相关论文: Fireball streak detection with minimal CPU process…

Detection and localization of fire in images and videos are important in tackling fire incidents. Although semantic segmentation methods can be used to indicate the location of pixels with fire in the images, their predictions are…

We have created a new image analysis pipeline to reprocess images taken by the Near Earth Asteroid Tracking survey and have applied it to ten nights of observations. This work is the first large-scale reprocessing of images from an asteroid…

With upcoming (continuum) surveys of high-resolution radio telescopes, detection rates of fast radio bursts (FRBs) might approach $10^5$ per sky per day by future extremely large observatories, such as the possible extension of the Square…

Digital tracking detects faint solar system bodies by stacking many images along hypothesized orbits, revealing objects that are undetectable in every individual exposure. Previous searches have been restricted to small areas and short time…

We propose firefly neural architecture descent, a general framework for progressively and dynamically growing neural networks to jointly optimize the networks' parameters and architectures. Our method works in a steepest descent fashion,…

Deep Neural Networks (DNNs) have demonstrated remarkable success across a wide range of tasks, particularly in fields such as image classification. However, DNNs are highly susceptible to adversarial attacks, where subtle perturbations are…

Feature pyramids are widely exploited in many detectors to solve the scale variation problem for object detection. In this paper, we first investigate the Feature Pyramid Network (FPN) architectures and briefly categorize them into three…

The paper describes a deep network based object detector specialized for ball detection in long shot videos. Due to its fully convolutional design, the method operates on images of any size and produces \emph{ball confidence map} encoding…

Diffusion models are known for generating high-quality images, causing serious security concerns. To combat this, most efforts rely on deep neural networks (e.g., CNNs and Transformers), while largely overlooking the potential of…

Most of the classical approaches to straight line detection only deal with a binary edge image and need to use 2D interpolation operation. This paper proposes a new transform method figuratively named as funnel transform which can…

We present our 500 pc distance-limited study of stellar fares using the Dark Energy Camera as part of the Deeper, Wider, Faster Program. The data was collected via continuous 20-second cadence g band imaging and we identify 19,914 sources…

We introduce a novel technique to mitigate the adverse effects of atmospheric turbulence on astronomical imaging. Utilizing a video-to-image neural network trained on simulated data, our method processes a sliding sequence of short-exposure…

3D object localisation based on a sequence of camera measurements is essential for safety-critical surveillance tasks, such as drone-based wildfire monitoring. Localisation of objects detected with a camera can typically be solved with…

In nuclear physics experiments involving in-flight fragmentation of ions, usually a large number of different nuclei is produced and various detection systems are employed to identify the species event by event, e.g. by measuring their…

Although the remarkable performance of deep neural networks (DNNs) in image classification, their vulnerability to adversarial attacks remains a critical challenge. Most existing detection methods rely on complex and poorly interpretable…

Deblurring can not only provide visually more pleasant pictures and make photography more convenient, but also can improve the performance of objection detection as well as tracking. However, removing dynamic scene blur from images is a…

Solar storms can have a major impact on the infrastructure of the earth. Some of the causing events are observable from ground in the H{\alpha} spectral line. In this paper we propose a new method for the simultaneous detection of flares…

This paper introduces a method based on a deep neural network (DNN) that is perfectly capable of processing radar data from extremely thinned radar apertures. The proposed DNN processing can provide both aliasing-free radar imaging and…

Recently, spiking neural networks (SNNs) have demonstrated substantial potential in computer vision tasks. In this paper, we present an Efficient Spiking Deraining Network, called ESDNet. Our work is motivated by the observation that rain…

As of today, there is no official definition of a meteor cluster. It is usually identified as a large number of meteors sharing a similar radiant and velocity, all occurring within a few seconds. Only eight clusters have been reported so…