Related papers: Current and Future Developments in Deep, Wide--fie…

Radio observations with Very Long Baseline Interferometry (VLBI) provide the highest resolution in astronomy. Combining earth-bound with space-based telescopes and advancing the observations to mm-wavelengths increases the resolution even…

The internet has been used for data transfer in radio astronomy ever since its inception; however it is only recently that network bandwidth capability means that the internet becomes competitive with traditional forms of data storage. Very…

In this review we present the current state-of-the-art on complex Langevin simulations and their implications for the QCD phase diagram. After a short summary of the complex Langevin method, we present and discuss recent developments. Here…

Very-long-baseline interferometry (VLBI) is a challenging observational technique, which requires in-depth knowledge about radio telescope instrumentation, interferometry, and the handling of noisy data. The reduction of the raw data is…

Vision-based prediction algorithms have a wide range of applications including autonomous driving, surveillance, human-robot interaction, weather prediction. The objective of this paper is to provide an overview of the field in the past…

In recent years, significant advances in computer vision have also propelled progress in remote sensing. Concurrently, the use of drones has expanded, with many organizations incorporating them into their operations. Most drones are…

In recent years, we have witnessed significant progress in emerging deep learning models, particularly Large Language Models (LLMs) and Vision-Language Models (VLMs). These models have demonstrated promising results, indicating a new era of…

The use of deep learning techniques has exploded during the last few years, resulting in a direct contribution to the field of artificial intelligence. This work aims to be a review of the state-of-the-art in scene recognition with deep…

New functionality to process Very Long Baseline Interferometry (VLBI) data has been implemented in the CASA package. This includes two new tasks to handle fringe fitting and VLBI-specific amplitude calibration steps. Existing tasks have…

Estimating depth from single RGB images and videos is of widespread interest due to its applications in many areas, including autonomous driving, 3D reconstruction, digital entertainment, and robotics. More than 500 deep learning-based…

Visual odometry (VO) is a prevalent way to deal with the relative localization problem, which is becoming increasingly mature and accurate, but it tends to be fragile under challenging environments. Comparing with classical geometry-based…

The signal processing community is currently witnessing a growing interest in near-field signal processing, driven by the trend towards the use of large aperture arrays with high spatial resolution in the fields of communication,…

Tracking the origin of the accelerating expansion of the Universe remains one of the most challenging research activities today. The final answer will depend on the precision and on the consistency of future data. The sensitivity of future…

We report on a recent 90 cm wide-field VLBI survey of two 3.1 deg^2 fields using the VLBA, Westerbork and Jodrell Bank telescopes. In-beam calibration was used to calibrate each field, the process was simplified by imaging the calibrators…

I review the development of UV and EUV astronomy, covering the spectral range from 5 to 300 nm, with emphasis on sky surveys for discrete sources. I discuss studies which resulted in lists of sources observed by imaging and deliberately…

The East Asian VLBI Network (EAVN) is an international VLBI facility in East Asia and is operated under mutual collaboration between East Asian countries, as well as part of Southeast Asian and European countries. EAVN currently consists of…

I review the present status of the mapping of the large-scale structure of the Universe through wide-angle redshift surveys. In the first part of the paper, I discuss the current state of the art, describing in some detail the recently…

Visual Question Answering (VQA) is an evolving research field aimed at enabling machines to answer questions about visual content by integrating image and language processing techniques such as feature extraction, object detection, text…

We present the current status of cosmic shear studies and their implications on cosmological models. Theoretical expectations and observational results are discussed in the framework of standard cosmology and CDM scenarios. The potentials…

Multi-label learning is a rapidly growing research area that aims to predict multiple labels from a single input data point. In the era of big data, tasks involving multi-label classification (MLC) or ranking present significant and…