To our knowledge, this study is the first to apply deep learning models that can, beyond diagnosis, identify molecular subtypes and predict outcomes in a single brain tumour entity (meningioma) using ...
Abstract: In recent years, the need for the efficient deployment of Neural Networks (NN) on edge devices has been steadily increasing. However, the high computational demand required for Machine ...
Abstract: Deep neural networks (DNNs) are widely used for image recognition, speech recognition, pattern analysis, and intrusion detection. Recently, the adversarial example attack, in which the input ...
Artificial Intelligence (AI) is rapidly taking over industries. The fear of job displacements is palpable; however, as companies around the world are scrambling to automate various processes, ...
This contains examples, scripts and code related to image classification using TensorFlow models (from here) converted to TensorRT. Converting TensorFlow models to TensorRT offers significant ...
The tuning of a pre-trained model is a crucial application for transfer learning in machine learning. It is a process of learning to re-adjust initially pre-trained models, with some big datasets, to ...
Machine learning is a complex discipline but implementing machine learning models is far less daunting than it used to be. Machine learning frameworks like Google’s TensorFlow ease the process of ...
This is an example application for TensorFlow Lite on Android. It uses video classification to continuously classify whatever it sees from the device's back camera. Inference is performed using the ...
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