- Unstructured data processing algorithms, such as Detection, Recognition and Identification (DRI) algorithms, which are widely used in the civilian world on RGB images and which can be transposed to other types of images (SAR, Infrared, hyperspectral...), or audio processing algorithms which can have variations for data such as radar, sonar....
- Anomaly detection technologies that allow, among other things, the exploitation of data when labels are not necessarily available.
- Luring, in particular neural networks or any other attack targeting AI, which can pose security problems in some applications using AI.
- Technologies allowing to qualify AI, i.e. to provide evidence and guarantees on the functioning of AI whether it is empirical measurements or formal evidence; methodologies/metrics allowing to qualify a learning or test database.
- Confidentiality of training data, i.e. the possibility or not to trace back to potentially classified training data characteristics.
- Finally, AI algorithms must also be able to be embedded on compact systems with low power consumption. Thus all technologies allowing to reach this goal (quantification, approximation) and what they imply (performance, robustness, qualification) are of interest.
CAID 2020 Conference
This year, the CAID conference proposes a special session dedicated to the use of Artificial Intelligence and/or Datascience for crisis management. In this framework, applied contributions to the fight against COVID 19 are welcome. The CAID conference is intended to be educational and presents issues related to artificial intelligence to an audience that may be new to this field. It is within this framework that we invite actors from all fields (academic research, industry, defence...) to submit publications related to one of the topics in the field of artificial intelligence and defence.How to submit
Submission of articles before Monday 31 August 2020 via the following url in PDF format: https://easychair.org/conferences/?conf=caid2020 It should include the title of the paper, the first and last names of the authors and their affiliation, the e-mail address of the main author, an abstract (10 lines max.) and a list of keywords. The paper should be a maximum of 8 pages, A4 format, following the Springer Lecture Notes in Computer Science model.- LaTeX model: ftp://ftp.springernature.com/cs-proceeding/llncs/llncs2e.zip ;
- Word template: ftp://ftp.springernature.com/cs-proceeding/llncs/word/splnproc1703.zip.
Programme Committee
- Alain DRONIOU (DGA)
- Guillaume QUIN (MBDA)
- Alexis OLIVEREAU (CEA)
- Christophe MEYER (THALES)
- Adrien CHAN HON TONG (ONERA)
- Judicaël MENANT (DGA)
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