most citedFeature Selection Using Reinforcement Learning

9 citations · 17 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CV2021

Graph Convolution Neural Network For Weakly Supervised Abnormality Localization In Long Capsule Endoscopy Videos

Sodiq Adewole, Philip Fernandes, James Jablonski +4

Temporal activity localization in long videos is an important problem. The cost of obtaining frame level label for long Wireless Capsule Endoscopy (WCE) videos is prohibitive. In t…

cs.CV20211 cited

Unsupervised Shot Boundary Detection for Temporal Segmentation of Long Capsule Endoscopy Videos

Sodiq Adewole, Philip Fernandes, James Jablonski +4

Physicians use Capsule Endoscopy (CE) as a non-invasive and non-surgical procedure to examine the entire gastrointestinal (GI) tract for diseases and abnormalities. A single CE exa…

cs.LG20219 cited

Feature Selection Using Reinforcement Learning

Sali Rasoul, Sodiq Adewole, Alphonse Akakpo

With the decreasing cost of data collection, the space of variables or features that can be used to characterize a particular predictor of interest continues to grow exponentially.…

cs.CV20217 cited

Lesion2Vec: Deep Metric Learning for Few-Shot Multiple Lesions Recognition in Wireless Capsule Endoscopy Video

Sodiq Adewole, Philip Fernandez, Michelle Yeghyayan +5

Effective and rapid detection of lesions in the Gastrointestinal tract is critical to gastroenterologist's response to some life-threatening diseases. Wireless Capsule Endoscopy (W…

eess.IV2020

Hierarchical Deep Convolutional Neural Networks for Multi-category Diagnosis of Gastrointestinal Disorders on Histopathological Images

Rasoul Sali, Sodiq Adewole, Lubaina Ehsan +8

Deep convolutional neural networks(CNNs) have been successful for a wide range of computer vision tasks, including image classification. A specific area of the application lies in…