Transformer-based large language models (LLMs) have achieved great succe...
Self-supervised learning (SSL) has achieved promising downstream perform...
In this paper we introduce SiamMask, a framework to perform both visual
...
3D object detection in autonomous driving aims to reason "what" and "whe...
In recent years, colorectal cancer has become one of the most significan...
Cervical cancer is the seventh most common cancer among all the cancers
...
Self-supervised learning on large-scale Vision Transformers (ViTs) as
pr...
Gastric cancer is the fifth most common cancer in the world. At the same...
Open-vocabulary object detection aims to detect novel object categories
...
Background and purpose: Colorectal cancer has become the third most comm...
This chapter proposes and provides an in-depth discussion of a scalable
...
Exploiting convolutional neural networks for point cloud processing is q...
GasHisSDB is a New Gastric Histopathology Subsize Image Database with a ...
Image classification has achieved unprecedented advance with the the rap...
Cervical cancer is a very common and fatal cancer in women, but it can b...
For deep learning methods applied to the diagnosis of gastric cancer
int...
The Analog Ensemble (AnEn) technique has been shown effective on several...
The rising temperature is one of the key indicators of a warming climate...
The encoding of the target in object tracking moves from the coarse
boun...
Object detection and instance segmentation are two fundamental computer
...
Unsupervised video object segmentation has often been tackled by methods...
Multi-modal information is essential to describe what has happened in a
...
The Analog Ensemble (AnEn) method tries to estimate the probability
dist...
Inspired by the fact that different modalities in videos carry complemen...
In this paper we illustrate how to perform both visual object tracking a...
Recently, Siamese networks have drawn great attention in visual tracking...
Local features at neighboring spatial positions in feature maps have hig...
Many scientific problems require multiple distinct computational tasks t...
Spectral clustering is a powerful tool for unsupervised data analysis. I...
Computational color constancy is a very important topic in computer visi...