tensorflow.js | BestHub

System Architect Go

Jul 4, 2024 · Artificial Intelligence

Optimizing Image Search System Architecture with Client‑Side Feature Extraction Using MobileNet

This article explains the architecture of an image‑search system that extracts feature vectors, stores them in a vector database, and performs similarity queries, then proposes an optimized design that offloads feature extraction to a lightweight MobileNet model running in the browser, reducing latency, server load, and component complexity.

Image SearchMobileNetSystem Architecture

0 likes · 9 min read

Optimizing Image Search System Architecture with Client‑Side Feature Extraction Using MobileNet

Rare Earth Juejin Tech Community

May 10, 2024 · Artificial Intelligence

Real-Time Dog Detection in Browser Using TensorFlow.js and MobileNet V2

This guide demonstrates how to build a web‑based real‑time dog detector that accesses the phone camera via the browser, processes video frames with TensorFlow.js and a pre‑trained COCO‑SSD MobileNet V2 model, and plays an audio alert when a dog is recognized, all deployed on an Android device using Termux.

JavaScriptMobileNetWeb Camera

0 likes · 8 min read

Real-Time Dog Detection in Browser Using TensorFlow.js and MobileNet V2

Rare Earth Juejin Tech Community

Nov 30, 2023 · Artificial Intelligence

Getting Started with TensorFlow.js: Front‑end, Node.js, and WeChat Mini‑Program Integration

This article introduces TensorFlow.js, explains its origin and core features, and provides step‑by‑step instructions for using it in browsers, Node.js, and WeChat mini‑programs, including package installation, sample code, and practical tips for front‑end developers.

Front-endJavaScriptMachine Learning

0 likes · 13 min read

Getting Started with TensorFlow.js: Front‑end, Node.js, and WeChat Mini‑Program Integration

IT Services Circle

Oct 10, 2023 · Frontend Development

How Adobe Brings Photoshop to the Browser: WebAssembly, Web Components, Service Workers, and AI Integration

Adobe’s new web‑based Photoshop demonstrates how modern browser APIs—such as WebAssembly, OPFS, Service Workers, Lit‑based Web Components, and TensorFlow.js—enable a complex, graphics‑intensive application to run efficiently across platforms while offering AI‑powered features and future‑proof performance optimizations.

Adobe PhotoshopLitOPFS

0 likes · 12 min read

How Adobe Brings Photoshop to the Browser: WebAssembly, Web Components, Service Workers, and AI Integration

DaTaobao Tech

Jul 8, 2022 · Frontend Development

Alibaba Front‑End Intelligent Technology: PipCook, DataCook, imgcook and Future Directions

Alibaba Front‑End Intelligent Technology combines PipCook, DataCook, and imgcook to enable data‑driven UI generation, on‑device AI inference via WASM‑Rust‑SIMD and WebGPU, and applications such as code IntelliSense and design‑to‑code, while outlining a roadmap toward unified AI‑powered interfaces for commerce.

AIFrontendMachine Learning

0 likes · 33 min read

Alibaba Front‑End Intelligent Technology: PipCook, DataCook, imgcook and Future Directions

Taobao Frontend Technology

Sep 23, 2021 · Artificial Intelligence

Build and Deploy ML Models with Pipcook 2.0 in Under 20 Seconds

Discover how Pipcook 2.0 dramatically speeds up machine‑learning workflows for web developers—cutting installation to under 20 seconds, enabling rapid model training, prediction, and deployment via concise JSON pipelines, with step‑by‑step guidance, code snippets, and practical examples for image and text classification.

AI PipelineMachine LearningModel Deployment

0 likes · 12 min read

Build and Deploy ML Models with Pipcook 2.0 in Under 20 Seconds

Taobao Frontend Technology

Jul 8, 2021 · Artificial Intelligence

How to Build Machine Learning Apps Directly in the Browser with JavaScript

This article explains a four‑level methodology for choosing JavaScript‑based machine‑learning tools, demonstrates practical code examples ranging from NLP with nlp.js to deep‑learning with TensorFlow.js, traditional ML with mljs, and statistical computing with stdlib, and shows how to run them entirely in the browser.

Frontend AIJavaScriptMachine Learning

0 likes · 11 min read

How to Build Machine Learning Apps Directly in the Browser with JavaScript

Taobao Frontend Technology

Jun 30, 2021 · Artificial Intelligence

How to Build Machine Learning Apps Directly in the Browser: A Four‑Layer Toolkit

This article outlines a four‑layer methodology for selecting JavaScript‑based machine‑learning tools—from domain‑specific NLP frameworks to deep‑learning libraries, traditional algorithms, and math/statistics packages—providing code examples, installation steps, and guidance on when to use each layer.

FrontendJavaScriptMachine Learning

0 likes · 10 min read

How to Build Machine Learning Apps Directly in the Browser: A Four‑Layer Toolkit

Taobao Frontend Technology

Oct 27, 2020 · Artificial Intelligence

Mastering Tensors in TensorFlow.js: From Scalars to Neural Networks

This guide explains the fundamentals of tensors in TensorFlow.js—including scalars, vectors, and higher‑dimensional tensors—demonstrates how to convert real‑world data such as the Titanic dataset into tensors, and shows how to build, compile, and train a simple neural network model using appropriate layers, loss functions, and optimizers.

JavaScriptdata preprocessingneural network

0 likes · 7 min read

Mastering Tensors in TensorFlow.js: From Scalars to Neural Networks

Taobao Frontend Technology

Sep 1, 2020 · Artificial Intelligence

Build a Browser‑Based MNIST Classifier with TensorFlow.js: A Step‑by‑Step Guide

Learn how to create a browser‑compatible MNIST image classification model using TensorFlow.js, covering data preprocessing with sprite images, model construction, training, and evaluation, while providing complete JavaScript code examples and practical tips for handling ArrayBuffer, DataView, and visualization.

BrowserJavaScriptMNIST

0 likes · 8 min read

Build a Browser‑Based MNIST Classifier with TensorFlow.js: A Step‑by‑Step Guide

政采云技术

Jun 14, 2020 · Frontend Development

Web-Based Face Recognition Authentication Using face-api.js

This article explains how to implement a web‑browser face‑recognition authentication system by capturing video streams with WebRTC, detecting faces with face‑api.js, converting images to Base64, and leveraging Baidu AI services for identity verification and liveness detection.

FrontendJavaScriptWebRTC

0 likes · 14 min read

Web-Based Face Recognition Authentication Using face-api.js

Taobao Frontend Technology

Apr 22, 2020 · Frontend Development

How Pipcook Leverages TensorFlow.js to Bring AI to Front‑End Development

This article explains how Pipcook combines TensorFlow.js with a JavaScript‑friendly pipeline to enable front‑end engineers to process data, train models, and deploy AI solutions, while comparing its approach to TFX and outlining future development and contribution opportunities.

AIFrontendJavaScript

0 likes · 11 min read

How Pipcook Leverages TensorFlow.js to Bring AI to Front‑End Development

58 Tech

Jul 16, 2019 · Frontend Development

The Role of Artificial Intelligence in Frontend Development: Opportunities, Tools, and Challenges

This article explores how artificial intelligence is influencing frontend development, detailing recent breakthroughs, practical frameworks like TensorFlow.js, real‑world applications, advantages, limitations, and emerging solutions for deploying machine learning models directly in browsers.

FrontendMachine LearningWeb Development

0 likes · 13 min read

The Role of Artificial Intelligence in Frontend Development: Opportunities, Tools, and Challenges

58 Tech

Jun 13, 2019 · Artificial Intelligence

AI and Front‑End Integration: Insights from the 58 Group Technical Salon

The article summarizes the 58 Group technical salon where Xiaomi AI experts and 58 front‑end architects discussed deep‑learning applications in graphics animation, model training and optimization techniques, and practical TensorFlow.js workflows for bringing AI capabilities to web front‑ends.

AIFront-endWeb Development

0 likes · 9 min read

AI and Front‑End Integration: Insights from the 58 Group Technical Salon