All networks were implemented using Python 3.6.9 with Tensorflow 1.14 and Keras 2.3.1. Training and testing was conducted on an Alienware X51 r3 PC running Ubuntu 18.04 LTE, implementing an Intel® Core™ i7-6700 (8 MB Cache, 4.0 GHz) CPU with 32 GB (2133 MHz) DDR4 RAM and a NVIDIA GeForce GTX 1060 GPU with 6 GB memory.

All networks utilized the Adam optimization algorithm to iteratively update network weights. Additionally, all networks used image augmentation to increase the robustness of the training datasets. Augmentation methods included random horizontal and vertical flipping, rotations of 90 or 270 degrees and scaling by values between 0.5 and 1.5. Non-linear transforms such as stretching, skewing or sheering were not used.

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