activity
20192026
most citedHow Do Adam and Training Strategies Help BNNs Optimization?

26 citations · 109 across the 18 of their papers we have counts for

collaborators

17 papers

cs.RO2026

RAEM: Robust Autonomous Exploration for Multi-Floor Environments with a Quadruped Robot

Zikang Yuan, Yuan Ren, Yian Wang +10

In this paper, we propose RAEM, a robust autonomous exploration framework for quadruped robots operating in multi-floor environments. Most existing ground-robot exploration approac…

cs.CV2022

Graph Reasoning Transformer for Image Parsing

Dong Zhang, Jinhui Tang, Kwang-Ting Cheng

Capturing the long-range dependencies has empirically proven to be effective on a wide range of computer vision tasks. The progressive advances on this topic have been made through…

cs.CV202210 cited

FedMix: Mixed Supervised Federated Learning for Medical Image Segmentation

Jeffry Wicaksana, Zengqiang Yan, Dong Zhang +4

The purpose of federated learning is to enable multiple clients to jointly train a machine learning model without sharing data. However, the existing methods for training an image…

cs.CV2022

Stereo Neural Vernier Caliper

Shichao Li, Zechun Liu, Zhiqiang Shen +1

We propose a new object-centric framework for learning-based stereo 3D object detection. Previous studies build scene-centric representations that do not consider the significant v…

cs.AR2021

R2F: A Remote Retraining Framework for AIoT Processors with Computing Errors

Dawen Xu, Meng He, Cheng Liu +5

AIoT processors fabricated with newer technology nodes suffer rising soft errors due to the shrinking transistor sizes and lower power supply. Soft errors on the AIoT processors pa…

cs.AR20214 cited

Energy-Efficient Accelerator Design for Deformable Convolution Networks

Dawen Xu, Cheng Chu, Cheng Liu +4

Deformable convolution networks (DCNs) proposed to address the image recognition with geometric or photometric variations typically involve deformable convolution that convolves on…