The goals of this research were to search for Convolutional Neural Network (CNN)
architectures, suitable for an on-device processor with limited computing resources …

We introduce a new family of neural network models called Convolutional Dynamic
Alignment Networks (CoDA-Nets), which are performant classifiers with a high degree of …

The integration of deep learning (DL) into image processing has driven transformative
advancements, enabling capabilities far beyond the reach of traditional methodologies. This …

The aim of this work is to search for a Convolutional Neural Network (CNN) architecture that
performs optimally across all factors, including accuracy, memory footprint, and computing …

Increasing the depth of the neural network and implementing the ensemble of neural
networks are two main methods to improve the accuracy of gas recognition algorithms …

Tourism image classification plays an important role in the study of clarifying the real
perception of tourism resources by tourists, which cannot be studied in depth by human …

The processing speed and memory footprint are important factors for applications
processing on resource-constrained devices such as IoT devices and embedded systems …

Deep learning technologies have been applied in various computer vision tasks in recent
years. However, deep models suffer performance decay when some unforeseen data are …

We introduce a new family of neural network models called Convolutional Dynamic
Alignment Networks (CoDA Nets), which are performant classifiers with a high degree of …

目前, 深度学习模型在现实中得到了广泛的应用, 当这些模型应用于不同的环境时,
可以利用环境中样本分布等经验来进一步提高分类的准确率. 基于此, 本文提出了基于用户指导 …