A Lazy Man's Approach to Benchmarking: Semisupervised Classifier Evaluation and Recalibration

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Recognition in Terra Incognita (2018, background): “However, it is known that current learning algorithms are dramatically less data-efficient than humans [11], transfer learning is difficult [12], and, anecdotally, vision algorithms do not generalize well across datasets [13, 14] (Fig.”
Introspective perception: Learning to predict failures in vision systems (2016, background): “[17] and Aghazadeh and Carslsson [18] analyzing statistics of the training and test data to predict the global performance of a classifier on a corpus of test instances.”