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Technical articles on Computer Vision applied to Business
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Grad CAM Method (Original Photo by Kelly Lund on Unsplash)

Introducing tf-explain, Interpretability for TensorFlow 2.0

A Tensorflow 2.0 library for deep learning model interpretability.

museum watching

Few-Shot Image Classification with Meta-Learning

Here is how you can teach your model to learn quickly from a few examples.

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Determine Your Network Hyper-parameters With Bayesian Optimization

Why and how Bayesian Optimization can be used for hyper-parameters tuning

How to Get Certified in Spark by Databricks?

This article aims to prepare you for the Databricks Spark Developer Certification: register, train and succeed, based on my recent experience.

Preview Image of the DSFD article

Face Detectors: Understand DSFD and the State-of-the-art Algorithms

Let’s dive into the recent Dual Shot Face Detector DSFD through a review of two famous detection algorithms: Faster R-CNN and Single Shot Detector.

annotation tools

Best Open Source Annotation Tools for Computer Vision

A Top 5 labeling tools to create Computer Vision datasets.

Grad CAM method on ‘deer’ ImageNet class (Original photo by Asa Rodger on Unsplash)

Interpretability of Deep Learning Models with Tensorflow 2.0

An introduction to interpretability methods to ease neural network training monitoring.

Edge detection, tutorial, knowledge

Edge Detection in Opencv 4.0, A 15 Minutes Tutorial

This tutorial will teach you, with examples, two OpenCV techniques in python to deal with edge detection.

The best of AI of June 2019

The Best of AI: New Articles Published This Month (June 2019)

10 data articles handpicked by the Sicara team, just for you.

bridge

Image Registration: From SIFT to Deep Learning

How the field has evolved from OpenCV to Neural Networks.

rboy

Basics in R Programming

You are about to begin a project on R? Before you watch any tutorial, read these basic standards.

Best Of May 2019

The Best of AI: New Articles Published This Month (May 2019)

10 data articles handpicked by the Sicara team, just for you