Abstract: Medical image segmentation is an important step in medical image analysis. With the rapid development of a convolutional neural network in image processing, deep learning has been used for ...

We present a generic image-to-image translation framework, pixel2style2pixel (pSp). Our pSp framework is based on a novel encoder network that directly generates a series of style vectors which are ...

Abstract: Current methods for remote sensing image dehazing confront noteworthy computational intricacies and yield suboptimal dehazed outputs, thereby circumscribing their pragmatic applicability. To ...

Abstract: To address the shortcomings of existing knowledge extraction techniques in semantic fusion, variable-length processing, and long tail discrimination, this paper proposes a method of sentence ...

Abstract: In this work, we propose a Wavelet-based Deep Auto Encoder-Decoder Network (WDAED) based image compression which takes care of the various frequency components present in an image.

Abstract: The thermometer code-to-binary code encoder has become the bottleneck of ultra-high speed flash ADCs. In this paper, the authors present the fat tree thermometer code-to-binary code encoder ...

Abstract: Existing learning-based arbitrary-scale point cloud upsampling methods are usually challenged with limited point cloud feature representation and noise-sensitive refinement of coarse point ...

Abstract: Light detection and ranging (LiDAR) point cloud denoising is critical for reliable environmental perception in autonomous driving and robotics. To overcome the lack of real-noise datasets ...

Abstract: We present an algorithm for registration between a large-scale point cloud and a close-proximity scanned point cloud, providing a localization solution that is fully independent of prior ...