Transformer-based deep imitation learning for dual-arm robot manipulationHeecheol KimYasuo KuniyoshiYoshiyuki Ohmura
深度学习(Deep Learning) Transformer 机器学习 赞同2添加评论 分享喜欢收藏申请转载 写下你的评论... 还没有评论,发表第一个评论吧 推荐阅读 Transformer中的归一化(一):什么是归一化&为什么要归一化 Gordo...发表于自然语言处... Transformer:新一代序列建模大杀器 提到预训练...
【重识别 Decoder 相似度】Transformer-Based Deep Image Matching for Generalizable Person Re-identification 煎饼果子不要果子 快快乐乐,没有脑袋2 人赞同了该文章 主要思路和创新点 本文针对的任务方向为广义行人重识别,似乎指的是跨数据集训练和测试的重识别。实际上,先前已有一些文章将 Transformer 应用到行...
(MSMU-RA)in a downlink cellular scenario with the aim of maximizing system spectral efficiency while guaranteeing user fairness.We first model the MSMU-RA problem as a dual-sequence decision-making pro-cess,and then solve it by a novel Transformer-based deep reinforcement learning(TDRL)approach....
During the diagnostic process, clinicians leverage multimodal information, such as the chief complaint, medical images and laboratory test results. Deep-learning models for aiding diagnosis have yet to meet this requirement of leveraging multimodal infor
During the diagnostic process, clinicians leverage multimodal information, such as the chief complaint, medical images and laboratory test results. Deep-learning models for aiding diagnosis have yet to meet this requirement of leveraging multimodal infor
Mixture Model (GMM), and the language model (LM) was based on n-gram models. The components of these systems were trained separately, which made it difficult to manage and configure them, which led to a decrease in the efficiency of using these systems. With the advent of deep learning,...
3) Feature Learning: 最后一层encoder layer输出的class token为全局特征向量 ,其余对应 N 个patch的输出为 。随后采用BNNeck技巧的交叉熵损失 和soft-margin三元组损失,即: 。 TransReID 1) Side Information Embedding: transformer模型可以很好的把side information编码到embedding representation中,对其信息进行结合,且...
[1] Deep Residual Learning for Image Recognition [2] Bottleneck Transformers for Visual Recognition [3] An image is worth 16x16 words: Transformers for image recognition at scale [4] Tokens-to-Token ViT: Training Vision Transformers from Scratch on ImageNet ...
(4)deepfactor (5)deepstate (6)neuralprophet (7)其它待补充 6 时间序列分类与回归中的模型结构 (1)shapenets (2)minirocket (3)其它待补充 7.GNN系列 (1) 常规的gcn/graphsage/gat/gin (2)mtgnn (3)其它待补充 8.将forecasting问题转化为cv问题 (1)GAF (2)mtf (3)recurrence (4)其它待补充 9 其...