Learning Slimming SAR Ship Object Detector Through Network Pruning and Knowledge Distillation
نویسندگان
چکیده
منابع مشابه
Learning Efficient Convolutional Networks through Network Slimming
Layer Width Width* Pruned P/F Pruned 1 64 22 65.6% 34.4% 2 64 62 3.1% 66.7% 3 128 83 35.2% 37.2% 4 128 119 7.0% 39.7% 5 256 193 24.6% 29.9% 6 256 168 34.4% 50.5% 7 256 85 66.8% 78.2% 8 256 40 84.4% 94.8% 9 512 32 93.8% 99.0% 10 512 32 93.8% 99.6% 11 512 32 93.8% 99.6% 12 512 32 93.8% 99.6% 13 512 32 93.8% 99.6% 14 512 32 93.8% 99.6% 15 512 32 93.8% 99.6% 16 512 38 92.6% 99.6% Total 5504 1034 81...
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15 صفحه اولSAR Imaging of Ship Wakes and Inverse Ship Wake Problem
Airborne Synthetic Aperture Radar (SAR) images of sea surface often reveal ship wakes, which appear in a form of bright and dark streaks. It is believed that some of them pertain to the ship generated Kelvin wave system and some to the ship turbulent wake (Reed et al., 1990). The streaks in SAR images are sufficiently narrow to consider them as straight segments. Assuming that the location and ...
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ژورنال
عنوان ژورنال: IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
سال: 2021
ISSN: 1939-1404,2151-1535
DOI: 10.1109/jstars.2020.3041783