Computer Vision: A Study On Different CNN Architectures and their Applications
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.https://medium.com/alumnaiacademy/introduction-to-computer-vision-4fc2a2ba9dc
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.https://medium.com/alumnaiacademy/introduction-to-computer-vision-4fc2a2ba9dc
Medium
Computer Vision: A Study On Different CNN Architectures and their Applications
Humans are heavily dependent on five senses to interpret the ongoing activities in the world around us. Though each of our senses isβ¦
500+ awesome bookmarks for Data Science & Machine Learning
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.https://towardsdatascience.com/500-free-high-quality-online-resources-for-data-science-machine-learning-7eda5bf33872
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.https://towardsdatascience.com/500-free-high-quality-online-resources-for-data-science-machine-learning-7eda5bf33872
Medium
500+ awesome bookmarks for Data Science & Machine Learning
What this i
The Secret to Mastering ML
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.https://medium.com/technomancy/the-secret-to-mastering-ml-9e328d5f06a
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.https://medium.com/technomancy/the-secret-to-mastering-ml-9e328d5f06a
Medium
The Secret to Mastering ML
Actually build things. Iβll show you where to begin.
Landmark Assisted CycleGAN for Cartoon Face Generation
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.https://deepai.org/publication/landmark-assisted-cyclegan-for-cartoon-face-generation
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.https://deepai.org/publication/landmark-assisted-cyclegan-for-cartoon-face-generation
DeepAI
Landmark Assisted CycleGAN for Cartoon Face Generation
07/02/19 - In this paper, we are interested in generating an cartoon face of a person by
using unpaired training data between real faces and ...
using unpaired training data between real faces and ...
Your State of AI Report 2019
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.https://medium.com/@NathanBenaich/state-of-ai-2019-733c81aeb04b
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.https://medium.com/@NathanBenaich/state-of-ai-2019-733c81aeb04b
Medium
π Your State of AI Report 2019
130 slides on research, talent, industry, China, geopolitics
FREE COURSE Intro to TensorFlow for Deep Learning
This course is a practical approach to deep learning for software developers
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.https://www.udacity.com/course/intro-to-tensorflow-for-deep-learning--ud187
This course is a practical approach to deep learning for software developers
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.https://www.udacity.com/course/intro-to-tensorflow-for-deep-learning--ud187
Udacity
TensorFlow for Deep Learning Training Course | Udacity
Learn online and advance your career with courses in programming, data science, artificial intelligence, digital marketing, and more. Gain in-demand technical skills. Join today!
Advancing Semi-supervised Learning with Unsupervised Data Augmentation
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.https://ai.googleblog.com/2019/07/advancing-semi-supervised-learning-with.html
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.https://ai.googleblog.com/2019/07/advancing-semi-supervised-learning-with.html
Googleblog
Advancing Semi-supervised Learning with Unsupervised Data Augmentation
Video classification with Keras and Deep Learning
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.https://www.pyimagesearch.com/2019/07/15/video-classification-with-keras-and-deep-learning/
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.https://www.pyimagesearch.com/2019/07/15/video-classification-with-keras-and-deep-learning/
PyImageSearch
Video classification with Keras and Deep Learning - PyImageSearch
In this tutorial, you will learn how to perform video classification using Keras, Python, and Deep Learning.
Adrian_Kaehler,_Gary_Bradski_Learning.pdf
20.9 MB
Learning OpenCV 3: Computer Vision in C++ with the OpenCV Library 1st Edition
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Who This Book Is For
This book contains descriptions, working code examples, and explanations of the
C++ computer vision tools contained in the OpenCV 3.x library. Thus, it should be
helpful to many different kinds of users:
Professionals and entrepreneurs
For practicing professionals who need to rapidly prototype or professionally
implement computer vision systems, the sample code provides a quick frameβ
work with which to start. Our descriptions of the algorithms can quickly teach or
remind the reader how they work. OpenCV 3.x sits on top of a hardware accelerβ
ation layer (HAL) so that implemented algorithms can run efficiently, seamlessly
taking advantage of a variety of hardware platforms.
Students....
Teachers....
Hobbyist....
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@DeepLearning_AI
Who This Book Is For
This book contains descriptions, working code examples, and explanations of the
C++ computer vision tools contained in the OpenCV 3.x library. Thus, it should be
helpful to many different kinds of users:
Professionals and entrepreneurs
For practicing professionals who need to rapidly prototype or professionally
implement computer vision systems, the sample code provides a quick frameβ
work with which to start. Our descriptions of the algorithms can quickly teach or
remind the reader how they work. OpenCV 3.x sits on top of a hardware accelerβ
ation layer (HAL) so that implemented algorithms can run efficiently, seamlessly
taking advantage of a variety of hardware platforms.
Students....
Teachers....
Hobbyist....
The Best Machine Learning Research of 2019 So Far - ODSC - Open Data Science - Medium
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.https://medium.com/@ODSC/the-best-machine-learning-research-of-2019-so-far-954120947794
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.https://medium.com/@ODSC/the-best-machine-learning-research-of-2019-so-far-954120947794
Medium
The Best Machine Learning Research of 2019 So Far
The uses of machine learning are expanding rapidly. Already in 2019, significant research has been done in exploring new vistas for the useβ¦
Everything You Need to Know About Autoencoders in TensorFlow
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.https://towardsdatascience.com/everything-you-need-to-know-about-autoencoders-in-tensorflow-b6a63e8255f0
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.https://towardsdatascience.com/everything-you-need-to-know-about-autoencoders-in-tensorflow-b6a63e8255f0
Medium
Everything You Need to Know About Autoencoders in TensorFlow
From theory to implementation in TensorFlow
A 2019 Guide to Object Detection
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.https://heartbeat.fritz.ai/a-2019-guide-to-object-detection-9509987954c3
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.https://heartbeat.fritz.ai/a-2019-guide-to-object-detection-9509987954c3
Medium
A 2019 Guide to Object Detection
Common model architectures and a few new approaches
2D or 3D? A Simple Comparison of Convolutional Neural Networks for Automatic Segmentation of Cardiac Imaging
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.https://towardsdatascience.com/2d-or-3d-a-simple-comparison-of-convolutional-neural-networks-for-automatic-segmentation-of-625308f52aa7
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.https://towardsdatascience.com/2d-or-3d-a-simple-comparison-of-convolutional-neural-networks-for-automatic-segmentation-of-625308f52aa7
Medium
2D or 3D? A Simple Comparison of Convolutional Neural Networks for Automatic Segmentation of Cardiac Imaging
Convolutional neural networks (CNNs) have shown promise for a multitude of computer vision tasks. Among these applications is automaticβ¦
Deepfakes, FaceGANS, and Synthetic Data: Welcome to the Reality Illusion of 2020
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.https://medium.com/swlh/deepfakes-facegans-and-the-rise-of-synthetic-data-welcome-to-2020-a54b88eecdf9
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.https://medium.com/swlh/deepfakes-facegans-and-the-rise-of-synthetic-data-welcome-to-2020-a54b88eecdf9
Medium
Deepfakes, FaceGANS, and Synthetic Data: Welcome to the Reality Illusion of 2020
Two weeks ago, I attended CVPR, the worldβs largest international artificial intelligence conference on computer vision to date. Asideβ¦
The 5 Feature Selection Algorithms every Data Scientist should know
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.https://towardsdatascience.com/the-5-feature-selection-algorithms-every-data-scientist-need-to-know-3a6b566efd2
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.https://towardsdatascience.com/the-5-feature-selection-algorithms-every-data-scientist-need-to-know-3a6b566efd2
The project is about predicting coronary heart disease by using three different ML algorithms
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https://blog.goodaudience.com/heart-disease-prediction-aa656f2db585
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https://blog.goodaudience.com/heart-disease-prediction-aa656f2db585
Medium
heart disease prediction
The project is about predicting coronary heart disease by using three different ML algorithms.
Review: G-RMI β Winner in 2016 COCO Detection (Object Detection)
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.https://towardsdatascience.com/review-g-rmi-winner-in-2016-coco-detection-object-detection-af3f2eaf87e4
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.https://towardsdatascience.com/review-g-rmi-winner-in-2016-coco-detection-object-detection-af3f2eaf87e4
Medium
Review: G-RMI β Winner in 2016 COCO Detection (Object Detection)
A Guide to Select a Detection Architecture: Faster R-CNN, R-FCN and SSD
Review: FSRCNN (Super Resolution)
What Are Covered
1. Brief Review of SRCNNFSRCNN Network
2. ArchitectureExplanation of 1Γ1 Convolution Used in
3. Shrinking and Expanding
4. Explanation of Multiple 3Γ3 Convolutions in Non-Linear Mapping
5. Ablation Study
6. Results
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.https://towardsdatascience.com/review-fsrcnn-super-resolution-80ca2ee14da4
What Are Covered
1. Brief Review of SRCNNFSRCNN Network
2. ArchitectureExplanation of 1Γ1 Convolution Used in
3. Shrinking and Expanding
4. Explanation of Multiple 3Γ3 Convolutions in Non-Linear Mapping
5. Ablation Study
6. Results
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.https://towardsdatascience.com/review-fsrcnn-super-resolution-80ca2ee14da4
Medium
Review: FSRCNN (Super Resolution)
This time, FSRCNN, by CUHK, is reviewed. In this paper, a real-time super resolution approach is proposed. Fast Super-Resolutionβ¦
How to Deal with Imbalanced Data using SMOTE - Analytics Vidhya - Medium
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.https://medium.com/analytics-vidhya/balance-your-data-using-smote-98e4d79fcddb
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.https://medium.com/analytics-vidhya/balance-your-data-using-smote-98e4d79fcddb
Medium
How to Deal with Imbalanced Data using SMOTE
With a Case Study in Python