The existing deep learning methods for human fall detection have difficulties to distinguish
falls from similar daily activities such as lying down because of not using the 3D network …

The size and complexity of CNN models are increasing and as a result they are requiring
more computational and memory resources to be used effectively. Use of a lower bit width …

Convolutional neural networks (CNNs) have achieved significant performance on various
real-life tasks. However, the large number of parameters in convolutional layers requires …

Vision Transformers (ViTs) have emerged as versatile and high-performance models for
various tasks such as image classification, object detection, and semantic segmentation …

The challenges of the aging population is becoming more and more prominent worldwide.
Among them, in the face of the elderly fall phenomenon, human fall detection technology …

Existing convolutional neural networks (CNNs) have achieved significant performance on
various real-life tasks, but a large number of parameters in convolutional layers requires …

ABSTRACT Convolutional Neural Networks (CNNs) have been successfully applied to solve
many reallife problems and paid more and more attention in recent years. However, the …

二值网络在速度, 能耗, 内存占用等方面优势明显, 但会对深度网络模型造成较大的精度损失.
为了解决上述问题, 本文提出了二值网络的“分阶段残差二值化” 优化算法 …

The global population of adults is increasing each year rapidly with the expectation of
billions of people in 2050. Enormous improvements in the technological and medical fields …

Binary neural networks have great resource and computing efficiency, while suffer from long
training procedure and non-negligible accuracy drops, when comparing to the fullprecision …