Implementation of research papers on Deep Learning+ NLP+ CV in Python using Keras, Tensorflow and Scikit Learn. - GauravBh1010tt/DeepLearn
deep learning techniques into supervised, unsupervised, reinforcement, and hybrid learning-based models. In addition to address each category, a brief description of these categories and their models is provided. Some of the critical topics in deep learning, namely, transfer, federated, and online le...
Some labs and research groups that are actively working on deep learning: University of Toronto -Machine Learning Group(Geoffrey Hinton, Rich Zemel, Ruslan Salakhutdinov, Brendan Frey, Radford Neal) Université de Montréal –MILA Lab(Yoshua Bengio, Pascal Vincent, Aaron Courville, Roland Memisevic) ...
Plan A: Overall picture recognition. Image preprocessing stage, the image processing into a uniform format size, and the use of transfer learning. In the training stage, the water meter pictures were input into the deep learning model to learn ten categories. Categorize each goal. According to ...
Deep learning is an important research field of machine learning. In recent years, many breakthroughs have been made in the field of target detection, which has been applied to specific target detection tasks. This paper first introduces the representative traditional detection methods and discusses th...
the potential application areas. In Section “Research Directions and Future Aspects”, we discuss various research issues of deep learning-based modeling and highlight the promising topics for future research within the scope of our study. Finally, Section “Concluding Remarks” concludes this paper....
To thoroughly review the literature, a two-step method was used to retrieve all the studies on relevant topics. First, we conducted a search of the computerized bibliographic databases including PubMed and Web of Science. The search strategy is detailed in Supplementary Appendix 1. The literature...
topics such as Monte Carlo Learning, Temporal Difference Learning, and SARSA would require whole blogs just themselves (If you are interested, though, please take a listen to David Silver’sLecture 4andLecture 5). Right now, however, I’m going to jump ahead to value function approximation an...
Research Overview on Edge Detection Algorithms Based on Deep Learning and Image Fusion (深度学习和图像融合的边缘检测算法综述) 1. Introduction 如何快速的、准确的提取图像的边缘信息是最近研究的热门,最近的研究表明边缘检测很重要。... 边缘检测主要分为两类: 传统的方法和基于深度学习的方法。 手工的...
research topics, which are useful for those wanting to specialize in DRL research. To help readers gain a deep understanding of DRL and quickly apply the techniques in practice, the third part presents mass applications, such as the intelligent transportation system and learning to run, with ...