Difference between revisions of "Kaggle Competitions"

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(→‎Passenger Screening Algorithm Challenge)
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[http://www.youtube.com/results?search_query=Passenger+Screening+Challenge+kaggle Youtube search...]
 
[http://www.youtube.com/results?search_query=Passenger+Screening+Challenge+kaggle Youtube search...]
  
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* [http://www.kaggle.com/c/passenger-screening-algorithm-challenge/discussion/45805 Passenger Screening Algorithm Challenge]
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* [http://www.kaggle.com/c/passenger-screening-algorithm-challenge Passenger Screening Algorithm Challenge]
 
** [http://www.kaggle.com/c/passenger-screening-algorithm-challenge/discussion/45805 1st Place | idle_speculation]
 
** [http://www.kaggle.com/c/passenger-screening-algorithm-challenge/discussion/45805 1st Place | idle_speculation]
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** [http://github.com/mmuneebs/screening 10th Place | MoeJoe (Shayan) ]
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** [http://suchir.io/posts/passenger-screening-algorithm-challenge-writeup.html 7th Place | Suchir Balaji]
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** [http://github.com/mmuneebs/screening Muneeb Saleem]
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** [http://github.com/ShayanPersonal/Kaggle-Passenger-Screening-Challenge-Solution 10th Place | MoeJoe (Shayan)]
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** [http://www.kaggle.com/tensorflight/discussion 32nd Place | TensorFlight]
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** [http://github.com/mmuneebs/screening ? | Muneeb Saleem]
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** [http://github.com/trueb2/passenger-screening ? | trueb2]
  
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While long lines and frantically shuffling luggage into plastic bins isn’t a fun experience, airport security is a critical and necessary requirement for safe travel.  
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About the Challenge: The Department of Homeland Security (DHS) gives notice of the availability of the “Department of Homeland Security’s Person Screening Algorithm Challenge Prize Competition and rules.” The DHS Science and Technology Directorate ( S&T) Homeland Security Advanced Research Projects Agency (HSARPA) Explosives Division (EXD) and the Transportation Security Administration (TSA) (Competition Sponsor) are seeking new automated detection algorithms from individuals and entities that improve the speed, accuracy, and detection of small threat objects and other prohibited items during the airport passenger screening process. Algorithms developed from this Competition, or through further research and development under a limited intellectual property use agreement, have the potential to improve the speed, the detection of prohibited items, and the accuracy of Advanced Imaging Technology (AIT) scanners. A comprehensive set of new automated detection algorithms have the potential to be integrated into the latest screening equipment.
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No one understands the need for both thorough security screenings and short wait times more than U.S. Transportation Security Administration (TSA). They’re responsible for all U.S. airport security, screening more than two million passengers daily. As part of their Apex Screening at Speed Program, DHS has identified high false alarm rates as creating significant bottlenecks at the airport checkpoints. Whenever TSA’s sensors and algorithms predict a potential threat, TSA staff needs to engage in a secondary, manual screening process that slows everything down. And as the number of travelers increase every year and new threats develop, their prediction algorithms need to continually improve to meet the increased demand. Currently, TSA purchases updated algorithms exclusively from the manufacturers of the scanning equipment used. These algorithms are proprietary, expensive, and often released in long cycles. In this competition, TSA is stepping outside their established procurement process and is challenging the broader data science community to help improve the accuracy of their threat prediction algorithms. Using a dataset of images collected on the latest generation of scanners, participants are challenged to identify the presence of simulated threats under a variety of object types, clothing types, and body types. Even a modest decrease in false alarms will help TSA significantly improve the passenger experience while maintaining high levels of security.
 
  
 
* [http://github.com/suhangpro/mvcnn Multi-view CNN (MVCNN) for shape recognition]
 
* [http://github.com/suhangpro/mvcnn Multi-view CNN (MVCNN) for shape recognition]

Revision as of 11:36, 23 May 2018

Youtube search...

Passenger Screening Algorithm Challenge

Youtube search...

About the Challenge: The Department of Homeland Security (DHS) gives notice of the availability of the “Department of Homeland Security’s Person Screening Algorithm Challenge Prize Competition and rules.” The DHS Science and Technology Directorate ( S&T) Homeland Security Advanced Research Projects Agency (HSARPA) Explosives Division (EXD) and the Transportation Security Administration (TSA) (Competition Sponsor) are seeking new automated detection algorithms from individuals and entities that improve the speed, accuracy, and detection of small threat objects and other prohibited items during the airport passenger screening process. Algorithms developed from this Competition, or through further research and development under a limited intellectual property use agreement, have the potential to improve the speed, the detection of prohibited items, and the accuracy of Advanced Imaging Technology (AIT) scanners. A comprehensive set of new automated detection algorithms have the potential to be integrated into the latest screening equipment.

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