来源:A Survey on Deep Transfer Learning. (International Conference on Artificial Neural Networks, ICANN, 2018),清华大学 背景:在一些特定领域(如生物信息学、医学、机器人技术),数据的采集和标注成本高,构建大规模数据集非常困难,数据规模限制了深度神经网络的表达能力(本质是少量数据难以确定模型完整的表达空间)。
迁移学习在特定领域如生物信息学、医学、机器人技术中应用广泛，旨在解决数据采集与标注成本高、构建大规模数据集困难的问题。其核心在于利用源域知识迁移至目标域，突破训练数据需独立同分布的限制，旨在提升任务预测性能。迁移学习通过发现和转换源域与目标域的隐性知识，实现深度神经网络预测函数的优化。深度...
So, Deep Transfer Learning(DTL) would be effective as it learns from one task and could work on another task. In addition, Edge Devices(ED) such as IoT, Webcam, Drone, Intelligent Medical Equipment, Robot, etc. are very useful in a pandemic situation. These types of equipment make the ...
论文(Improving information extraction by acquiring external evidence with reinforcement learning) 将信息提取任务建模为马尔科夫决策过程(MDP)该过程动态的使用了实体预测任务, 并提供了一组自动生成的替代方案中选择下一个 query 的方法. 模型流程包含从 发出搜索查询, 从新来源中提取, 识别获得的特征, 然后重复该过...
Yang, and C. Liu. A Survey on Deep Transfer Learning. In International Conference on Artificial Neural Networks, pages 270-279. Springer, 2018. 3Chuanqi Tan, Fuchun Sun, Tao Kong, Wenchang Zhang, Chao Yang, and Chunfang Liu. A survey on deep transfer learning. In ICANN, 2018....
内容提示: A Survey on Deep Transfer LearningChuanqi Tan 1 , Fuchun Sun 2 , Tao Kong 1 ,Wenchang Zhang 1 , Chao Yang 1 , and Chunfang Liu 2State Key Laboratory of Intelligent Technology and SystemsTsinghua National Laboratory for Information Science and Technology (TNList)Department of Computer...
A Survey on Deep Learning in Medical Image Analysis(2) A Survey on Deep Learning in Medical Image Analysis(2) 4. Anatomical application areas 这部分介绍深度学习在医疗图像上的各种应用场景,我们强调一些重要的贡献并且讨论系统在大数据集或者公共挑战数据集上的性能,这些表现在网址 http:\\www.grand-...
A Survey on Deep Transfer Learning to Edge Computing for Mitigating the COVID-19 Pandemic Highlights of the article are: Presented a systematic study of Deep Learning (DL), Deep Transfer Learning (DTL) and Edge Computing(EC) to mitigate COVID-1... A Sufian,A Ghosh,AS Sadiq,... - 《...
As a new classification platform, deep learning has recently received increasing attention from researchers and has been successfully applied to many domains. In some domains, like bioinformatics and robotics, it is very difficult to construct a large-sc
Fig. 1. Different Learning Processes between TraditionalMachine Learning and Transfer Learning 图1展示了传统的学习和迁移学习的学习过程之间的不同。我们可以看到,传统的机器学习技术致力于从每个任务中抓取信息,而迁移学习致力于当目标任务缺少高质量的训练数据时,从之前任务向目标任务迁移知识。