Содержание
- 2. Agenda Reason behind image-to-image translation - Problems with manufacturing Structure of neural network - Vanilla GAN
- 3. Image-to-Image Problems with optical images: - Weather conditions - Hours of darkness 2022 https://avatars.mds.yandex.net/get-zen_doc/176438/pub_5a8545c81410c32cdb85b939_5a8546c455876b90a66af9f2/scale_1200
- 4. Image-to-Image Problems with synthetic aperture radar (SAR) images: - Grainy noise - Lack of colours 2022
- 5. Image-to-Image The way to mitigate all problems at once 2022 SAR images Generated images Real optical
- 6. GAN Structure Discriminator (D) identify images Generator (G) create image from noise 2022 https://qiita-user-contents.imgix.net/https%3A%2F%2Fqiita-image-store.s3.ap-northeast-1.amazonaws.com%2F0%2F567823%2F8c19ec3d-693d-e5c1-070c-ce69f1a16d58.jpeg?ixlib=rb-1.2.2&auto=format&gif-q=60&q=75&w=1400&fit=max&s=06c4a34575c9c4963f0f7076eb8f4b72
- 7. GAN Structure Red rectangles: scenes for training Blue rectangles: scenes for test 2022
- 8. GAN Structure Division into smaller patches Translation from SAR to optical Stitching pieces the image 2022
- 9. Experiments and results Image translation: Example of ready picture Example of translated patch 2022 SAR images
- 10. Experiments and results 2022 Comparison of various approaches
- 11. Experiments and results Cloud removal experiment 2022
- 12. Summary Worthwhile and important problem has found it’s solution Modern and elegant methods were used Mind-blowing
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