activity
20192022
most citedA Comparative Study on Polyp Classification using Convolutional Neural Networks

86 citations · 94 across the 6 of their papers we have counts for

collaborators

9 papers

cs.CV20222 cited

Accumulated Trivial Attention Matters in Vision Transformers on Small Datasets

Xiangyu Chen, Qinghao Hu, Kaidong Li +2

Vision Transformers has demonstrated competitive performance on computer vision tasks benefiting from their ability to capture long-range dependencies with multi-head self-attentio…

cs.CV2022

Robust Structured Declarative Classifiers for 3D Point Clouds: Defending Adversarial Attacks with Implicit Gradients

Kaidong Li, Ziming Zhang, Cuncong Zhong +1

Deep neural networks for 3D point cloud classification, such as PointNet, have been demonstrated to be vulnerable to adversarial attacks. Current adversarial defenders often learn…

cs.CV2022

Dilated Continuous Random Field for Semantic Segmentation

Xi Mo, Xiangyu Chen, Cuncong Zhong +3

Mean field approximation methodology has laid the foundation of modern Continuous Random Field (CRF) based solutions for the refinement of semantic segmentation. In this paper, we…

cs.CV2021

SGNet: A Super-class Guided Network for Image Classification and Object Detection

Kaidong Li, Nina Y. Wang, Yiju Yang +1

Most classification models treat different object classes in parallel and the misclassifications between any two classes are treated equally. In contrast, human beings can exploit…

cs.CV2021

Colonoscopy Polyp Detection and Classification: Dataset Creation and Comparative Evaluations

Kaidong Li, Mohammad I. Fathan, Krushi Patel +6

Colorectal cancer (CRC) is one of the most common types of cancer with a high mortality rate. Colonoscopy is the preferred procedure for CRC screening and has proven to be effectiv…

cs.CV2020

Why Layer-Wise Learning is Hard to Scale-up and a Possible Solution via Accelerated Downsampling

Wenchi Ma, Miao Yu, Kaidong Li +1

Layer-wise learning, as an alternative to global back-propagation, is easy to interpret, analyze, and it is memory efficient. Recent studies demonstrate that layer-wise learning ca…