PMC:7796058 / 61891-63261 JSONTXT 2 Projects

Annnotations TAB TSV DIC JSON TextAE

Id Subject Object Predicate Lexical cue
T456 0-147 Sentence denotes Evaluating precision, recall, and F-Score of video-Based and audio-Based risky behavior detection are listed in in Table 5 and Table 7 accordingly.
T457 148-440 Sentence denotes Table 8 includes time performance of different developed functionalities (e.g., video-based person density, video-based physical distancing, video-based risky behavior detection, and audio-based risky behavior detection) on various platforms such as Jetson NX, laptop, and android smartphone.
T458 441-546 Sentence denotes The performance of using a deep learning engine is highly dependent on Graphics and Computing processors.
T459 547-658 Sentence denotes Therefore, the performance of those functionalities is evaluated on a laptop with more robust processing units.
T460 659-746 Sentence denotes The laptop has NVIDIA GeForce RTX 2070 with 7.5 computation capabilities and a Core i7.
T461 747-815 Sentence denotes Therefore, the performance on Jetson NX is lower than on the laptop.
T462 816-937 Sentence denotes The best performance values are video-based risky behavior detection because they only involve the object detection task.
T463 938-1060 Sentence denotes Audio-based risky behavior detection segments the voice in specific time frames and converts them into spectrogram images.
T464 1061-1119 Sentence denotes Voice patterns are detected in images using the VGG model.
T465 1120-1202 Sentence denotes Therefore, the time of processing for audio is higher than video object detection.
T466 1203-1370 Sentence denotes Video-based people density and video-based physical distancing give worse performance values than simple object detection regarding complexities in tracking functions.