Seminar

Event-based vision represents a paradigm shift in how vision information is captured and processed. By only responding to dynamic intensity changes in the scene, event-based sensing produces far less data than conventional frame-based cameras, promising to springboard a new generation of high-speed, low-power machines for edge intelligence. However, processing such dynamically sparse input originated from […]

Parallel imaging is widely used in clinical MRI to accelerate data acquisition or correct artifacts through the use of multiple receiving coils where each coil exhibits a unique spatial coil sensitivity map. Parallel reconstruction using null operations (PRUNO) is a k-space reconstruction method where a k-space nulling system is derived using null-subspace bases of the […]

Recent development of ultra-low-field (ULF) MRI presents opportunities for low-power, EMI shielding-free, and portable clinical applications of MRI. However, the imaging performance of these emerging ULF MRI scanners remains limited due to its three orders of magnitude weaker main magnetic field, resulting in the poor signal-to-noise ratio. Advancements in deep learning have opened new frontiers […]

In recent years, there has been an intensive development of portable ultralow-field magnetic resonance imaging (MRI) for low-cost, shielding-free, and point-of-care applications. However, its quality is poor and scan time is long. We propose a fast acquisition and deep learning reconstruction framework to accelerate brain MRI at 0.055 tesla. The acquisition consists of a single […]

Superconductors can potentially be used in electrical machines in future electric aircraft, since superconductors can increase the power density of electrical machines. When superconductors are carrying ac or are subject to an alternating magnetic field, they experience ac loss. AC loss affects the efficiency of the machines and the cooling power needed, which has implications […]

Federated learning (FL) inevitably confronts the challenge of system heterogeneity in practical scenarios. To enhance the capabilities of most model-homogeneous FL methods in handling system heterogeneity, we propose a training scheme that can extend their capabilities to cope with this challenge. In this seminar, we commence our study with a detailed exploration of homogeneous and […]

Existing methods for adapting Neural Radiance Fields (NeRFs) to scene changes require extensive data capture and model retraining, which is both time-consuming and labor-intensive. In this paper, we tackle the challenge of efficiently adapting NeRFs to real-world scene changes over time using a few new images while retaining the memory of unaltered areas, focusing on […]

Rapid advancements in 3D vision-language (3D-VL) tasks, such as 3D Visual Question Answering (3D-VQA) and 3D Visual Grounding (3D-VG), have opened up new avenues for human interaction with embodied agents or robots using natural language. Despite this progress, we find a notable limitation: existing 3D-VL models exhibit heightened sensitivity to language input, struggling to handle […]

Moire patterns, appearing as color distortions, severely degrade the image and video qualities when filming a screen with digital cameras. Considering the increasing demands for capturing videos, we study how to remove such undesirable moire patterns in videos, namely video demoireing. To this end, we introduce the first hand-held video demoireing dataset with a dedicated […]

Resting-state fMRI (rsfMRI) has emerged as the most valuable, non-invasive imaging technique to map long-range, brain-wide functional connectivity networks. Recently, dynamic rsfMRI network segregation and integration have been shown to facilitate and modulate diverse cognitive functions. Such dynamics are structural-functional hierarchically organized and have been observed across a range of temporal scales, spanning from days […]

Arrays, graphs, and point sets are fundamental data organization forms in mathematics, with significant applications in scientific computing and engineering problems like signal processing, molecular discovery, and 3D vision. However, the progress of digital circuitry, limited by Moore's Law, has slowed down, impeding the advancement of these problems. The increasing data and computational demands have […]

Morphological profiling in imaging microscopy can reveal biological cells characteristics. However, current image-based assay relays heavily on costly and extensive amount of fluorescent antibodies and is limited by the trade-off between the image resolution and scalability of the experiment. Therefore, here we presented a spinning arrayed optofluidic platform to achieve live cell, label free, large-scale […]

Quantitative phase and polarization microscope (QPPI) is a useful label-free microscopic tool in revealing the quantitative biophysical information of cells, such as cell shape, dry mass and their subcellular distribution. However, the current existing QPPI system could only offer a low imaging speed which is not sufficient to observe the dynamic activities of the live […]