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PointNet 论文总结 | 巽离阁
https://sptau.github.io/posts/2ed13e41.html
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
WSL 安装总结 | 巽离阁
https://sptau.github.io/posts/f1f0ebac.html
配置 WSL 在 Ubuntu 上进行训练
PyTorch 搭建 DenseNet 模型对 CIFAR10 数据集分类总结 | 巽离阁
https://sptau.github.io/posts/25308b42.html
本次实验以 [Densely Connected Convolutional Networks] 作为主要参考来源,使用 PyTorch 搭建 DenseNet 模型实现对 CIFAR10 数据集的训练和测试
CNN 参数更新 | 巽离阁
https://sptau.github.io/posts/98f1e749.html#fn_1
从 LeNet-5 回顾 CNN 的参数更新过程
ICCV 2017 扫读总结 | 巽离阁
https://sptau.github.io/posts/c254b0.html
扫读 ICCV 2017 论文集中感兴趣的论文,将根据 略读 - 细读 - 精读 的方式快速过一遍
基于机器学习的相邻时序植物点云配准总结 | 巽离阁
https://sptau.github.io/posts/5f7835f6.html
该项目主要是利用相机固定时间间隔拍摄环绕植物的图像,利用软件重建为点云后,将相邻时序的植物点云进行配准,实现叶片的配对
| 巽离阁
https://sptau.github.io/404.html?
江湖行走 初心依旧 来年还乡 一梦千秋
PyTorch 搭建 ResNet 模型对 CIFAR10 数据集分类总结 | 巽离阁
https://sptau.github.io/posts/cfb33f60.html
本次试验将以 [Deep Residual Learning for Image Recognition] 作为主要参考来源,使用 PyTorch 搭建 ResNet 模型实现对 CIFAR10 数据集的训练和测试
WSL 深度学习总结 | 巽离阁
https://sptau.github.io/posts/e5bb69fc.html
在 WSL 下复现 PointNet 代码
点云补全论文阅读总结 | 巽离阁
https://sptau.github.io/posts/781c276d.html
阅读 2017-2023 年的 ICCV 、 CVPR 、 ECCV 等会议论文集中以补全 (Completion) 为关键词的论文
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