１．Try to use wavelet transform time-frequency diagram, S-transform time-frequency diagram, W-V transform time-frequency diagram and short-time Fourier time-frequency diagram as data sets for deep learning.
2.Try to improve CNN-LSTM network parameters and reduce training time.
3.Begin to write the paper framework of ICIAE.
4. … Continue Reading ››
期末レポートを完成しました。
研究論文を準備しています。現在、ハードウェア部分のコードに取り組んでいます。
日本語を勉強します。
1.I am writing my AROB thesis.
2.I am running the DCGAN program to try to complete the image generation.
Read three reviews this week.
Single-View 3D reconstruction: A Survey of deep learning methods
A Review of 3D Reconstruction Methods for Visual Deep Learning
Review of 3D reconstruction algorithm research
A Review of 3D Reconstruction Methods for Visual Deep Learning
I am writing a paper recently, and I felt a little confused about expressing the skills I used in this paper. So I read some papers like "Deep layer aggregation", "Center3D", "Objects as points", "CornerNet" and "Deformable Convolutional Networks". The paper is still under writing.
AROBの論文を書きます。
論文のプログラムを実行します。
Uniformer（https://openreview.net/forum?id=nBU_u6DLvoK）:
Introduction:
Combining the ability of aggregation feature context of 3D convolution with the self-attention mechanism of visual transformer, to improve the ability of remote dependence of the model. Uniformer combines the advantages of both and achieves good results in many visual tasks.