Category: Study

17 Posts

【笔记】实用机器学习 – Data I
李沐老师实用机器学习学习笔记,数据I 1.1 课程介绍 工业界有很多机器学习的应用, 例如传统的制造业中,可以利用传感器,自动找出出现问题的设备 ?️ 授课视频: 跟李沐学AI的个人空间_哔哩哔哩_Bilibili ? 课件: Syllabus - Practical Machine Learning 机器学习工作流: 定义问题: 找出最关键的问题,在一个项目中,最能产生效果的问题 数据:收集高质量的数据,需要考虑隐私问题 训练模型:模型现在越来越复杂,成本越来越高 部署模型:为了实时化 监控:要不断的监控,可能存在偏向性问题 机器学习的角色: 软件设计工程师: 开发维护数据流,模型训练和服务流 领域专家:有商业眼光,发现问题 数据科学家:全栈能力,数据挖掘,模型训练和部署 机器学习专家:模型定制化,模型调优 1.2 数据获取 外部数据集 数据集的三种类型: 学术数据集:干净,简单,但是选择不多,通常是小规模的 比赛数据集:接近于真实的机器学习应用。缺点是简单,数量少 原始数据:有更大的灵活性,但需要更多的预处理 生成数据集 使用GAN 仿真 数据增广
BoTNet (Bottleneck Transformers)
BoTNet (2021-01): 将 Self-Attention 嵌入 ResNet 文章:Bottleneck Transformers for Visual Recognition 论文: https://arxiv.org/abs/2101.11605 摘要: We present BoTNet, a conceptually simple yet powerful backbone architecture that incorporates self-attention for multiple computer vision tasks including image classification, object detection and instance segmentation. By just replacing the spatial convolutions with global self-attention in…
[Reading Notes] Arbitrary Style Transfer in Real-time with Adaptive Instance Normalization
Source Paper: [ICCV'2017] https://arxiv.org/abs/1703.06868 Authors: Xun Huang, Serge Belongie Code: https://github.com/xunhuang1995/AdaIN-style Contributions In this paper, the authors present a simple yet effective approach that for the first time enables arbitrary style transfer in real-time. Arbitrary style transfer: takes a content image $C$ and an arbitrary style image $S$ as inputs,…
[Reading Notes] Collaborative Distillation for Ultra-Resolution Universal Style Transfer
Source Authors: Huan Wang, Yijun Li, Yuehai Wang, Haoji Hu, Ming-Hsuan YangPaper: [CVPR2020] https://arxiv.org/abs/2003.08436Code: https://github.com/mingsun-tse/collaborative-distillation Contributions It proposes a new knowledge distillation method "Collobrative Distillation" based on the exclusive collaborative relation between the encoder and its decoder. It proposes to restrict the students to learn linear embedding of the teacher's…
YOLObile: Real-Time Object Detection on Mobile Devices via Compression-Compilation Co-Design
Paper Information Paper: YOLObile: Real-Time Object Detection on Mobile Devices via Compression-Compilation Co-Design Authors: Yuxuan Cai, Hongjia Li, Geng Yuan, Wei Niu, Yanyu Li, Xulong Tang, Bin Ren, Yanzhi Wang Paper: https://arxiv.org/abs/2009.05697 Github: https://github.com/nightsnack/YOLObile Objective: Real-time object detection for mobile devices. Study notes and presentation: Download: https://connectpolyu-my.sharepoint.com/:p:/g/personal/18048204r_connect_polyu_hk/EcRbix5iqshBglmxuLurS-sBBFmbrk8chRkim1y54-yOXw?e=8Qdfmd This is an…
A Image Quality Evaluation Toolbox For MATLIB
MeTriX MuX Visual Quality Assessment Package The name of the package is MeTriX MuX Visual Quality Assessment Package. The official website does not work (attempt on 08-Sep-2019), and the download link http://foulard.ece.cornell.edu/gaubatz/metrix_mux/metrix_mux_1.1.zip is invaild. I find a copy that is from a github repository https://github.com/sattarab/image-quality-tools/tree/master/metrix_mux Installation It can be easily…