Building a Sketch Recognition System with CNN

Overview

Build an end-to-end drawing recognition system with CNNs. Master data prep, training, and evaluation—from raw sketches to real results. Gain hands-on experience turning messy data into accurate predictions.

Syllabus

Course 1: Introduction to Drawing Recognition and CNN Fundamentals
Course 2: Data Preparation for Drawing Recognition
Course 3: Drawing Recognition with CNNs for Sketches
Course 4: Building the UI for Drawing Recognition

Courses

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1 hour
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The course focuses on the fundamentals of drawing recognition using Convolutional Neural Networks (CNNs). It covers the basics of CNNs, their architecture, and how they can be applied to recognize hand-drawn sketches. The course also includes practical exercises to reinforce the concepts learned.
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2 hours
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The course focuses on preparing the dataset for drawing recognition. It covers the basics of data preparation, how to preprocess the data, and how to split the dataset into training and testing sets. The course also includes practical exercises to reinforce the concepts learned.
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2 hours
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The course focuses on the application of Convolutional Neural Networks (CNNs) for recognizing hand-drawn sketches. It covers the architecture of CNNs, how they can be trained on sketch datasets, and practical exercises to reinforce the concepts learned.
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2 hours
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The course focuses on building a user interface (UI) for drawing recognition using HTML, CSS, and JavaScript. It covers the basics of web development, how to create a simple UI for drawing recognition, and how to integrate the CNN model with the UI.