Data Augmentation

Research Progress on Small Target Detection Technology Based on Deep Learning

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Research Progress on Small Target Detection Technology Based on Deep Learning

Author: Liu Genghuan Paper Title: Research Progress on Small Target Detection Technology Based on Deep Learning (Invited) Authors: Liu Genghuan1,2,3, Zeng Xiangjin1,2,3, Dou Jiazhen1,2,3, Ren Zhenbo4, Zhong Liyun1,2,3, Di Janglei1,2,3, Qin Yuwen1,2,3 Affiliation: 1. Guangdong University of Technology, School of Information Engineering, Advanced Photonic Technology Research Institute 2. Key Laboratory of Perceptual Fusion Photonic Technology, … Read more

10 TensorFlow 2.x Tips for Efficient Use

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10 TensorFlow 2.x Tips for Efficient Use

Author | Rohan Jagtap Compiled by | ronghuaiyang Source | AI Park TensorFlow 2.x provides a lot of simplicity in building models and overall use of TensorFlow. In this article, we will explore 10 features of TF 2.0 that make using TensorFlow smoother, reduce the number of lines of code, and improve efficiency. TensorFlow 2.x … Read more

Enhancing Multi-Modal Data: MixGen from Amazon’s Li Mu Team

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Enhancing Multi-Modal Data: MixGen from Amazon's Li Mu Team

Follow our public account to discover the beauty of CV technology This article shares the paper「MixGen: A New Multi-Modal Data Augmentation」, how to perform data augmentation on multi-modal data? The Amazon Li Mu team proposed a simple and effective MixGen, significantly improving performance across multiple multi-modal tasks! Details are as follows: Paper link: https://arxiv.org/abs/2206.08358 Code … Read more

PaddleOCR v2: 7% Improvement in Accuracy, 220% Speed Boost

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PaddleOCR v2: 7% Improvement in Accuracy, 220% Speed Boost

Follow the official WeChat account “ML_NLP“ Set as “Starred“, delivering heavy content to you first! 1. Introduction Engineers in the OCR field must have heard of the PaddleOCR project, whose main recommended PP-OCR algorithm has been widely used by developers in China and abroad, In just half a year,the total number of stars has exceeded … Read more

Overview of Neural Machine Translation Methods for Low-Resource Languages

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Overview of Neural Machine Translation Methods for Low-Resource Languages

Written by Zhang Xiaojun, Lai Wen Abstract: Although neural machine translation models perform well with language pairs that have large-scale high-quality parallel corpora, experiments show that the performance of neural machine translation significantly decreases for low-resource language pairs, even underperforming traditional statistical machine translation models. This article analyzes the current challenges faced by neural machine … Read more

Path to Efficient and Robust Natural Language Processing

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Path to Efficient and Robust Natural Language Processing

Guest Speaker | Yuxiang Wu Transcript Organizer | Lin Zhang Guest Speaker Introduction Yuxiang Wu, PhD from University College London.Currently pursuing a PhD at University College London (UCL), under the supervision of Professor Sebastian Riedel and Professor Pontus Stenetorp.His research areas include Natural Language Processing and Machine Learning, with a current focus on pre-trained language … Read more

Breaking the BERT Ceiling: 11 Techniques to Boost NLP Classification SOTA

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Breaking the BERT Ceiling: 11 Techniques to Boost NLP Classification SOTA

Follow the public account “ML_NLP“ Set as “Starred“, heavy content delivered first-hand! Source | Xixiaoyao’s Cute Selling House At this point in 2020, our focus on NLP classification tasks is no longer about how to construct models or being fixated on what classification models look like. Just like the current focus in the CV field, … Read more

A Cutting-Edge Review of Diffusion Models and Knowledge Graphs

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A Cutting-Edge Review of Diffusion Models and Knowledge Graphs

Approximately 7500 words, suggested reading time 16 minutes. This article introduces a new knowledge graph diffusion model named DiffKG, which combines generative diffusion models with data augmentation paradigms to achieve robust knowledge graph representation learning. The importance of knowledge graphs (graph networks) in recommendation systems is self-evident, but not all relationships are relevant to the … Read more

Audio Augmentation in TensorFlow and PyTorch

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Audio Augmentation in TensorFlow and PyTorch

Source: Deephub Imba This article is approximately 2100 words long and is suggested to be read in 9 minutes. This article will introduce two methods to apply augmentation to datasets in TensorFlow. For image-related tasks, common data augmentation methods include rotating, blurring, or resizing images. This is because the inherent properties of images make data … Read more

10 TensorFlow 2.x Tips for Efficient Usage

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10 TensorFlow 2.x Tips for Efficient Usage

Click on the above “Beginner Learning Vision”, choose to add Star or Top ” Important content delivered at the first time Author | Rohan Jagtap Compiled by | ronghuaiyang Source | AI Park TensorFlow 2.x provides a lot of simplicity in building models and the overall use of TensorFlow. In this article, we will explore … Read more