Deep Neural Networks (DNNs) have achieved great success in a massive number of artificial intelligence (AI) applications by delivering high-quality computer vision, natural language processing, and virtual reality applications. However, these emerging AI applications also come with increasing computation and memory demands, which are challenging to handle especially for the embedded systems where limited computation/memory resources, tight power budgets, and small form factors are demanded. Challenges also come from the diverse application-specific requirements, including real-time responses, high-throughput performance, and reliable inference accuracy. To address these challenges, we will introduce a series of effective design methods in t...
Deep Neural Networks (DNNs) have become a promising solution to inject AI in our daily lives from se...
With the increasing popularity of machine learning, coupled with increasing computing power, the f...
As deep learning for resource-constrained systems become more popular, we see an increased number of...
As the use of AI-powered applications widens across multiple domains, so do increase the computation...
Deep learning techniques have made great success in areas such as computer vision, speech recognitio...
This paper presents a state-of-the-art overview on how to architect, design, and optimize Deep Neura...
© 2017 IEEE. Deep neural networks (DNNs) are currently widely used for many artificial intelligence ...
Deep neural networks (DNNs) are becoming a key enabling technique for many application domains. Howe...
© 2009-2012 IEEE. Deep learning has recently become im-mensely popular for image recognition, as wel...
Deep learning's recent history has been one of achievement: from triumphing over humans in the game ...
In recent years, deep neural networks (DNNs) have revolutionized the field of machine learning. DNNs...
Large Deep Neural Networks (DNNs) are the backbone of today's artificial intelligence due to their a...
In the recent decade, Intelligent Systems--advanced computer systems that can make useful prediction...
Machine learning has risen to prominence in recent years thanks to advancements in computer technolo...
A number of competing concerns slow adoption of deep learning for computer vision on“edge” devices. ...
Deep Neural Networks (DNNs) have become a promising solution to inject AI in our daily lives from se...
With the increasing popularity of machine learning, coupled with increasing computing power, the f...
As deep learning for resource-constrained systems become more popular, we see an increased number of...
As the use of AI-powered applications widens across multiple domains, so do increase the computation...
Deep learning techniques have made great success in areas such as computer vision, speech recognitio...
This paper presents a state-of-the-art overview on how to architect, design, and optimize Deep Neura...
© 2017 IEEE. Deep neural networks (DNNs) are currently widely used for many artificial intelligence ...
Deep neural networks (DNNs) are becoming a key enabling technique for many application domains. Howe...
© 2009-2012 IEEE. Deep learning has recently become im-mensely popular for image recognition, as wel...
Deep learning's recent history has been one of achievement: from triumphing over humans in the game ...
In recent years, deep neural networks (DNNs) have revolutionized the field of machine learning. DNNs...
Large Deep Neural Networks (DNNs) are the backbone of today's artificial intelligence due to their a...
In the recent decade, Intelligent Systems--advanced computer systems that can make useful prediction...
Machine learning has risen to prominence in recent years thanks to advancements in computer technolo...
A number of competing concerns slow adoption of deep learning for computer vision on“edge” devices. ...
Deep Neural Networks (DNNs) have become a promising solution to inject AI in our daily lives from se...
With the increasing popularity of machine learning, coupled with increasing computing power, the f...
As deep learning for resource-constrained systems become more popular, we see an increased number of...