Characterizing Disparity Between Edge Models and High-Accuracy Base Models for Vision Tasks
Z Wang, S Nirjon - arXiv preprint arXiv:2407.10016, 2024 - arxiv.org
Edge devices, with their widely varying capabilities, support a diverse range of edge AI
models. This raises the question: how does an edge model differ from a high-accuracy …
models. This raises the question: how does an edge model differ from a high-accuracy …
Efficient tensor decomposition-based filter pruning
In this paper, we present CORING, which is short for effiCient tensOr decomposition-based
filteR prunING, a novel filter pruning methodology for neural networks. CORING is crafted to …
filteR prunING, a novel filter pruning methodology for neural networks. CORING is crafted to …
[HTML][HTML] Construction of a Deep Learning Model for Unmanned Aerial Vehicle-Assisted Safe Lightweight Industrial Quality Inspection in Complex Environments
Z Jing, R Wang - Drones, 2024 - mdpi.com
With the development of mobile communication technology and the proliferation of the
number of Internet of Things (IoT) terminal devices, a large amount of data and intelligent …
number of Internet of Things (IoT) terminal devices, a large amount of data and intelligent …
Targeted and Automatic Deep Neural Networks Optimization for Edge Computing
DNNs, commonly employed for complex tasks such as image and language processing, are
increasingly sought for deployment on Internet of Things (IoT) devices. These devices …
increasingly sought for deployment on Internet of Things (IoT) devices. These devices …
[PDF][PDF] Explaining the Difference Between Edge Models and High-Accuracy Base Models for Vision Tasks
Z Wang, S Nirjon - Parameters (M) - ewsn.org
Recent literature has proposed numerous neural network models for edge devices that aim
to solve the same learning task, eg, image classification and object detection. These models …
to solve the same learning task, eg, image classification and object detection. These models …