![]() For comparison sake, that’s almost 100,000 more than many other airlines in the rankings. This is impressive stuff, and with over 290,000 flights in the year, it’s quite an accomplishment. Can you even imagine the numbers had they not been so adversely affected by weather?Īnd of course, there’s Aeroflot – the most punctual mainline airline of 2019. Japan suffered through incredibly powerful typhoons in 2019, yet despite this, both airlines managed to actually improve overall on time performance. It’s not easy to keep on time performance at that scale.Īlso super impressive? The Japanese carriers. Perhaps most impressive here is actually Delta, who came third with over 1.1 million flights in 2019, compared to under 300,000 from every other top 10 competitor. ![]() Aeroflot, with 86.68% of flights on time.Īlitalia, Air France, Emirates, Korean and SAS round out the top ten, and there are a few interesting points to note with the results.Consider this the Academy Awards of on time performance on a global scale, rather than just against other local airlines. Here are a few airlines to look out for… Leading Global Airlines For On Time Flightsīefore breaking down the results for a few key regions, it’s fun to take a look at the overall winners. Cirium, a leading data analytics firm has crunched the numbers from 2019, and has revealed the best airlines and airports for on time flight performance. When it comes to doing so, there’s a huge disparity between the airlines which give you the best chance of doing so, and the worst. Scenarios simultaneously, leading to SOTA performance.We all love a comfy seat, service with a smile and maybe even a nice gin and tonic to settle into the journey, but air travel is all about getting from Point A to Point B with an on time flight. We investigate various test-timeĪdaptation methods on three commonly used datasets with four scenarios, and a (ii) Dynamic Online re-weighTing (DOT), designed toĪddress the class bias within optimization. (i) Test-time Batch Renormalization (TBR), introduced to improve the estimated In this paper, we provide a plug-in solution called DELTA forĭegradation-freE fuLly Test-time Adaptation, which consists of two components: Work well in certain scenarios while show performance degradation in others due (time) dependent or class-imbalanced data. Stream with independent and class-balanced samples, we further observe that theĭefects can be exacerbated in more complicated test environments, such as In addition to the extensively studied test We show that during test-time adaptation, the parameter update is biased The currently received test samples, resulting in inaccurate estimates. That the normalization statistics in test-time BN are completely affected by Like test-time batch normalization (BN) and self-learning. Unfavorable defects are concealed in the prevalent adaptation methodologies Several efforts have beenĭevoted to improving adaptation performance. Stream during real-time inference, which is urgently required when the testĭistribution differs from the training distribution. Download a PDF of the paper titled DELTA: degradation-free fully test-time adaptation, by Bowen Zhao and 2 other authors Download PDF Abstract: Fully test-time adaptation aims at adapting a pre-trained model to the test
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