High-Performance and Lightweight AI Model for Robot Vacuum Cleaners with Low Bitwidth Strong Non-Uniform Quantization
Artificial intelligence (AI) plays a critical role in the operation of robot vacuum cleaners, enabling them to intelligently navigate to clean and avoid indoor obstacles. Due to limited computational resources, manufacturers must balance performance and cost. This necessitates the development of lig...
Main Authors: | Qian Huang, Zhimin Tang |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2023-07-01
|
Series: | AI |
Subjects: | |
Online Access: | https://www.mdpi.com/2673-2688/4/3/29 |
Similar Items
-
Towards Indoor Suctionable Object Classification and Recycling: Developing a Lightweight AI Model for Robot Vacuum Cleaners
by: Qian Huang
Published: (2023-09-01) -
Bit-Weight Adjustment for Bridging Uniform and Non-Uniform Quantization to Build Efficient Image Classifiers
by: Xichuan Zhou, et al.
Published: (2023-12-01) -
Two Novel Non-Uniform Quantizers with Application in Post-Training Quantization
by: Zoran Perić, et al.
Published: (2022-09-01) -
Iterative Algorithm for Parameterization of Two-Region Piecewise Uniform Quantizer for the Laplacian Source
by: Jelena Nikolić, et al.
Published: (2021-11-01) -
Whether the Support Region of Three-Bit Uniform Quantizer Has a Strong Impact on Post-Training Quantization for MNIST Dataset?
by: Jelena Nikolić, et al.
Published: (2021-12-01)