Energy-Efficient and Improved Image Recognition with Conditional Deep Learning
By Priyadarshini Panda, Abhronil Sengupta, Kaushik Roy. 2017
43 citations recorded by the source corpus.
Subfields: Artificial Intelligence, Computer Vision and Pattern Recognition, Efficiency & Compression
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
- Simone Scardapane
- Chun-Yi Lee
- Michele Scarpiniti
- Aurelio Uncini
- Enzo Baccarelli
- Chi Lo
- Shih-Chieh Chang
- Yu-Yi Su
In Computer Vision and Pattern Recognition
- Michele Scarpiniti
- Enzo Baccarelli
- Simone Scardapane
- Aurelio Uncini
- Chun-Yi Lee
- Chi Lo
- Shih-Chieh Chang
- Yu-Yi Su
In Efficiency & Compression
Citations in the corpus
- Why Should We Add Early Exits to Neural Networks? (2020, methodology): “Focusing only on early exit i , using the auxiliary classifier improves the efficiency of the network whenever the following relation is met [ 56 ] : Because the number of possible placements of M early exits in a network grows exponentially in the network’s depth L , the optimal placement according…”
- A Dynamic Deep Neural Network Design for Efficient Workload Allocation in Edge Computing (2017, methodology): “Unfortunately, if the confidence levels of two or more classes are close, CDL may lead to incorrect predictions.”