SqueezeVGGNet: A Methodology for designing low complexity VGG Architecture for Resource Constraint Edge Applications. - Ramesh Reddy Chandrapu; Chandrajit Pal; Anagha Nimbekar; Amit Acharyya (NEWCAS, 2022)

Low Complexity Reconfigurable-Scalable Architecture Design Methodology for Deep Neural Network Inference Accelerator. - Anagha Nimbekar; Chandrasekhara Srinivas Vatti; Y. V. Sai Dinesh; Sunidhi Singh; Tarun Gupta; Ramesh Reddy Chandrapu; Amit Acharyya (SOCC, 2022)

Selective Binarization based Architecture Design Methodology for Resource-constrained Computation of Deep Neural Networks. - Ramesh Reddy Chandrapu; Dubacharla Gyaneshwar; Sumohana S. Channappayya; Amit Acharyya (ISCAS, 2023)