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Alibaba F(x) Team

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How Do You Use Deep Learning to Identify UI Components?

This blog discusses the usage of deep learning for recognizing UI components and introduces a correct method of using machine learning to solve various problems.

Imgcook 3.0 Series: Layout Algorithm – Design-based Code Generation

This blog discusses in depth about layout algorithms used by imgcook, focusing on page splitting, loop, and multi-status identification.

Imgcook 3.0 Series: How Does Design-based Code Generation Recognize Components?

This post describes how imgcook recognizes design components and expresses them with front-end components for intelligent code generation.

Imgcook 3.0 Series: How Does Design-based Code Generation Recognize Icons?

This article will describe how imgcook optimizes data and model by building a complete closed-loop procedure for the icon model.

Imgcook 3.0 Series: Semantic Analysis of Fields

This article introduces the concept of semantics in D2C and elaborates further on various semantic decision models based on reinforcement learning and text classification.

Intelligently Generate Frontend Code from Design Files: Intelligent Plugins

This article is a part of the article series discussing how to generate frontend code from design files intelligently.

Intelligently Generate Frontend Code from Design Files: imgcook

This article is a part of the article series discussing how to generate frontend code from design files intelligently.

Intelligently Generate Frontend Code from Design Files: Business Logic Generation

This article is a part of the article series discussing how to generate frontend code from design files intelligently.

Intelligently Generate Frontend Code from Design Files: Basic Component Recognition

This article is a part of the article series discussing how to generate frontend code from design files intelligently.

Intelligently Generate Frontend Code from Design Files: Field Binding

This article is a part of the article series discussing how to generate frontend code from design files intelligently.

Intelligently Generate Frontend Code from Design Files: Image Segmentation

This article discusses how to generate frontend code from design files intelligently, covering image segmentation and content extraction from complex image backgrounds.

Intelligently Generate Frontend Code from Design Files: Business Module Recognition

This article discusses business module recognition and explores the random forest and XGBoost models for intelligent frontend code generation.

Intelligently Generate Frontend Code from Design Files: Form and Table Recognition

This article discusses how to generate frontend code from design files intelligently, specifically on code generation for forms and tables.

Ideas for Using Recursive Autoencoders for Intelligent Layout Generation

This article uses the main ideas of the "READ: Recursive Autoencoders for Document Layout Generation" paper and discusses its implementation in frontend scenarios.

Implement Your Own Control Recognition Model with Pipcook

This article guides you through the implementation of your own frontend intelligent project and use of machine learning to address programming problems.

Information Input Considerations for Intelligently Generating Frontend Code

This article focuses on ways to obtain information and how imgcook has helped on the journey of generating more accurate code.

Pipcook — Providing the Frontend with a Complete Intelligent Algorithm Framework

This article introduces Pipcook and discusses how it can be optimized and used for an intelligent frontend.

TensorFlow.js Helps Recognize Large Quantities of Icons in Milliseconds!

This article discusses how to implement Deep Learning, Sample Generation, Model Training, Model Compression, and Conversion with TensorFlow.

Building a High-Level Frontend Machine Learning Framework Based on the tfjs-node

This article describes how Pipcook is integrated with TensorFlow and how the underlying models of tfjs-node are used to build a machine learning pipeline.

AI Empowers Design-to-Code in the Mid-End and Backend Scenarios

This article explores how AI empowers Design-to-Code (D2C) in mid-end and backend scenarios.

Latest Comments

Adnan Zaidi Commented on TensorFlow.js Helps Recognize Large Quantities of Icons in Milliseconds!

Really informative to start with !!!

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