30,873 research outputs found
Structured Pruning for Deep Convolutional Neural Networks: A survey
The remarkable performance of deep Convolutional neural networks (CNNs) is
generally attributed to their deeper and wider architectures, which can come
with significant computational costs. Pruning neural networks has thus gained
interest since it effectively lowers storage and computational costs. In
contrast to weight pruning, which results in unstructured models, structured
pruning provides the benefit of realistic acceleration by producing models that
are friendly to hardware implementation. The special requirements of structured
pruning have led to the discovery of numerous new challenges and the
development of innovative solutions. This article surveys the recent progress
towards structured pruning of deep CNNs. We summarize and compare the
state-of-the-art structured pruning techniques with respect to filter ranking
methods, regularization methods, dynamic execution, neural architecture search,
the lottery ticket hypothesis, and the applications of pruning. While
discussing structured pruning algorithms, we briefly introduce the unstructured
pruning counterpart to emphasize their differences. Furthermore, we provide
insights into potential research opportunities in the field of structured
pruning. A curated list of neural network pruning papers can be found at
https://github.com/he-y/Awesome-Pruning . A dedicated website offering a more
interactive comparison of structured pruning methods can be found at:
https://huggingface.co/spaces/he-yang/Structured-Pruning-Survey .Comment: Accepted by IEEE Transactions on Pattern Analysis and Machine
Intelligenc
Measurement of body temperature and heart rate for the development of healthcare system using IOT platform
Health can be define as a state of complete mental, physical and social well-being and not merely the absence of disease or infirmity according to the World Health Organization (WHO) [1]. Having a healthy body is the greatest blessing of life, hence healthcare is required to maintain or improve the health since the healthcare is the maintenance or improvement of health through the diagnosis, prevention, and treatment of injury, disease, illness, and other mental and physical impairments in human beings. The novel paradigm of Internet of Things (IoT) has the potential to transform modern healthcare and improve the well-being of entire society [2].
IoT is a concept aims to connec
A survey of cost-sensitive decision tree induction algorithms
The past decade has seen a significant interest on the problem of inducing decision trees that take account of costs of misclassification and costs of acquiring the features used for decision making. This survey identifies over 50 algorithms including approaches that are direct adaptations of accuracy based methods, use genetic algorithms, use anytime methods and utilize boosting and bagging. The survey brings together these different studies and novel approaches to cost-sensitive decision tree learning, provides a useful taxonomy, a historical timeline of how the field has developed and should provide a useful reference point for future research in this field
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