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- - 0.925 - - [61] Kaggle PSNA - 0.755 - - - - - 0.793 0.758 [45] DarkCovidNet 0.981 94.17 99.61 90.65 - - - - 0.979 [13] GoogleNet (for normal class) - - 91.00 91.00 - - 0.964 - - [4] DecafCNN [78] - - 78.00 84.00 - - 87.00 - - [35] Ensemble DCNN - - - - - - 0.99 - - [31] ResNet101 0.989 98.15 98.66 98.93 - - - - 0.964
Ref. Dataset Hardware and software platform used Input image size Time required for training
[47] CheXpert NVIDIA Geforce RTX 2080 Ti with 11GB memory. Python with Keras and TensorFlow 224 × 224 pixels -
[51] Lung ultrasonography videos from Italy RTX-2080 NVIDIA GPU 1,005 frames 11 hours
[46] NIH Tuberculosis Chest X-ray dataset [18] and Belarus Tuberculosis Portal dataset [21] Nvidia GeForce GTX 1050 Ti 512 × 512 5–6 ms
[26] ChestX-ray14 dataset 8-core CPU and four TITAN V GPUs Pytorch 1.0 framework in Python 3.6 on an Ubuntu 16.04 server 224 × 224 -
[20] ChestX-ray14 dataset NVIDIA TITAN Xp GPUs Pytorch 224 × 224 6 hours
[70] ChestX-ray14 dataset Dev-Box linux server with 4 Titan X GPUs 224 × 224 -
[5] ChestX-ray14 dataset Intel Core(TM) i7-6850k CPU 3.60GHz processor, 4TB of hard disk space, 7889 MB of RAM, and a CUDA-enabled NVidia Titan 11 GB graphics processing unit with python and Keras library on TensorFlow 224 × 224 -
[49] ChestX-ray8 NVIDIA GeForce GTX TITAN and PyTorch 512 × 512 20 hours
[46] NIH Tuberculosis Chest X-ray [18], Belarus Tuberculosis [A6] Nvidia GeForce GTX 1050 Ti 512 × 512 1 hour
[61] Kaggle PSNA Nvidia Tesla V100 and Nvidia K80 and Keras library of Python 512 × 512 7 hours
[13] St. Michael’s Hospital chest x-ray 3 NVIDIA Titan X 12GB GPUs 256 × 256 1 hour
[35] NIH Tuberculosis Chest X-ray [18], Belarus Tuberculosis [A6] Intel i5

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