Search Results for author: Rodney LaLonde

Found 8 papers, 5 papers with code

Deformable Capsules for Object Detection

no code implementations11 Apr 2021 Rodney LaLonde, Naji Khosravan, Ulas Bagci

In this study, we introduce a new family of capsule networks, deformable capsules (DeformCaps), to address a very important problem in computer vision: object detection.

object-detection Object Detection

Capsules for Biomedical Image Segmentation

no code implementations9 Apr 2020 Rodney LaLonde, Ziyue Xu, Ismail Irmakci, Sanjay Jain, Ulas Bagci

The proposed convolutional-deconvolutional capsule network, SegCaps, shows state-of-the-art results while using a fraction of the parameters of popular segmentation networks.

Computed Tomography (CT) Image Segmentation +1

Diagnosing Colorectal Polyps in the Wild with Capsule Networks

1 code implementation10 Jan 2020 Rodney LaLonde, Pujan Kandel, Concetto Spampinato, Michael B. Wallace, Ulas Bagci

In this study, we design a novel capsule network architecture (D-Caps) to improve the viability of optical biopsy of colorectal polyps.

Image Classification

Encoding Visual Attributes in Capsules for Explainable Medical Diagnoses

2 code implementations12 Sep 2019 Rodney LaLonde, Drew Torigian, Ulas Bagci

To the best of our knowledge, this is the first study to investigate capsule networks for making predictions based on radiologist-level interpretable attributes and its applications to medical image diagnosis.

Lung Cancer Diagnosis Multi-Task Learning

INN: Inflated Neural Networks for IPMN Diagnosis

1 code implementation30 Jun 2019 Rodney LaLonde, Irene Tanner, Katerina Nikiforaki, Georgios Z. Papadakis, Pujan Kandel, Candice W. Bolan, Michael B. Wallace, Ulas Bagci

This is one of the first studies to train an end-to-end deep network on multisequence MRI for IPMN diagnosis, and shows that our proposed novel inflated network architectures are able to handle the extremely limited training data (139 MRI scans), while providing an absolute improvement of $8. 76\%$ in accuracy for diagnosing IPMN over the current state-of-the-art.

Capsules for Object Segmentation

7 code implementations11 Apr 2018 Rodney LaLonde, Ulas Bagci

A new architecture recently introduced by Sabour et al., referred to as a capsule networks with dynamic routing, has shown great initial results for digit recognition and small image classification.

Semantic Segmentation

ClusterNet: Detecting Small Objects in Large Scenes by Exploiting Spatio-Temporal Information

no code implementations CVPR 2018 Rodney LaLonde, Dong Zhang, Mubarak Shah

To reduce the large search space, the first stage (ClusterNet) takes in a set of extremely large video frames, combines the motion and appearance information within the convolutional architecture, and proposes regions of objects of interest (ROOBI).

object-detection Object Detection

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