27 citations · 30 across the 3 of their papers we have counts for
3 papers
cs.LG2019★ 1 cited
Learning Non-Parametric Invariances from Data with Permanent Random Connectomes
Dipan K. Pal, Akshay Chawla, Marios Savvides
One of the fundamental problems in supervised classification and in machine learning in general, is the modelling of non-parametric invariances that exist in data. Most prior art h…
cs.CV2017★ 27 cited
Improving Object Detection from Scratch via Gated Feature Reuse
Zhiqiang Shen, Honghui Shi, Jiahui Yu +7
In this paper, we present a simple and parameter-efficient drop-in module for one-stage object detectors like SSD when learning from scratch (i.e., without pre-trained models). We…
cs.CV2017★ 2 cited
Reformulating Level Sets as Deep Recurrent Neural Network Approach to Semantic Segmentation
Ngan Le, Kha Gia Quach, Khoa Luu +2
Variational Level Set (LS) has been a widely used method in medical segmentation. However, it is limited when dealing with multi-instance objects in the real world. In addition, it…