Dermatology:
deep neural networks identify skin cancer / suspicious lesions.
Not exact matches
To
identify the characteristics that are most helpful in screening for cancer, the team created hand - crafted pyramid features (basic components of recognition systems)-- as well as investigated the performance of a common
deep learning framework known as convolutional
neural networks (CNN) for cervical disease classification.
Predictive accuracies ranging from 89.4 % to as high as 99.1 % show that trained
deep learning
neural networks (DNNs) can
identify weather fronts, tropical cyclones, and long narrow air flows that transport water vapor from the tropics called atmospheric rivers.
The «
Deep Neural Networks» used in the system will
identify specific objects in...