Generative Adversarial Networks (GANs) have shown promise in augmenting datasets and boosting convolutional neural networks' (CNN) performance on image classification tasks.
Beyond unicellular and multicellular organisms, there is a third type of structural complexity in living animals: that of the mechanical self-assembly of groups of distinct multicellular organisms into dynamical, functional structures.
Existing Multi-Plane Image (MPI) based view-synthesis methods generate an MPI aligned with the input view using a fixed number of planes in one forward pass.
In scientific literature, XANES/Raman data are usually plotted in line graphs which is a visually appropriate way to represent the information when the end-user is a human reader.
The detection and tracking of objects in the scene are done on the distorted data at the host.
To avoid the ill-posedness, we investigate the effect of regularizing the phase retrieval algorithm with image priors for various overlap ratios between the neighboring diffraction patterns.
In this paper, we propose EveRestNet, a convolutional neural network designed to remove blocking artifacts in videostreams using events from neuromorphic sensors.
The adaptive sparse depth sampling network is jointly trained with a fusion network of an RGB image and sparse depth, to generate optimal adaptive sampling masks.
Due to recent improvements in image resolution and acquisition speed, materials microscopy is experiencing an explosion of published imaging data.
The utilization of computational photography becomes increasingly essential in the medical field.
We propose a two-stage framework to address the proposed compound figure separation problem.
We propose a self-supervised learning-based algorithm for LF video reconstruction from stereo video.
We first introduce an event-to-silhouette (E2S) neural network module to transform a stack of event frames to the corresponding silhouettes, with additional neural branches for camera pose regression.
Computed tomography is widely used to examine internal structures in a non-destructive manner.
The use of computed tomography (CT) imaging has become of increasing interest to academic areas outside of the field of medical imaging and industrial inspection, e. g., to biology and cultural heritage research.
The histograms are then variably sampled via Poisson Disk Sampling prioritized by the QT based segmentation map.
First, a subfigure label detector is built to extract the global layout information of the compound figure.
We introduce a system and methods for the three-dimensional measurement of extended specular surfaces with high surface normal variations.
Temporal Video Frame Synthesis (TVFS) aims at synthesizing novel frames at timestamps different from existing frames, which has wide applications in video codec, editing and analysis.
We propose a lens-free coded aperture camera system for human action recognition that is privacy-preserving.
We propose an XRF image inpainting approach to address the issue of long scanning time, thus speeding up the scanning process while still maintaining the possibility to reconstruct a high quality XRF image.
Compressive holography has been introduced as a method that allows 3D tomographic reconstruction at different depths from a single 2D image.
Recent advances in ptychography have demonstrated that one can image beyond the diffraction limit of the objective lens in a microscope.
Unfortunately, a detailed analysis of CI has proven to be a challenging problem because performance depends equally on three components: (1) the optical multiplexing, (2) the noise characteristics of the sensor, and (3) the reconstruction algorithm.