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Advanced Computer Vision with Deep-learning | Free Udemy Course
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Advanced Computer Vision with Deep-learning | Free Udemy Course

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Object detection, Image segmentation, Visualization and Interpretability - Free Course | Free Udemy Course

3.82
(9 ratings)
3292 students
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Course Language EnglishCourse Caption English [Auto]Course Length 35:59 to be exact 2159 seconds!Number of Lectures 18
This course includes:
  • 36 mins hours of on-demand video
  • Full lifetime access
  • Access on mobile and TV
  • 12 additional resources

Hello I am Nitsan Soffair, A Deep RL researcher at BGU.In this Computer-vision course, you will learn the newest state-of-the-art Computer vision (CV) Deep-learning knowledge.You will do the followingGet state-of-the-art knowledge of the followingObject detectionImage segmentationVisualization and InterpretabilityValidate your knowledge by answering short and very easy 3-question queezes of each lectureBe able to complete the course by ~2 hours.SyllabusIntroduction to Computer visionClassification and Object detectionTechnology in the field of computer vision for finding and identifying objects in an image or video sequenceSegmentationThe process of partitioning a digital image into multiple image segments of pixels' sets.Transfer-learningA research problem in machine learning (ML) that focuses on storing knowledge gained while solving one problem and applying it to a different but related problem.ResnetsAn artificial neural network (ANN). Skip connections are used to jump over some layers.Object localizationa computer technology to detect instances of semantic objects of a certain class i.e. humans, buildings in images and videos.Object detectionR-CNNDetection algorithm.Fast R-CNNDetection network region-proposal algorithm.Faster R-CNNObject detection network region-proposal algorithm.RetinaNetA dense detector evaluating the loss.Image segmentationFCNTransforms image pixels to classes using CNN.Upsampling methodsPerformed on a sequence of signal's samples/continuous function.Evaluation with IoU and Dice-scoreEvaluation metrics.U-NetA Deep neural-networl model based on fully-connected neural-network.Visualization and InterpretabilityClass activation mapsTechnique gets the discriminative image regions used by CNN to identify specific classes in image.Saliency mapsAn image that highlights the region on which people's eyes focus first.ResourcesWikipediaCourseraWho this course is for:Anyone intersting in Computer-vision with Deep-learning

Course Content:

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5 Lectures | 06:23
4 Lectures | 04:23
4 Lectures | 03:28
2 Lectures | 01:56
3 Lectures | 19:49
3.82
(9 course ratings)
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