Deep Learning and Its Applications to Signal and Information Processing [Exploratory DSP]

By Dong Yu, Li Deng. IEEE Signal Processing Magazine, 2011

387 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Computer Vision and Pattern Recognition, Signal Processing

View Paper: https://www.semanticscholar.org/paper/4c2fedecddcae64514ad99b7301ad6e04654f10d

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

1. Li Deng
2. Jianfeng Gao
3. Dong Yu
4. Xiaodong He
5. Yoshua Bengio
6. Jianshu Chen
7. Mohit Bansal
8. Hamid Palangi

In Computer Vision and Pattern Recognition

1. Jianfeng Gao
2. Li Deng
3. Xiaodong He
4. Dong Yu
5. Luc Van Gool
6. Trevor Darrell
7. Dacheng Tao
8. Xiaogang Wang

In Signal Processing

1. Li Deng
2. Dong Yu
3. Xiaodong He
4. Jianshu Chen
5. Jianfeng Gao
6. Jinyu Li
7. Xiao-Lei Zhang
8. Rabab Kreidieh Ward

Citations in the corpus

• Neural information retrieval: at the end of the early years (2017, background): “For general introductions to deep learning, see Arel et al. (2010), Deng (2014), Goodfellow et al. (2016), LeCun et al. (2015), Schmidhuber (2015), Yu and Deng (2011), and Bengio (2009).”
• Deep Crossing: Web-Scale Modeling without Manually Crafted Combinatorial Features (2016, background): “Deep Learning [9, 20, 16] carries the promise of learning from individual features without manual intervention [17, 21].”
• Automatic language identification using deep neural networks (2014, background): “Deep neural networks have recently proved to be successful in diverse and challenging machine learning applications, such as acoustic modelling [13] [14], visual object recognition [15] and many others [16]; especially when a large amount of training data is available.”
• Epileptic Seizures Detection Using Deep Learning Techniques: A Review (2020, methodology): “GATED RECURRENT UNIT (GRU) One variation of LSTM is GRU, which combines the input and forgets gates into one update gate [16], [17], [18], [19].”
• Deep Belief Networks Based Voice Activity Detection (2013, background): “Recently, DBN has received much attention in both the machine learning community [36] and the signal processing community [37] with successful applications to the speech recognition [4]–[9], natural language processing [38], etc.”
• A Survey on Machine Learning Techniques for Cyber Security in the Last Decade (2020, background): “These areas attracted the research and academic community over the last decade [200]–[203].”
• A survey of deep neural network architectures and their applications (2017, methodology): “In addition, by adopting machine learning methods, the human-level artificial intelligence (AI) has been improved as well, see [101,137,165] for more discussions.”
• Deep Sentence Embedding Using Long Short-Term Memory Networks: Analysis and Application to Information Retrieval (2015, methodology): “The BM25 model uses the bag-of-words representation for queries and documents, which is a state-of-the-art document ranking model based on term matching, widely used as a baseline in IR society.”