All language subtitles for 001 Different Computer Vision Tasks

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Would you like to inspect the original subtitles? These are the user uploaded subtitles that are being translated: 1 00:00:00,300 --> 00:00:00,990 In this video. 2 00:00:00,990 --> 00:00:04,530 We'll explain some of the tasks that are often performed by computer vision. 3 00:00:05,560 --> 00:00:07,480 First image classification. 4 00:00:08,310 --> 00:00:13,110 Image classification is the process of determining the category of an image based on the objects in 5 00:00:13,110 --> 00:00:13,230 it. 6 00:00:14,210 --> 00:00:17,210 The input image classification is an image with one object. 7 00:00:17,210 --> 00:00:21,380 What the output is, what object is in the input image with its probability value. 8 00:00:22,210 --> 00:00:23,950 There is also a localization. 9 00:00:24,750 --> 00:00:29,580 Localization perform classification coupled with determining the location of the object in the form 10 00:00:29,580 --> 00:00:30,840 of a bonding box. 11 00:00:31,830 --> 00:00:33,360 Next object detection. 12 00:00:34,190 --> 00:00:39,470 The main purpose of object detection is to predict the location of objects with bounding boxes and classify 13 00:00:39,470 --> 00:00:41,300 objects in each bounding box. 14 00:00:41,960 --> 00:00:45,770 The input to object detection is an image containing one or more objects. 15 00:00:46,430 --> 00:00:51,020 The output is the prediction of the location of the object with the bounding box and the classification 16 00:00:51,020 --> 00:00:53,120 of the object for each bounding box. 17 00:00:53,810 --> 00:00:55,400 Next Image segmentation. 18 00:00:56,190 --> 00:00:59,580 Image segmentation is a further extension of object detection. 19 00:01:00,210 --> 00:01:03,270 Object detection only predicts the bounding box of the object. 20 00:01:03,270 --> 00:01:06,540 While in image segmentation, we can find out the shape of the object. 21 00:01:07,430 --> 00:01:11,900 There are two types of segmentation instant segmentation and semantic segmentation. 22 00:01:12,710 --> 00:01:18,080 Instant segmentation recognizes an object's boundaries and labels its pixels with a different color. 23 00:01:19,290 --> 00:01:24,300 Semantic segmentation assigns a different color to each pixel in the image, including the background 24 00:01:24,300 --> 00:01:26,880 based on the results of the object classification. 25 00:01:28,150 --> 00:01:28,570 From YOLO. 26 00:01:28,570 --> 00:01:32,020 If you want to YOLO, physics can only be used on object detection. 27 00:01:32,780 --> 00:01:36,740 YOLO v seven can be used for object detection and instant segmentation. 28 00:01:37,510 --> 00:01:42,790 The YOLO v seven is also planning to make YOLO seven semantic segmentation in the near future. 29 00:01:43,120 --> 00:01:43,780 See you then. 2800

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