümmer, Christian , Clemen, Thomas , Hickler, Thomas , Kutsch, Werner Leo , Lenfers, Ulfia A , Martens, Carola , Midgley, Guy F , Mukwashi, Kanisios , Odipo, Victor , Scheiter, Simon , Schmullius, Christiane , Baade, Jussi , du Toit, Justin C , Scholes, Robert J , Smit, Izak P , Stevens, Nicola , Twine, Wayne
- Date: 2019
- Subjects: To be catalogued
- Language: English
- Type: text , article
- Identifier: http://hdl.handle.net/10962/460589 , vital:75967 , xlink:href="https://doi.org/10.1007/s10584-019-02544-0"
- Description: Southern Africa is particularly sensitive to climate change, due to both ecological and socio-economic factors, with rural land users among the most vulnerable groups. The provision of information to support climate-relevant decision-making requires an understanding of the projected impacts of change and complex feedbacks within the local ecosystems, as well as local demands on ecosystem services. In this paper, we address the limitation of current approaches for developing management relevant socio-ecological information on the projected impacts of climate change and human activities. We emphasise the need for linking disciplines and approaches by expounding the methodology followed in our two consecutive projects. These projects combine disciplines and levels of measurements from the leaf level (ecophysiology) to the local landscape level (flux measurements) and from the local household level (socio-economic surveys) to the regional level (remote sensing), feeding into a variety of models at multiple scales. Interdisciplinary, multi-scaled, and integrated socio-ecological approaches, as proposed here, are needed to compliment reductionist and linear, scale-specific approaches. Decision support systems are used to integrate and communicate the data and models to the local decision-makers.
- Full Text:
- Date Issued: 2019
Segmenting objects with indistinct edges, with application to aerial imagery of vegetation
- James, Katherine M F, Bradshaw, Karen L
- Authors: James, Katherine M F , Bradshaw, Karen L
- Date: 2019
- Subjects: To be catalogued
- Language: English
- Type: text , book
- Identifier: http://hdl.handle.net/10962/460614 , vital:75969 , ISBN 9781450372657 , https://doi.org/10.1145/3351108.3351124
- Description: Image segmentation mask creation relies on objects having distinct edges. While this may be true for the objects seen in many image segmentation challenges, it is less so when approaching tasks such as segmentation of vegetation in aerial imagery. Such datasets contain indistinct edges, or areas of mixed information at edges, which introduces a level of annotator subjectivity at edge pixels. Existing loss functions apply equal learning ability to both these pixels of low and high annotation confidence. In this paper, we propose a weight map based loss function that takes into account low confidence in the annotation at edges of objects by down-weighting the contribution of these pixels to the overall loss. We examine different weight map designs to find the most optimal one when applied to a dataset of aerial imagery of vegetation, with the task of segmenting a particular genus of shrub from other land cover types. When compared to inverse class frequency weighted binary cross-entropy loss, we found that using weight map-based loss produced a better performing model than binary cross-entropy loss, improving F1 score by 4%.
- Full Text:
- Date Issued: 2019
- Authors: James, Katherine M F , Bradshaw, Karen L
- Date: 2019
- Subjects: To be catalogued
- Language: English
- Type: text , book
- Identifier: http://hdl.handle.net/10962/460614 , vital:75969 , ISBN 9781450372657 , https://doi.org/10.1145/3351108.3351124
- Description: Image segmentation mask creation relies on objects having distinct edges. While this may be true for the objects seen in many image segmentation challenges, it is less so when approaching tasks such as segmentation of vegetation in aerial imagery. Such datasets contain indistinct edges, or areas of mixed information at edges, which introduces a level of annotator subjectivity at edge pixels. Existing loss functions apply equal learning ability to both these pixels of low and high annotation confidence. In this paper, we propose a weight map based loss function that takes into account low confidence in the annotation at edges of objects by down-weighting the contribution of these pixels to the overall loss. We examine different weight map designs to find the most optimal one when applied to a dataset of aerial imagery of vegetation, with the task of segmenting a particular genus of shrub from other land cover types. When compared to inverse class frequency weighted binary cross-entropy loss, we found that using weight map-based loss produced a better performing model than binary cross-entropy loss, improving F1 score by 4%.
- Full Text:
- Date Issued: 2019
- «
- ‹
- 1
- ›
- »