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We propose a new convolutional neural network (CNN) which performs coarse and fine segmentation for end-to-end synthetic aperture radar (SAR) automatic target recognition (ATR) system. In recent years, many CNNs for SAR ATR using deep…

Time domain radio astronomy observing campaigns frequently generate large volumes of data. Our goal is to develop automated methods that can identify events of interest buried within the larger data stream. The V-FASTR fast transient system…

The observation of the transient sky through a multitude of astrophysical messengers hasled to several scientific breakthroughs these last two decades thanks to the fast evolution ofthe observational techniques and strategies employed by…

The classification of variable objects provides insight into a wide variety of astrophysics ranging from stellar interiors to galactic nuclei. The Zwicky Transient Facility (ZTF) provides time series observations that record the variability…

Scene Text Recognition (STR), the task of recognizing text against complex image backgrounds, is an active area of research. Current state-of-the-art (SOTA) methods still struggle to recognize text written in arbitrary shapes. In this…

With the upcoming Vera C.~Rubin Observatory Legacy Survey of Space and Time (LSST), it is expected that only $\sim 0.1\%$ of all transients will be classified spectroscopically. To conduct studies of rare transients, such as Type I…

While microlensing is very rare, occurring on average once per million stars observed, current and near-future surveys are coming online with the capability of providing photometry of almost the entire visible sky to depths up to R ~ 22 mag…

Optical Character Recognition (OCR) systems have been widely used in various applications for extracting semantic information from images. To give the user more control over their privacy, an on-device solution is needed. The current…

We describe the Wise Observatory Optical Transient Search (WOOTS), a survey for supernovae (SNe) and other variable and transient objects in the fields of redshift 0.06-0.2 Abell galaxy clusters. We present the survey design and…

We propose a framework for top-down salient object detection that incorporates a tightly coupled image classification module. The classifier is trained on novel category-aware sparse codes computed on object dictionaries used for saliency…

With the upcoming commensal surveys for Fast Radio Bursts (FRBs), and their high candidate rate, usage of machine learning algorithms for candidate classification is a necessity. Such algorithms will also play a pivotal role in sending…

Upcoming next-generation sky surveys will detect large number of faint objects with magnitudes larger than 25. When objects are crowded within a limited a field of view, blending becomes unavoidable. Blending leads to the omission of many…

Speculative Decoding (SD) is a recently proposed technique for faster inference using Large Language Models (LLMs). SD operates by using a smaller draft LLM for autoregressively generating a sequence of tokens and a larger target LLM for…

Microlensing has a unique advantage for detecting dark objects in the Milky Way, such as free-floating planets, neutron stars, and stellar-mass black holes. Most microlensing surveys focus on the Galactic bulge, where higher stellar density…

We introduce a transformer-based neural network for the accurate classification of real and bogus transient detections in astronomical images. This network advances beyond the conventional convolutional neural network (CNN) methods, widely…

Context. Transient astronomical events that exhibit no discernible association with a host galaxy are commonly referred to as hostless. These rare phenomena are associated with extremely energetic events, and they can offer unique insights…

Astronomical transients are stellar objects that become temporarily brighter on various timescales and have led to some of the most significant discoveries in cosmology and astronomy. Some of these transients are the explosive deaths of…

Vast amounts of astronomical photometric data are generated from various projects, requiring significant effort to identify variable stars and other object classes. In light of this, a general, widely applicable classification framework…

This paper introduces an algorithm for the detection of change-points and the identification of the corresponding subsequences in transient multivariate time-series data (MTSD). The analysis of such data has become more and more important…

The ALICE High Level Trigger has to process data online, in order to select interesting (sub)events, or to compress data efficiently by modeling techniques.Focusing on the main data source, the Time Projection Chamber (TPC), we present two…