| Id |
Subject |
Object |
Predicate |
Lexical cue |
| T246 |
0-151 |
Sentence |
denotes |
The CNNCF is a modular framework consisting of two stages that were trained with different optimization goals and controlled by the control gate block. |
| T247 |
152-329 |
Sentence |
denotes |
Each stage consisted of multiple residual blocks (ResBlock-A and ResBlock-B) that retained the features in the different layers, thereby preventing the degradation of the model. |
| T248 |
330-437 |
Sentence |
denotes |
The design of the control gate block was inspired by the synaptic frontend structure in the nervous system. |
| T249 |
438-546 |
Sentence |
denotes |
We calculated the score of the optimization target, and a score above a predefined threshold was acceptable. |
| T250 |
547-690 |
Sentence |
denotes |
If the times of the neurotransmitter were above another predefined threshold, the control gate was opened to let the features information pass. |
| T251 |
691-742 |
Sentence |
denotes |
The framework was trained in a step-by-step manner. |
| T252 |
743-952 |
Sentence |
denotes |
Training occurred at each stage for a specified goal, and the second stage used the features extracted by the first stage, thereby reusing the features and increasing the convergence speed of the second stage. |
| T253 |
953-1070 |
Sentence |
denotes |
The CNNCF exhibited excellent performance for identifying the COVID-19 cases automatically in the X-data and CT-data. |
| T254 |
1071-1258 |
Sentence |
denotes |
Unlike traditional machine learning methods, the CNNCF was trained in an end-to-end manner, which ensured the flexibility of the framework for different data sets without much adjustment. |
