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Wang et al., “Approximate Computing Methodologies for Image and Video Processing Applications,” ACM Transactions on Multimedia Computing, Communications, and Applications, vol. 12, no. 3, pp. 45-56, Sept. 2020" }, { "key": "ref4", "unstructured": "K. Liu et al., “Synthesis and Implementation of Approximate Computing Designs Using CAD Tools,” IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, vol. 39, no. 6, pp. 1101-1113, June 2021" }, { "key": "ref5", "unstructured": "Y. Xu et al., “Impact of Approximation Techniques on Power Consumption in Multiplier Circuits,” Proceedings of the International Symposium on Low Power Electronics and Design, pp. 235-243, July 2018" }, { "key": "ref6", "unstructured": "Z. Wang et al., “Comparative Analysis of Approximation Techniques in Digital Signal Processing Tasks,” IEEE Transactions on Signal Processing, vol. 67, no. 11, pp. 2805-2818, Nov. 2019" }, { "key": "ref7", "unstructured": "L. Zhang et al., “Approximate Computing Techniques for Low-Power Multipliers in IoT Devices,” IEEE Transactions on Circuits and Systems, vol. 64, no. 9, pp. 2015-2027, Sept. 2017" }, { "key": "ref8", "unstructured": "M. Li et al., “Optimization of Approximate Multipliers for Deep Learning Accelerators,” Proceedings of the International Conference on Neural Information Processing Systems, pp. 340-352, Dec. 2019" }, { "key": "ref9", "unstructured": "N. Wu et al., “Application of Approximate Multipliers in Biomedical Signal Processing,” Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, pp. 112-120, Aug. 2020" }, { "key": "ref10", "unstructured": "P. Wang et al., “Energy-Efficient Multiplier Architectures for Cryptographic Circuits Using Approximate Computing,” IEEE Transactions on Very Large Scale Integration (VLSI) Systems, vol. 26, no. 6, pp. 1123-1135, June 2018" }, { "key": "ref11", "unstructured": "Q. 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