The learned perceptual image patch similarity in both channels is below 0.008. These experiments thoroughly demonstrate that the proposed semantic communication is a superior deep learning-based joint source-channel coding method, offering a high CR and low distortion of reconstructed images....
Fig. 2: Neural generative coding computation and circuitry. a The two key computation steps taken by an entire NGC network (a GNCN-t2-LΣ) when processing an input (z0 = x): (1) prediction and laterally-weighted error computation, (2) error-correction of neural states. In this dia...
Extending Neural P-frame Codecs for B-frame Coding Reza Pourreza and Taco Cohen | ICCV, 2021 Wireless and RF Neural Augmentation of Kalman Filter with Hypernetwork for Channel Tracking Kumar Pratik, Rana Ali Amjad, et al. | Globecom, 2021 Personalization and On-Device Learning Federated Lea...
However, it is closed-source and does not support the generation of multimodal interleaved sequences. To address this gap, we present MIO, which is trained on a mixture of discrete tokens across four modalities using causal multimodal modeling. MIO undergoes a four-stage training process: (1) ...
Recent advances in deep learning techniques have led to improved diagnostic abilities in ophthalmology. A generative adversarial network (GAN), which consists of two competing types of deep neural networks, including a generator and a discriminator, has
The scattering of tiny particles in the atmosphere causes a haze effect on remote sensing images captured by satellites and similar devices, significantly disrupting subsequent image recognition and classification. A generative adversarial network named
channel pairs is significantly higher than the absolute coherence between the input-output pairs, especially in the lower frequency range. This can be expected since the coherence between the output channel pairs is not explicitly minimized during training. This indicates that joint optimization of the...
The scattering of tiny particles in the atmosphere causes a haze effect on remote sensing images captured by satellites and similar devices, significantly disrupting subsequent image recognition and classification. A generative adversarial network named
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To understand how an autoregressive model is used to model a process, consider a random process {Xi} that consists of real-valued random samples Xi, with a time index i∈Z. The joint distribution of a finite sequence, p(xi, . . . , xi−N), can be expressed as a product of condi...