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TORRENT DETAILS

[FreeCoursesOnline.Me] Coursera - Deep Learning In Computer Vision

TORRENT SUMMARY

[FreeCoursesOnline.Me] Coursera - Deep Learning in Computer Vision

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Size

1.1 GB in 99 files

Release Date(s)

Torrent Release: 06-11-2018 by user

Infohash

89972431050503e9523138b7544b420a089a8691

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DESCRIPTION

[COURSERA] DEEP LEARNING IN COMPUTER VISION [FCO]

About this course: Deep learning added a huge boost to the already rapidly developing field of computer vision. With deep learning, a lot of new applications of computer vision techniques have been introduced and are now becoming parts of our everyday lives. These include face recognition and indexing, photo stylization or machine vision in self-driving cars. The goal of this course is to introduce students to computer vision, starting from basics and then turning to more modern deep learning models. We will cover both image and video recognition, including image classification and annotation, object recognition and image search, various object detection techniques, motion estimation, object tracking in video, human action recognition, and finally image stylization, editing and new image generation. In course project, students will learn how to build face recognition and manipulation system to understand the internal mechanics of this technology, probably the most renown and oftenly demonstrated in movies and TV-shows example of computer vision and AI.

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FILE LIST

Filename		Size
	001.Introduction and digital images/001. Short introduction to computer vision.mp4	15.3 MB
	001.Introduction and digital images/001. Short introduction to computer vision.srt	7.1 KB
	001.Introduction and digital images/002. Digital images.mp4	12.2 MB
	001.Introduction and digital images/002. Digital images.srt	5.1 KB
	001.Introduction and digital images/003. Structure of human eye and vision.mp4	22.3 MB
	001.Introduction and digital images/003. Structure of human eye and vision.srt	8.4 KB
	001.Introduction and digital images/004. Color models.mp4	57.7 MB
	001.Introduction and digital images/004. Color models.srt	21.5 KB
	002.Basic image processing/005. Image processing goals and tasks.mp4	10.8 MB
	002.Basic image processing/005. Image processing goals and tasks.srt	3.6 KB
	002.Basic image processing/006. Contrast and brightness correction.mp4	19.7 MB
	002.Basic image processing/006. Contrast and brightness correction.srt	7 KB
	002.Basic image processing/007. Image convolution.mp4	26 MB
	002.Basic image processing/007. Image convolution.srt	9.6 KB
	002.Basic image processing/008. Edge detection.mp4	31.9 MB
	002.Basic image processing/008. Edge detection.srt	11.7 KB
	003.Image classification/009. Recap Image classification.mp4	32.4 MB
	003.Image classification/009. Recap Image classification.srt	10.8 KB
	003.Image classification/010. AlexNet, VGG and Inception architectures.mp4	43.8 MB
	003.Image classification/010. AlexNet, VGG and Inception architectures.srt	14.2 KB
	003.Image classification/011. ResNet and beyond.mp4	43.2 MB
	003.Image classification/011. ResNet and beyond.srt	12.3 KB
	003.Image classification/012. Fine-grained image recognition.mp4	25.4 MB
	003.Image classification/012. Fine-grained image recognition.srt	7.5 KB
	003.Image classification/013. Detection and classification of facial attributes.mp4	24.1 MB
	003.Image classification/013. Detection and classification of facial attributes.srt	8.1 KB
	004.Content-based image retrieval/014. Content-based image retrieval.mp4	31.6 MB
	004.Content-based image retrieval/014. Content-based image retrieval.srt	9.3 KB
	004.Content-based image retrieval/015. Computing semantic image embeddings using convolutional neural networks.mp4	35.6 MB
	004.Content-based image retrieval/015. Computing semantic image embeddings using convolutional neural networks.srt	11 KB
	004.Content-based image retrieval/016. Employing indexing structures for efficient retrieval of semantic neighbors.mp4	37.3 MB
	004.Content-based image retrieval/016. Employing indexing structures for efficient retrieval of semantic neighbors.srt	11.7 KB
	004.Content-based image retrieval/017. Face verification.mp4	25.2 MB
	004.Content-based image retrieval/017. Face verification.srt	7.9 KB
	004.Content-based image retrieval/018. The re-identification problem in computer vision.mp4	21.1 MB
	004.Content-based image retrieval/018. The re-identification problem in computer vision.srt	6.8 KB
	005.Keypoints regression/019. Facial keypoints regression.mp4	25.6 MB
	005.Keypoints regression/019. Facial keypoints regression.srt	7.5 KB
	005.Keypoints regression/020. CNN for keypoints regression.mp4	23.2 MB
	005.Keypoints regression/020. CNN for keypoints regression.srt	7.2 KB
	006.Sliding window detectors/021. Object detection problem.mp4	22.4 MB
	006.Sliding window detectors/021. Object detection problem.srt	9.8 KB
	006.Sliding window detectors/022. Sliding windows.mp4	11.8 MB
	006.Sliding window detectors/022. Sliding windows.srt	4.7 KB
	006.Sliding window detectors/023. HOG-based detector.mp4	9.1 MB
	006.Sliding window detectors/023. HOG-based detector.srt	3.4 KB
	006.Sliding window detectors/024. Detector training.mp4	11.7 MB
	006.Sliding window detectors/024. Detector training.srt	4.4 KB
	006.Sliding window detectors/025. Viola-Jones face detector.mp4	19.4 MB
	006.Sliding window detectors/025. Viola-Jones face detector.srt	8 KB
	006.Sliding window detectors/026. Attentional cascades and neural networks.mp4	12.2 MB
	006.Sliding window detectors/026. Attentional cascades and neural networks.srt	4.8 KB
	007.Modern detector architectures/027. Region-based convolutional neural network.mp4	10.7 MB
	007.Modern detector architectures/027. Region-based convolutional neural network.srt	4.3 KB
	007.Modern detector architectures/028. From R-CNN to Fast R-CNN.mp4	17.8 MB
	007.Modern detector architectures/028. From R-CNN to Fast R-CNN.srt	6.9 KB
	007.Modern detector architectures/029. Faster R-CNN.mp4	15.8 MB
	007.Modern detector architectures/029. Faster R-CNN.srt	5.7 KB
	007.Modern detector architectures/030. Region-based fully-convolutional network.mp4	8.5 MB
	007.Modern detector architectures/030. Region-based fully-convolutional network.srt	3.1 KB
	007.Modern detector architectures/031. Single shot detectors.mp4	14.5 MB
	007.Modern detector architectures/031. Single shot detectors.srt	2.5 KB
	007.Modern detector architectures/032. Speed vs. accuracy tradeoff.mp4	7.1 MB
	007.Modern detector architectures/032. Speed vs. accuracy tradeoff.srt	2.5 KB
	007.Modern detector architectures/033. Fun with pedestrian detectors.mp4	5.8 MB
	007.Modern detector architectures/033. Fun with pedestrian detectors.srt	1.6 KB
	008.Object tracking/034. Introduction to video analysis.mp4	12.7 MB
	008.Object tracking/034. Introduction to video analysis.srt	5.2 KB
	008.Object tracking/035. Optical flow.mp4	17.3 MB
	008.Object tracking/035. Optical flow.srt	7.8 KB
	008.Object tracking/036. Deep learning in optical flow estimation.mp4	19 MB
	008.Object tracking/036. Deep learning in optical flow estimation.srt	8.6 KB
	008.Object tracking/037. Visual object tracking.mp4	18.7 MB
	008.Object tracking/037. Visual object tracking.srt	8.1 KB
	008.Object tracking/038. Examples of visual object tracking methods.mp4	42.9 MB
	008.Object tracking/038. Examples of visual object tracking methods.srt	20.8 KB
	008.Object tracking/039. Multiple object tracking.mp4	18.2 MB
	008.Object tracking/039. Multiple object tracking.srt	8.1 KB
	008.Object tracking/040. Examples of multiple object tracking methods.mp4	26.3 MB
	008.Object tracking/040. Examples of multiple object tracking methods.srt	12 KB
	009.Action recognition/041. Introduction to action recognition.mp4	21.9 MB
	009.Action recognition/041. Introduction to action recognition.srt	9.3 KB
	009.Action recognition/042. Action classification.mp4	26.6 MB
	009.Action recognition/042. Action classification.srt	11.9 KB
	009.Action recognition/043. Action classification with convolutional neural networks.mp4	18.8 MB
	009.Action recognition/043. Action classification with convolutional neural networks.srt	8.2 KB
	009.Action recognition/044. Action localization.mp4	22.4 MB
	009.Action recognition/044. Action localization.srt	10.1 KB
	010.Image segmentation/045. Image segmentation.mp4	16 MB
	010.Image segmentation/045. Image segmentation.srt	4.8 KB
	010.Image segmentation/046. Oversegmentation.mp4	17.8 MB
	010.Image segmentation/046. Oversegmentation.srt	5.4 KB
	010.Image segmentation/047. Deep learning models for image segmentation.mp4	32.7 MB
	010.Image segmentation/047. Deep learning models for image segmentation.srt	10.1 KB
	010.Image segmentation/048. Human pose estimation as image segmentation.mp4	33.4 MB
	010.Image segmentation/048. Human pose estimation as image segmentation.srt	10.9 KB
	011.Style transfer and image generation/049. Style transfer.mp4	22.7 MB
	011.Style transfer and image generation/049. Style transfer.srt	6.6 KB
	011.Style transfer and image generation/050. Generative adversarial networks.mp4	29.5 MB

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