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Author |
Cristina L. Abad; Yi Lu; Roy H. Campbell |
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Title  |
DARE: Adaptive Data Replication for Efficient Cluster Scheduling |
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Conference Article |
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2011 |
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IEEE International Conference on Cluster Computing, 2011 |
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159 - 168 |
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MapReduce, replication, scheduling, locality |
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Placing data as close as possible to computation is a common practice of data intensive systems, commonly referred to as the data locality problem. By analyzing existing production systems, we confirm the benefit of data locality and find that data have different popularity and varying correlation of accesses. We propose DARE, a distributed adaptive data replication algorithm that aids the scheduler to achieve better data locality. DARE solves two problems, how many replicas to allocate for each file and where to place them, using probabilistic sampling and a competitive aging algorithm independently at each node. It takes advantage of existing remote data accesses in the system and incurs no extra network usage. Using two mixed workload traces from Facebook, we show that DARE improves data locality by more than 7 times with the FIFO scheduler in Hadoop and achieves more than 85% data locality for the FAIR scheduler with delay scheduling. Turnaround time and job slowdown are reduced by 19% and 25%, respectively. |
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English |
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yes |
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Call Number |
cidis @ cidis @ |
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21 |
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Author |
Jorge L. Charco; Boris X. Vintimilla; Angel D. Sappa |
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Title |
Deep learning based camera pose estimation in multi-view environment. |
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Conference Article |
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2018 |
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14th IEEE International Conference on Signal Image Technology & Internet based Systems (SITIS 2018) |
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224-228 |
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This paper proposes to use a deep learning network architecture for relative camera pose estimation on a multi-view environment. The proposed network is a variant architecture of AlexNet to use as regressor for prediction the relative translation and rotation as output. The proposed approach is trained from scratch on a large data set that takes as input a pair of images from the same scene. This new architecture is compared with a previous approach using standard metrics, obtaining better results on the relative camera pose. |
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no |
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gtsi @ user @ |
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93 |
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Author |
Henry O. Velesaca; Raul A. Mira; Patricia L. Suarez; Christian X. Larrea; Angel D. Sappa. |
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Title |
Deep Learning based Corn Kernel Classification. |
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Conference Article |
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Year |
2020 |
Publication |
The 1st International Workshop and Prize Challenge on Agriculture-Vision: Challenges & Opportunities for Computer Vision in Agriculture on the Conference Computer on Vision and Pattern Recongnition (CVPR 2020) |
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2020-June |
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9150684 |
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294-302 |
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This paper presents a full pipeline to classify sample sets of corn kernels. The proposed approach follows a segmentation-classification scheme. The image segmentation is performed through a well known deep learning based
approach, the Mask R-CNN architecture, while the classification is performed by means of a novel-lightweight network specially designed for this task—good corn kernel, defective corn kernel and impurity categories are considered.
As a second contribution, a carefully annotated multitouching corn kernel dataset has been generated. This dataset has been used for training the segmentation and
the classification modules. Quantitative evaluations have been performed and comparisons with other approaches provided showing improvements with the proposed pipeline. |
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21607508 |
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978-172819360-1 |
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no |
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cidis @ cidis @ |
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124 |
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Author |
Patricia Suarez, Henry Velesaca, Dario Carpio, Angel Sappa, Patricia Urdiales, Francisca Burgos |
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Title |
Deep Learning based Shrimp Classification |
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Conference Article |
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2022 |
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17th International Symposium on Visual Computing, San Diego, USA, Octubre 3-5. Lecture Notes in Computer Science (LNCS) |
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13598 LNCS |
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36-45 |
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no |
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cidis @ cidis @ |
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194 |
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Author |
Boris Vintimilla, Jorge Vulgarin, Henry Velesaca |
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Title |
Deep Learning-based Human Height Estimation from a Stereo Vision System |
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Conference Article |
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2023 |
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IEEE 13th International Conference on Pattern Recognition Systems (ICPRS) 2023, julio 4-7 |
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979-835033337-4 |
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no |
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Call Number |
cidis @ cidis @ |
Serial |
215 |
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Author |
Henry Velesaca, Boris Vintimilla, Jorge Vulgarin, Coen Antens & Alberto Rubio Pérez |
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Title |
Deep Learning-based Multimodal Sensing Framework for AntiSpoofing Systems |
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Journal Article |
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Year |
2024 |
Publication |
In Fourth International Conference on Innovations in Computational Intelligence and Computer Vision (ICICV 2024) |
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no |
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cidis @ cidis @ |
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238 |
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Author |
Patricia L. Suárez, Angel D. Sappa and Boris X. Vintimilla |
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Title |
Deep learning-based vegetation index estimation |
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Book Chapter |
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Year |
2021 |
Publication |
Generative Adversarial Networks for Image-to-Image Translation Book. |
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Chapter 9 |
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Issue 2 |
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205-232 |
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Call Number |
cidis @ cidis @ |
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137 |
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Author |
Xavier Soria, Angel Sappa, Patricio Humanante, Arash Akbarinia |
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Title |
Dense extreme inception network for edge detection. |
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Journal Article |
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Year |
2023 |
Publication |
Pattern Recognition |
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Vol. 139 |
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00313203 |
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Call Number |
cidis @ cidis @ |
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216 |
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Author |
Xavier Soria; Edgar Riba; Angel D. Sappa |
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Title |
Dense Extreme Inception Network: Towards a Robust CNN Model for Edge Detection |
Type |
Conference Article |
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Year |
2020 |
Publication |
2020 IEEE Winter Conference on Applications of Computer Vision (WACV) |
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9093290 |
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1912-1921 |
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Abstract |
This paper proposes a Deep Learning based edge de- tector, which is inspired on both HED (Holistically-Nested Edge Detection) and Xception networks. The proposed ap- proach generates thin edge-maps that are plausible for hu- man eyes; it can be used in any edge detection task without previous training or fine tuning process. As a second contri- bution, a large dataset with carefully annotated edges, has been generated. This dataset has been used for training the proposed approach as well the state-of-the-art algorithms for comparisons. Quantitative and qualitative evaluations have been performed on different benchmarks showing im- provements with the proposed method when F-measure of ODS and OIS are considered. |
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978-172816553-0 |
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no |
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cidis @ cidis @ |
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126 |
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Author |
Patricia L. Suarez, Dario Carpio, Angel Sappa |
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Title |
Depth Map Estimation from a Single 2D Image |
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Conference Article |
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2023 |
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17th International Conference On Signal Image Technology & Internet Based Systems |
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cidis @ cidis @ |
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226 |
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