Research Article
Classification of Long-Tailed Data Based on Bilateral-Branch Generative Network with Time-Supervised Strategy
| | Inputs: training datasets , | | | Output: BBN network model (input; weight) | | (1) | | | (2) | for k = 2 to K do | | (3) | | | (4) | for i = 1 to do | | (5) | A random sample of class in | | (6) | | | (7) | end for | | (8) | end for | | (9) | | | (10) | for i = 0 to do | | (11) | j A random sample of | | (12) | | | (13) | | | (14) | | | (16) | | | (17) | | | (18) | | | (19) | | | (20) | end for | | (21) | |
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