“…Depth of field and motion blur have also been used to generate realistic images. …”
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“…It is suggested that our proposed auditory feedback could blur the distinction between self and others, and that the operator attributes the subject of the motion of the manipulated object to himself.…”
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“…The MAF is compared with several current algorithms without reference and achieves a 95% and 96% accuracy for blur type and blur degree, respectively. The DFDA is compared with various texture and corner methods and achieves an accuracy, precision, and recall of up to 100%, and also performs well on attacked datasets with reduction and cut. …”
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“…This was accompanied by higher amounts of introduced astigmatic retinal image blur.…”
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“…Logistic regression on a Gabor Filter bank (GFB) modeling a population of V1 simple cells separates the categories with nearly 80% accuracy, and furthermore exhibits tuning to penumbral blur. A Filter-Rectify Filter (FRF) style neural network extending the GFB model performed at better than 80% accuracy, and exhibited blur tuning and greater sensitivity to texture differences. …”
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“…Atmospheric turbulence (AT) can change the path and direction of light during video capturing of a target in space due to the random motion of the turbulent medium, a phenomenon that is most noticeable when shooting videos at long ranges, resulting in severe video dynamic distortion and blur. To mitigate geometric distortion and reduce spatially and temporally varying blur, we propose a novel Atmospheric Turbulence Video Restoration Generative Adversarial Network (ATVR-GAN) with a specialized Recurrent Neural Network (RNN) generator, which is trained to predict the scene’s turbulent optical flow (OF) field and utilizes a recurrent structure to catch both spatial and temporal dependencies. …”
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“…Here, we show that observers require on average a massive difference of approximately 40% to detect a change in the number of objects that vary irrelevantly in blur, contrast and spatial separation, and that some naive observers require even more than this. …”
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“…This article elucidates the need to consider the inherent spatial transfer function (blur), of any thermographic instrument used to measure thermal fields. …”
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“…Consequently, the proposed model showed more than 1 dB superior performance compared with the existing noise-to-blur model.…”
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“…This study explores the sensitivity of the BRISQUE method to different types of image degradations, such as Gaussian noise and Gaussian blur. By evaluating the performance of the VGG16 model on these degraded datasets with varying levels of noise and blur, a correlation is established between image degradation and BRISQUE scores. …”
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“…However, extracting molecule-specific information from fluorescence images is often limited by the noise and blur intrinsic to the cell and the imaging system. …”
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“…We presented participants with audio–visual sentences in which the visual component was either blurred or not blurred. We found that there was a greater cost in recall performance for semantically meaningless speech in the audio–visual ‘blur’ compared to audio–visual ‘no blur’ condition and this effect was specific to the older group. …”
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“…The image reconstruction algorithm first removes the image blur using the modelled impulse response function and then corrects for geometrical distortions caused by the foil tilt. …”
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“…However, when the vehicle is moving, motion blur occurs in the LED images, making it difficult to detect the LEDs. …”
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“…LSFG can also measure the mean blur rate, which quantitatively calculates the blood flow. …”
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“…In recent years, substantial improvement has been made to solve various challenges of VOT techniques such as change of scale, occlusions, motion blur, and illumination variations. This paper proposes a tracking algorithm in a spatiotemporal context (STC) framework. …”
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“…RESULTS: The mean blur rate of the affected eye was significantly lower than that of the unaffected eye. …”
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“…However, large deformation, noise, and blur among EM images remain the task challenging. …”
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“…This paper presents an efficient underwater image enhancement method, named ECO-GAN, to address the challenges of color distortion, low contrast, and motion blur in underwater robot photography. The proposed method is built upon a preprocessing framework using a generative adversarial network. …”
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“…To increase the number of training data, the face images were propagated with augmentation image technique, in which ten augmentations were used such as Rotate, Flip, Gaussian Blur, Gamma Contrast, Sigmoid Contrast, Sharpen, Emboss, Histogram Equalization, Hue and Saturation, Average Blur so the face images became 240 face images per cluster. …”
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