anti-noise
This dataset consists of images with two types of artificially added noise, intended for evaluating the robustness of machine learning models against noise perturbations. The first type of noise introduces randomly generated pixel values ranging from 0 to 255 at random positions in the image. The second type of noise adds binary noise by setting pixels at random locations to either 0 or 255. The dataset includes images with varying amounts of noisy pixels, allowing for detailed analysis under different noise intensities.
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The dataset contains thousands of signal frames from 60 ZigBee devices. The devices and USRP N210 were placed on two movable cabinets on wheels with a maximum distance of 3 meters between them. Due to distance constraints, a coaxial attenuator with an attenuation of 60 dB was fitted at the receiver in order to obtain signals at low SNR. The SNR of the received signal is changed by adjusting the distance between the two cabinets, which can be reduced to about 0 dB when the distance is about 3 metres.
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