The Bright Future of Speech Recognition Technology

The Bright Future of Speech Recognition Technology

Click the “High Technology and Industrialization” above to subscribe! Speech recognition technology enables computers to “understand” human speech through research in signal processing and pattern recognition. In recent years, with the rapid development of deep learning technology, the accuracy of speech recognition systems has significantly improved, reaching or approaching human levels in many fields. Speech … Read more

Simple Algorithm Flow for OCR ID Card Recognition

Simple Algorithm Flow for OCR ID Card Recognition

Click the above “Visual Learning for Beginners“, select to add “Star” or “Top“ Essential content delivered promptly Conducting research on OCR ID card recognition, I will organize the algorithm flow from the perspective of basic image processing. Introduction to OCR Optical Character Recognition (OCR) The goal is to analyze and recognize characters in images, converting … Read more

Understanding Optical Character Recognition (OCR)

Understanding Optical Character Recognition (OCR)

Introduction Optical Character Recognition (OCR) is a branch of computer vision research, belonging to pattern recognition and artificial intelligence, and is an important component of computer science. This article will briefly describe the various components in the field of OCR, using the above image as the main clue. 1. Introduction to Optical Character Recognition Computer … Read more

A Survey on Generative Diffusion Models

A Survey on Generative Diffusion Models

0. Introduction This article reviews deep generative models, particularly diffusion models, and how they endow machines with human-like imagination. Diffusion models show great potential in generating realistic samples, overcoming the posterior distribution alignment obstacles in variational autoencoders and alleviating the instability of adversarial objectives in generative adversarial networks. Diffusion models consist of two interconnected processes: … Read more

StableVideo: Generate Continuous Flicker-Free Videos Using Stable Diffusion

StableVideo: Generate Continuous Flicker-Free Videos Using Stable Diffusion

Source: DeepHub IMBA This article is approximately 2100 words long and is recommended to be read in 7 minutes. This article summarizes the paper by Chai et al., which proposes a new method that enables diffusion models to edit videos with high temporal consistency. Using Stable Diffusion to generate videos has always been a research … Read more

Understanding Diffusion Models from a Unified Perspective

Understanding Diffusion Models from a Unified Perspective

Source: PaperWeekly This article is about 8700 words, and it is recommended to read for 15+minutes This article briefly summarizes the derivation process of diffusion models from a unified perspective. Source This article is a compilation of some technical blogs and overviews that I recently read about diffusion models, mainly referencing Calvin Luo’s paper, aimed … Read more

Building an LLM from Scratch: A Step-by-Step Guide

Building an LLM from Scratch: A Step-by-Step Guide

MLNLP community is a well-known machine learning and natural language processing community both domestically and internationally, covering NLP master’s and PhD students, university teachers, and researchers from enterprises. The vision of the community is to promote communication and progress between the academic and industrial sectors of natural language processing and machine learning, especially for beginners. … Read more

Prospects For Large Language Models In The Era Of AGI

Author: Wang Yurun This article is about 5000 words long and suggests a reading time of 10 minutes. The goal of AGI has always been the ultimate vision of artificial intelligence research. 1. What is AGI AGI (Artificial General Intelligence) refers to an artificial intelligence system that can exhibit a wide and flexible range of … Read more

Latest Research: iTransformer – Are Transformers Unsuitable for Multivariate Time Series Forecasting?

Latest Research: iTransformer - Are Transformers Unsuitable for Multivariate Time Series Forecasting?

Paper Title: Inverted Transformers are Effective for Time Series Forecasting Authors: Yong Liu, Tengge Hu, Haoran Zhang, Haixu Wu, Shiyu Wang, Lintao Ma, Mingsheng Long Compiler: Sienna Reviewer: Los Introduction: iTransformer is the latest research achievement in the field of time series forecasting in 2024, currently demonstrating the best performance (SOTA) on standard time series … Read more

Implementing the Transformer Model from Scratch

Implementing the Transformer Model from Scratch

Madio.net Mathematics China /// Editor: Mathematics China Qianxia Since thoroughly understanding the Self_Attention mechanism, the author’s understanding of the Transformer model has risen directly from the underground to the atmosphere, and the meridians have been opened. Before going to sleep every night, that gentle phrase “Attention is all you need” often echoes in my ears, … Read more