Related papers: Introducing SESHAT: A Tool for Object Classificati…
Astrometry is one of the main pillars of astronomy, and one of its oldest branches. Over the years, an increasing number of astrometric works by means of Hubble Space Telescope (HST) data have revolutionized our understanding of various…
Recent research works have proposed machine learning models for classifying IoT devices connected to a network. However, there is still a practical challenge of not having all devices (and hence their traffic) available during the training…
The James Webb Space Telescope (JWST) is predicted to make great advances in the field of exoplanet atmospheres. Its 25 m2 mirror means that it can reach unprecedented levels of precision in observations of transit spectra, and can thus…
The StarLight program conceptualizes fast interstellar travel via small wafer satellites (wafersats) that are propelled by directed energy. This process is wildly different from traditional space travel and trades large and slow spacecraft…
Real-world scenarios pose several challenges to deep learning based computer vision techniques despite their tremendous success in research. Deeper models provide better performance, but are challenging to deploy and knowledge distillation…
A number of transiting, potentially habitable Earth-sized exoplanets have recently been detected around several nearby M dwarf stars. These worlds represent important targets for atmospheric characterization for the upcoming NASA James Webb…
The Sloan Digital Sky Survey (SDSS) has created a knowledge gap between the Northern and the Southern hemispheres which is very marked for white dwarfs: only $\simeq 15$% of the known white dwarfs are south of the equator. Here we make use…
Incremental few-shot object detection aims at detecting novel classes without forgetting knowledge of the base classes with only a few labeled training data from the novel classes. Most related prior works are on incremental object…
The two-step galaxy morphology classification framework {\tt USmorph} successfully combines unsupervised machine learning (UML) with supervised machine learning (SML) methods. To enhance the UML step, we employed a dual-encoder architecture…
Characterizing the fundamental parameters of stars from observations is crucial for studying the stars themselves, their planets, and the galaxy as a whole. Stellar evolution theory predicting the properties of stars as a function of…
Our understanding of exoplanet demographics partly depends on their corresponding host star parameters. With the majority of exoplanet-host stars having only atmospheric constraints available, robust inference of their parameters is…
We present LiSTA (LiDAR Spatio-Temporal Analysis), a system to detect probabilistic object-level change over time using multi-mission SLAM. Many applications require such a system, including construction, robotic navigation, long-term…
We propose the use of the James Webb Space Telescope (JWST) in simultaneous observations with an Earth-based telescope for parallax measurements to tightly constrain the orbital trajectory of hazardous near-Earth objects (NEOs). We…
The James Webb Space Telescope (JWST), scheduled for launch in 2014, is expected to revolutionize our understanding of the high-redshift Universe. Even so, many of the most interesting sources that may be hiding at redshifts z~10…
Distributed machine learning is becoming a popular model-training method due to privacy, computational scalability, and bandwidth capacities. In this work, we explore scalable distributed-training versions of two algorithms commonly used in…
Wisps are among the most prominent scattered light artifacts in JWST/NIRCam imaging. They often appear in certain regions of the detectors and contaminate observations at surface-brightness levels relevant for faint-source photometry. We…
In this paper, we propose an original object detection methodology applied to Global Wheat Head Detection (GWHD) Dataset. We have been through two major architectures of object detection which are FasterRCNN and EfficientDet, in order to…
The expansion of satellite constellations poses a significant challenge to optical ground-based astronomical observations, as satellite trails degrade observational data and compromise research quality. Addressing these challenges requires…
Source counts -- the number density of sources as a function of flux density -- represent one of the fundamental metrics in observational cosmology due to their straightforward and simple nature. It is an important tool that provides…
Gen TSO is a noise calculator specifically tailored to simulate James Webb Space Telescope (JWST) time-series observations of exoplanets. Gen TSO enables the estimation of signal-to-noise ratios (S/N) for transit or eclipse depths through…