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To enhance the accuracy and robustness of PM$_{2.5}$ concentration forecasting, this paper introduces FALNet, a Frequency-Aware LSTM Network that integrates frequency-domain decomposition, temporal modeling, and attention-based refinement.…

The aim of this white paper is to discuss the observing strategies for the LSST Wide-Fast-Deep that would improve the study of blazars (emission variability, census, environment) and Fast Radio Bursts (FRBs). For blazars, these include the…

We present microsecond-resolution, coherently-dedispersed, polarimetric measurements of 35 fast radio bursts (FRBs) detected during the Commensal Real-time ASKAP Fast Transients (CRAFT) incoherent sum (ICS) survey with the Australian Square…

Since the discovery of RRATs, interest in single pulse radio searches has increased dramatically. Due to the large data volumes generated by these searches, especially in planned surveys for future radio telescopes, such searches have to be…

Currently, many face forgery detection methods aggregate spatial and frequency features to enhance the generalization ability and gain promising performance under the cross-dataset scenario. However, these methods only leverage one level…

Magnetic resonance imaging (MRI) is an important non-invasive clinical tool that can produce high-resolution and reproducible images. However, a long scanning time is required for high-quality MR images, which leads to exhaustion and…

Fast Radio Bursts (FRBs) are a promising tool for studying the low-density universe as their dispersion measures (DM) are extremely sensitive probes of electron column density. Active Galactic Nuclei (AGN) inject energy into the…

Fast radio bursts (FRBs) are brief flashes of emission detectable to cosmological distances. Cosmology applications rely on an understanding of how the detected sample relates to the underlying population. To this end we examine the…

Radio interferometers composed of a large array of small antennas posses large fields of view, coupled with high sensitivities. For example, the Karoo Array Telescope (MeerKAT), achieves a gain of up to 2.8 K/Jy across its…

The search for free-floating planets (FFPs) is a key science driver for upcoming microlensing surveys like the Nancy Grace Roman Galactic Exoplanet Survey. These rogue worlds are typically detected via short-duration microlensing events,…

Deep learning-based computer-aided diagnosis has achieved unprecedented performance in breast cancer detection. However, most approaches are computationally intensive, which impedes their broader dissemination in real-world applications. In…

We investigate the S/N of a new incoherent dedispersion algorithm optimized for FPGA-based architectures intended for deployment on ASKAP and other SKA precursors for fast transients surveys. Unlike conventional CPU- and GPU-optimized…

Punctuation and word casing prediction are necessary for automatic speech recognition (ASR). With the popularity of on-device end-to-end streaming ASR systems, the on-device punctuation and word casing prediction become a necessity while we…

Fast blue optical transients (FBOTs) are luminous, rapidly evolving events with blue spectra, possibly powered by newborn magnetars and linked to fast radio bursts (FRBs). Given this potential connection, we conducted deep radio…

We present the first results from a new backend on the Australian Square Kilometre Array Pathfinder, the Commensal Realtime ASKAP Fast Transient COherent (CRACO) upgrade. CRACO records millisecond time resolution visibility data, and…

Fast radio bursts (FRBs) provide a sensitive probe of ionized baryons through their dispersion measure (DM). In addition to slowly evolving cosmological terms, at least two repeaters now show clear secular DM-decrease episodes:…

Image deblurring plays a crucial role in enhancing visual clarity across various applications. Although most deep learning approaches primarily focus on sRGB images, which inherently lose critical information during the image signal…

This research addresses the challenge of developing a universal deepfake detector that can effectively identify unseen deepfake images despite limited training data. Existing frequency-based paradigms have relied on frequency-level…

Efficient anomaly detection and diagnosis in multivariate time-series data is of great importance for modern industrial applications. However, building a system that is able to quickly and accurately pinpoint anomalous observations is a…

Fast radio transient search algorithms identify signals of interest by iterating and applying a threshold on a set of matched filters. These filters are defined by properties of the transient such as time and dispersion. A real transient…