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In the era of sky surveys like Palomar Transient Factory (PTF), ZwickyTransient Facility (ZTF) and the upcoming Vera Rubin Observatory (VRO) andILMT, a plethora of image data will be available. ZTF scans the sky with afield of view of 48 deg$^{2}$ and VRO will have a FoV of 9.6 deg$^{2}$ but witha much larger aperture. The 4m ILMT covers a 22$'$ wide strip of the sky. Beinga zenith telescope, ILMT has several advantages like low observation air mass,best image quality, minimum light pollution and no pointing time loss.Transient detection requires all these imaging data to be processed through aDifference Imaging Algorithm (DIA) followed by subsequent identification andclassification of transients. The ILMT is also expected to discover severalknown and unknown astrophysical objects including transients. Here, we proposea pipeline with an image subtraction algorithm and a convolutional neuralnetwork (CNN) based automated transient discovery and classification system.The pipeline was tested on ILMT data and the transients as well as variablecandidates were recovered and classified.

Automated transient detection in the context of the 4m ILMT