activity
20182021
most citedA Two-Stage Approach to Few-Shot Learning for Image Recognition

156 citations · 156 across the 3 of their papers we have counts for

collaborators

5 papers

cs.RO2021

Global-Position Tracking Control of 3-D Bipedal Walking via Virtual Constraint Design and Multiple Lyapunov Analysis

Yan Gu, Yuan Gao, Bin Yao +1

A safety-critical measure of legged locomotion performance is a robot's ability to track its desired time-varying position trajectory in an environment, which is herein termed as "…

cs.CV2020

Few-shot Image Recognition with Manifolds

Debasmit Das, J. H. Moon, C. S. George Lee

In this paper, we extend the traditional few-shot learning (FSL) problem to the situation when the source-domain data is not accessible but only high-level information in the form…

cs.LG2019156 cited

A Two-Stage Approach to Few-Shot Learning for Image Recognition

Debasmit Das, C. S. George Lee

This paper proposes a multi-layer neural network structure for few-shot image recognition of novel categories. The proposed multi-layer neural network architecture encodes transfer…

cs.CV2019

Zero-shot Image Recognition Using Relational Matching, Adaptation and Calibration

Debasmit Das, C. S. George Lee

Zero-shot learning (ZSL) for image classification focuses on recognizing novel categories that have no labeled data available for training. The learning is generally carried out wi…

cs.CV2018

Unsupervised Domain Adaptation using Regularized Hyper-graph Matching

Debasmit Das, C. S. George Lee

Domain adaptation (DA) addresses the real-world image classification problem of discrepancy between training (source) and testing (target) data distributions. We propose an unsuper…