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Building Image Processing Applications Using scikit-image (Janani Ravi, 2018)

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  • 文件大小:259MB
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文件列表

  1. 4. Segmentation and Transformation/10. Comparing Images Using MSE and SSIM.mp4 22MB
  2. exercise.7z 21MB
  3. 3. Object and Feature Detection/7. Applying Denoising Filters.mp4 16MB
  4. 3. Object and Feature Detection/9. Filling Holes and Finding Peaks Using Erosion and Dilation.mp4 16MB
  5. 2. Working with Image Data/05. Working with Images as NumPy Arrays.mp4 14MB
  6. 4. Segmentation and Transformation/03. Applying Global and Local Thresholding Algorithms.mp4 12MB
  7. 4. Segmentation and Transformation/05. Segmentation and Merging Segments Using Rags.mp4 11MB
  8. 2. Working with Image Data/14. Canny Edge Detection.mp4 11MB
  9. 2. Working with Image Data/10. Contours.mp4 10MB
  10. 4. Segmentation and Transformation/08. Applying Image Transformations.mp4 9MB
  11. 3. Object and Feature Detection/5. Corner Detection.mp4 9MB
  12. 3. Object and Feature Detection/4. Visualizing Hog Feature Descriptors.mp4 9MB
  13. 3. Object and Feature Detection/3. Visualizing Daisy Descriptors on Images.mp4 9MB
  14. 2. Working with Image Data/09. Block Views and Pooling Operations.mp4 9MB
  15. 2. Working with Image Data/07. Masking Color Images.mp4 8MB
  16. 4. Segmentation and Transformation/07. Segmentation Using Classic and Compact Watershed.mp4 8MB
  17. 2. Working with Image Data/06. Masking Images Using Array Manipulation.mp4 7MB
  18. 2. Working with Image Data/04. Introducing scikit-image.mp4 6MB
  19. 2. Working with Image Data/11. Convex Hull.mp4 5MB
  20. 2. Working with Image Data/12. Edge Detection.mp4 5MB
  21. 1. Course Overview/1. Course Overview.mp4 4MB
  22. 2. Working with Image Data/08. Introducing Block Views and Pooling.mp4 4MB
  23. 3. Object and Feature Detection/2. Feature Detection and Image Descriptors.mp4 4MB
  24. 2. Working with Image Data/13. Roberts and Sobel Edge Detection.mp4 3MB
  25. 4. Segmentation and Transformation/09. Introducing the MSE and SSIM as Distance Measures.mp4 3MB
  26. 4. Segmentation and Transformation/04. Image Segmentation and Region Adjacency Graphs.mp4 3MB
  27. 4. Segmentation and Transformation/02. Introducing Thresholding.mp4 3MB
  28. 3. Object and Feature Detection/6. Introducing Denoising Filters.mp4 3MB
  29. 2. Working with Image Data/03. Prerequisites and Course Outline.mp4 3MB
  30. 4. Segmentation and Transformation/06. Introducing Watershed Algorithms for Segmentation.mp4 2MB
  31. 3. Object and Feature Detection/8. Morphological Reconstruction.mp4 2MB
  32. 4. Segmentation and Transformation/11. Summary and Further Study.mp4 2MB
  33. 3. Object and Feature Detection/1. Module Overview.mp4 2MB
  34. 2. Working with Image Data/02. Module Overview.mp4 2MB
  35. 4. Segmentation and Transformation/01. Module Overview.mp4 1MB
  36. 2. Working with Image Data/01. Version Check.mp4 590KB
  37. cover.jpg 96KB
  38. 2. Working with Image Data/05. Working with Images as NumPy Arrays.vtt 9KB
  39. 2. Working with Image Data/14. Canny Edge Detection.vtt 8KB
  40. 2. Working with Image Data/10. Contours.vtt 8KB
  41. 4. Segmentation and Transformation/10. Comparing Images Using MSE and SSIM.vtt 8KB
  42. 3. Object and Feature Detection/9. Filling Holes and Finding Peaks Using Erosion and Dilation.vtt 8KB
  43. 3. Object and Feature Detection/7. Applying Denoising Filters.vtt 7KB
  44. 3. Object and Feature Detection/5. Corner Detection.vtt 7KB
  45. 4. Segmentation and Transformation/05. Segmentation and Merging Segments Using Rags.vtt 7KB
  46. 2. Working with Image Data/04. Introducing scikit-image.vtt 7KB
  47. 2. Working with Image Data/09. Block Views and Pooling Operations.vtt 6KB
  48. 2. Working with Image Data/07. Masking Color Images.vtt 5KB
  49. 4. Segmentation and Transformation/03. Applying Global and Local Thresholding Algorithms.vtt 5KB
  50. 2. Working with Image Data/06. Masking Images Using Array Manipulation.vtt 5KB
  51. 2. Working with Image Data/12. Edge Detection.vtt 5KB
  52. 3. Object and Feature Detection/4. Visualizing Hog Feature Descriptors.vtt 5KB
  53. 3. Object and Feature Detection/3. Visualizing Daisy Descriptors on Images.vtt 5KB
  54. 2. Working with Image Data/11. Convex Hull.vtt 5KB
  55. 2. Working with Image Data/08. Introducing Block Views and Pooling.vtt 5KB
  56. 4. Segmentation and Transformation/07. Segmentation Using Classic and Compact Watershed.vtt 4KB
  57. 3. Object and Feature Detection/2. Feature Detection and Image Descriptors.vtt 4KB
  58. 4. Segmentation and Transformation/08. Applying Image Transformations.vtt 4KB
  59. 4. Segmentation and Transformation/09. Introducing the MSE and SSIM as Distance Measures.vtt 3KB
  60. 2. Working with Image Data/03. Prerequisites and Course Outline.vtt 3KB
  61. 4. Segmentation and Transformation/02. Introducing Thresholding.vtt 3KB
  62. 4. Segmentation and Transformation/04. Image Segmentation and Region Adjacency Graphs.vtt 3KB
  63. 1. Course Overview/1. Course Overview.vtt 3KB
  64. 3. Object and Feature Detection/6. Introducing Denoising Filters.vtt 3KB
  65. 4. Segmentation and Transformation/11. Summary and Further Study.vtt 3KB
  66. 3. Object and Feature Detection/8. Morphological Reconstruction.vtt 3KB
  67. 4. Segmentation and Transformation/06. Introducing Watershed Algorithms for Segmentation.vtt 2KB
  68. playlist.m3u 2KB
  69. 2. Working with Image Data/13. Roberts and Sobel Edge Detection.vtt 2KB
  70. ~i.txt 2KB
  71. 3. Object and Feature Detection/1. Module Overview.vtt 2KB
  72. 2. Working with Image Data/02. Module Overview.vtt 2KB
  73. 4. Segmentation and Transformation/01. Module Overview.vtt 1KB
  74. 2. Working with Image Data/01. Version Check.vtt 7B