… denoising method called FlashLight CNN (FLCNN) that implements a deep neural network
for image denoising. … networks alone for denoising grayscale images corrupted by additive …

… , have managed to attain excellent denoising results [72],[11]. In this thesis, a new method
for image denoising based on deep neural networks called FlashLight CNN is proposed. It is …

… Our denoising framework takes a flash/no-flash image pair (IF and IN ) as input and outputs
a denoised no-flash image … We exploit a convolutional neural network that infers two types of …

… problem of image denoising, they proposed FlashLight CNN, a … Set12, whereas a flashLight
CNN with 1361649 parameters takes … , the efficiency of Flashlight CNN plateaus. It might be …

… In the case of the flashlight CNN, it uses a very similar strategy, while also using inception
… Although these functions have been used in various studies for image denoising, the results …

… FlashLight CNN demonstrates the state of the art in quantitative and visual comparison with
current image de… , a lot of methods have been designed in order denoise the CT images [15]. …

… denoising neural network called FlashLight CNN. A complex-valued deep convolutional neural
network … [24], and it effectively improved the denoising performance of the network. Guan …

… denoising method called FlashLight CNN (FLCNN) that implements a deep neural network
for image denoising. … networks alone for denoising grayscale images corrupted by additive …

… Warmup and boost are the two phases that make up the FlashLight CNN, … CNN heads to
efficiently reduce noise. The MHCNN has achieved real image denoising and AWGN denoising …

… The other network considered in this chapter is called FlashLight CNN (FLCNN). It is far
more complex to analyze comparing to DnCNN. FLCNN was proposed and studied in thesis …