Equipping Mobile Robots with ‘Smart Eyes’ | New AI Scenarios

Equipping Mobile Robots with 'Smart Eyes' | New AI Scenarios

In a factory workshop in Hunan Xiangjiang New Area, rows of robots are busy on the production line. On the assembly line, robotic arms move like agile hands, easily grasping, rotating, and installing various parts… With the sound of machinery starting up, each of their movements is precise and efficient, ensuring a seamless production process. … Read more

From The Three Elements of AI to The Path of Four Elements

From The Three Elements of AI to The Path of Four Elements

In April 2024, Zhang Bo, an academician of the Chinese Academy of Sciences, professor of the Department of Computer Science at Tsinghua University, and honorary dean of the Tsinghua University Institute of Artificial Intelligence, delivered a speech titled “Entering the ‘No-Man’s Land’, Exploring the Path of Artificial Intelligence” at the Tsinghua University “Humanities Tsinghua Forum”. … Read more

Understanding Cloud Computing, Big Data, AI, and IoT Concepts

Understanding Cloud Computing, Big Data, Artificial Intelligence, and Internet of Things Concepts Through Diagrams In recent years, the terms “Cloud Computing, Big Data, Artificial Intelligence, Internet of Things” have become very popular, with major news headlines competing to report on them. These technology concepts also serve as a guiding compass for the future of internet … Read more

Research on Third-Class AI Medical Devices: Case Studies

Research on Third-Class AI Medical Devices: Case Studies

Research on Third-Class AI Medical Devices: Case Studies AI medical devices include independent software that is itself a medical device (AI SaMD) and medical devices containing AI software components (AI SiMD). Third-class medical devices are directly approved by the National Medical Products Administration, and the registration and regulation of third-class deep learning independent software have … Read more

Optimizing Small Target Detection Without Resizing

Optimizing Small Target Detection Without Resizing

Click on the above “Beginner’s Visual Learning”, select to add Star or “Pinned” Heavyweight content delivered first-hand Introduction Traditional deep learning-based object detection networks often resize images during the data preprocessing stage to achieve a uniform size and scale in the feature maps. The resizing aims to facilitate model propagation and fully connected classification. However, … Read more

Comprehensive Summary of Loss Functions

Author: mingo_敏 Editor: Deep Learning Natural Language Processing Link:https://blog.csdn.net/shanglianlm/article/details/85019768 Many of the loss functions in TensorFlow and PyTorch are similar; here we take PyTorch as an example. 19 Types of Loss Functions 1. L1 Loss L1Loss Calculates the absolute difference between output and target. torch.nn.L1Loss(reduction='mean') Parameters: reduction – three values: none: no reduction; mean: returns … Read more

Agentic Reasoning: Unveiling Deep Research with Multi-Agent Models

Agentic Reasoning: Unveiling Deep Research with Multi-Agent Models

Hello everyone! This is a channel focused on cutting-edge AI and agents~ Following the releases of Deep Research by Google, OpenAI, and Perplexity, the University of Oxford has published a paper titled “Agentic Reasoning: Reasoning LLMs with Tools for the Deep Research” and has open-sourced the code. Today, let’s take a detailed look at their … Read more

The Development of Artificial Intelligence and Intelligent Computing

The Development of Artificial Intelligence and Intelligent Computing

The field of artificial intelligence has recently experienced explosive growth led by generative AI large models. On November 30, 2022, OpenAI launched an AI conversational chatbot, ChatGPT, whose outstanding natural language generation capabilities attracted widespread attention worldwide, surpassing 100 million users in just two months. This led to a wave of large models both domestically … Read more

Introduction to Image Edge and Contour Extraction Methods Based on Deep Learning

Introduction to Image Edge and Contour Extraction Methods Based on Deep Learning

Click the above“Beginner’s Visual Learning”, select to addstar or “pin” Important content delivered promptly Image source: Internet Author: Huang Yu, Chief Scientist at Singularity Auto Editor: Hoh Xil Source: https://zhuanlan.zhihu.com/p/78051407 Introduction: The extraction of edges and contours is a very tricky task, as details may be obscured by overly strong image lines. Texture itself is … Read more