Asim Khan

TL;DR: This survey paper is intended to provide a preliminary review of the available literature on the computer vision efforts against COVID-19 pandemic, and to make it available to computer vision researchers to save precious time.

TL;DR: A pedestrian detection framework that is computationally less expensive as well as more accurate than HOG-linear SVM and hardware implementation on Altera Cyclone IV field-programmable gate array results in more than 40% savings in logic resources.

TL;DR: A preliminary review of the literature on research community efforts against COVID-19 pandemic is presented to make it possible for computer vision researchers to find existing and future research directions.

TL;DR: In this article, the effect of gas-phase fluorination on DC flashover characteristics of epoxy resin/Al2O3 nanocomposites was analyzed, and it was found that the fluorination modifies the surface molecular structure of the epoxy resins, which may weaken its adsorption capacity for gases and make it easier to desorb gases and reduce flashover voltage.

TL;DR: The proposed DeepLens Classification and Detection Model (DCDM) approach deals with limitations by introducing automated detection and classification of the leaf diseases in fruits and vegetables via scalable transfer learning on AWS SageMaker and importing on AWS DeepLens for real-time practical usability.