Peter Moss Acute Myeloid & Lymphoblastic Leukaemia AI Research Project's repositories
all-classifiers-2019
A collection of computer vision projects for Acute Lymphoblastic Leukemia classification/early detection.
all-arduino-nano-33-ble-sense-classifier
The ALL Arduino Nano 33 BLE Sense Classifier is an experiment to explore how low powered microcontrollers, specifically the Arduino Nano 33 BLE Sense, can be used to detect Acute Lymphoblastic Leukemia.
all-detection-system-2019
Intel DevMesh AI Spotlight Award winner. Acute Lymphoblastic Leukemia Detection System 2019 uses Tensorflow 1.4.1 & Neural Compute Stick 1 to provide an intelligent network and diagnosis system. Project by Adam Milton-Barker.
AML-ALL-Research-Archive
A repository dedicated to sharing the AML/ALL related public information, papers, code and datasets that we come across through R&D.
ALL-Detection-System-For-Oculus-Rift
Acute Lymphoblastic Leukemia Detection System 2020 uses Tensorflow 2 & Oculus Rift to provide a virtual detection system. Project by Adam Milton-Barker.
all-jetson-nano-classifier
An Acute Lymphoblastic Leukemia classifier developed for the NVIDIA Jetson Nano. Jetson AI Certification project by Adam Milton-Barker.
all-oneapi-classifier-2020
An Acute Lymphoblastic Leukemia classifier trained using Intel Distribution for Python and Intel Optimized Tensorflow (Tensorflow 2.1), and using OpenVINO to deploy the model on UP2 & Raspberry Pi.
ALL-Tensorflow-Classifier-2020
An Acute Lymphoblastic Leukemia CNN based on the proposed architecture in the Acute Leukemia Classification Using Convolution Neural Network In Clinical Decision Support System paper, using the Acute Lymphoblastic Leukemia Image Database for Image Processing dataset. Project by Adam Milton-Barker.
all-fastai-2019
A series of Acute Lymphoblastic Leukemia CNNs programmed in Python using FastAI. Project by team member Salvatore Raieli.
all-fastai-2020
A series of Acute Lymphoblastic Leukemia CNNs programmed in Python using FastAI. Project by team member Salvatore Raieli.
all-detection-system-for-magic-leap-1
Acute Lymphoblastic Leukemia Detection System 2020 uses Tensorflow 2 & Magic Leap to provide a mixed reality detection system. Project by Adam Milton-Barker.
contributing-guide
The contributing guide provides instructions on how to contribute to the Peter Moss Acute Myeloid and Lymphoblastic Leukemia AI Research Project.
all-agx-xavier-classifier
An Acute Lymphoblastic Leukemia classifier developed for the NVIDIA AGX Xavier using Intel® oneAPI AI Analytics Toolkit, Intel® Optimization for Tensorflow*, and TensorRT.