Labs Introduction The generation of image data has always been a challenging task in the field of computer vision. Traditional methods for generating image data are usually based on mathematical models, making it difficult to create realistic images. With the emergence of deep neural networks and large-scale datasets, significant progress has been made in image … Read more
Contrastive Language-Image Pre-training (CLIP) has gained wide attention for its excellent zero-shot performance and outstanding transferability. However, training such large models typically requires substantial computation and storage, posing a barrier for general users with consumer-grade computers. To address this observation, this paper explores how to achieve competitive performance using only an Nvidia RTX 3090 GPU … Read more
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
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
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
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
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
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
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
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