Results 11 to 20 of about 114,821 (305)

Experiment design of the International CLIVAR C20C+ Detection and Attribution project [PDF]

Weather and Climate Extremes, 2019
There is a growing research interest in understanding extreme weather in the context of anthropogenic climate change, posing a requirement for new tailored climate data products.
Dáithí A. Stone, Nikolaos Christidis, Chris Folland, Sarah Perkins-Kirkpatrick, Judith Perlwitz, Hideo Shiogama, Michael F. Wehner, Piotr Wolski, Shreyas Cholia, Harinarayan Krishnan, Donald Murray, Oliver Angélil, Urs Beyerle, Andrew Ciavarella, Andrea Dittus, Xiao-Wei Quan, Mark Tadross   +16 more
doaj   +2 more sources

A framework for the detection and attribution of biodiversity change. [PDF]

Philos Trans R Soc Lond B Biol Sci, 2023
The causes of biodiversity change are of great scientific interest and central to policy efforts aimed at meeting biodiversity targets. Changes in species diversity and high rates of compositional turnover have been reported worldwide.
Gonzalez A, Chase JM, O'Connor MI.
europepmc   +2 more sources

Attribute-Aware Pedestrian Detection in a Crowd [PDF]

IEEE Transactions on Multimedia, 2021
Pedestrian detection is an initial step to perform outdoor scene analysis, which plays an essential role in many real-world applications. Although having enjoyed the merits of deep learning frameworks from the generic object detectors, pedestrian detection is still a very challenging task due to heavy occlusion and highly crowded group.
Jialiang Zhang, Lixiang Lin, Jianke Zhu, Yang Li 0041, Yun-chen Chen, Yao Hu, Steven C. H. Hoi   +6 more
openaire   +3 more sources

Open-vocabulary Attribute Detection

2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023
Vision-language modeling has enabled open-vocabulary tasks where predictions can be queried using any text prompt in a zero-shot manner. Existing open-vocabulary tasks focus on object classes, whereas research on object attributes is limited due to the lack of a reliable attribute-focused evaluation benchmark.
María Alejandra Bravo, Sudhanshu Mittal, Simon Ging, Thomas Brox   +3 more
openaire   +3 more sources

Attribute Restoration Framework for Anomaly Detection [PDF]

IEEE Transactions on Multimedia, 2022
With the recent advances in deep neural networks, anomaly detection in multimedia has received much attention in the computer vision community. While reconstruction-based methods have recently shown great promise for anomaly detection, the information equivalence among input and supervision for reconstruction tasks can not effectively force the network
Fei Ye, Chaoqin Huang, Jinkun Cao, Maosen Li, Ya Zhang 0002, Cewu Lu   +5 more
openaire   +2 more sources

Community detection in Attributed Network [PDF]

Companion of the The Web Conference 2018 on The Web Conference 2018 - WWW '18, 2018
Graph clustering techniques are very useful for detecting densely connected groups in large graphs. Many existing graph clustering methods mainly focus on the topological structure, but ignore the vertex properties. Existing graph clustering methods have been recently extended to deal with nodes attribute. First we motivate the interest in the study of
Issam Falih, Nistor Grozavu, Rushed Kanawati, Younès Bennani   +3 more
openaire   +1 more source

Color attributes for object detection [PDF]

2012 IEEE Conference on Computer Vision and Pattern Recognition, 2012
State-of-the-art object detectors typically use shape information as a low level feature representation to capture the local structure of an object. This paper shows that early fusion of shape and color, as is popular in image classification, leads to a significant drop in performance for object detection.
Fahad Shahbaz Khan, Rao Muhammad Anwer, Joost van de Weijer 0001, Andrew D. Bagdanov, María Vanrell 0001, Antonio M. López 0001   +5 more
openaire   +1 more source

Detecting Errors in Numeric Attributes [PDF]

, 2014
To detect errors in numeric data, this paper proposes numeric functional dependencies (NFDs), a class of dependencies that allow us to specify arithmetic relationships among numeric attributes. We show that NFDs subsume conditional functional dependencies (CFDs); hence, we can catch data inconsistencies, numeric or not, in a uniform logic framework by ...
Grace Fan, Wenfei Fan, Floris Geerts
openaire   +3 more sources

Outlying property detection with numerical attributes [PDF]

Data Mining and Knowledge Discovery, 2016
The outlying property detection problem is the problem of discovering the properties distinguishing a given object, known in advance to be an outlier in a database, from the other database objects. In this paper, we analyze the problem within a context where numerical attributes are taken into account, which represents a relevant case left open in the ...
ANGIULLI, Fabrizio, FASSETTI, Fabio, Manco G, PALOPOLI, Luigi   +3 more
openaire   +8 more sources

Detection of interdependences in attribute selection [PDF]

, 1998
220
Javier Lorenzo 0001, Mario Hernández, Juan Méndez   +2 more
openaire   +3 more sources