Background: Dermoscopic image segmentation using deep learning algorithms is a critical
technology for skin cancer detection and therapy. Specifically, this technology is a spatially …

Combining disease categories and crop species leads to complex intra-class and inter-class
differences. Significant intra-class difference and subtle inter-class difference pose a great …

In this paper, a global convolutional network (GCN)-based fast coding unit (CU) partition
method of intra-mode VVC is proposed. By using the GCN module with large kernel size …

Current keyword spotting systems are typically trained with a large amount of pre-defined
keywords. Recognizing keywords in an open-vocabulary setting is essential for …

Understanding the fundamental mechanism behind the success of transformer networks is
still an open problem in the deep learning literature. Although their remarkable performance …

In the Machine Learning research community, there is a consensus regarding the
relationship between model complexity and the required amount of data and computation …

Recently, vision architectures based exclusively on multi-layer perceptrons (MLPs) have
gained much attention in the computer vision community. MLP-like models achieve …

To alleviate the social contradiction between limited medical resources and increasing
medical needs, the medical image-assisted diagnosis based on deep learning has become …

Quantization is wildly taken as a model compression technique, which obtains efficient
models by converting floating-point weights and activations in the neural network into lower …

Vision multi-layer perceptrons (MLPs) have shown promising performance in computer
vision tasks, and become the main competitor of CNNs and vision Transformers. They use …