A Preliminary Exploration into an Alternative CellLineNet: An Evolutionary Approach

no code implementations • 26 Jul 2020 • Akwarandu Ugo Nwachuku, Xavier Lewis-Palmer, Darlington Ahiale Akogo

Within this paper, the exploration of an evolutionary approach to an alternative CellLineNet: a convolutional neural network adept at the classification of epithelial breast cancer cell lines, is presented.

Classification General Classification

CellLineNet: End-to-End Learning and Transfer Learning For Multiclass Epithelial Breast cell Line Classification via a Convolutional Neural Network

no code implementations • 18 Aug 2018 • Darlington Ahiale Akogo, Vincent Appiah, Xavier-Lewis Palmer

CellLineNet is 31-layer Convolutional Neural Network trained, validated and tested on a 3, 252 image dataset of 5 types of Epithelial Breast cell Lines (MDA-MB-468, MCF7, 10A, 12A and HC11) in an end-to-end fashion.

Classification General Classification +1

End-to-End Learning via a Convolutional Neural Network for Cancer Cell Line Classification

no code implementations • 25 Jul 2018 • Darlington Ahiale Akogo, Xavier-Lewis Palmer

Computer Vision for automated analysis of cells and tissues usually include extracting features from images before analyzing such features via various Machine Learning and Machine Vision algorithms.

General Classification

ScaffoldNet: Detecting and Classifying Biomedical Polymer-Based Scaffolds via a Convolutional Neural Network

no code implementations • 17 May 2018 • Darlington Ahiale Akogo, Xavier-Lewis Palmer

We developed a Convolutional Neural Network model to identify and classify Airbrushed (alternatively known as Blow-spun), Electrospun and Steel Wire scaffolds.

BIG-bench Machine Learning