Decimal floating-point fused multiply-add with redundant internal encodings. - Liu Han; Hao Zhang 041; Seok-Bum Ko (IET Comput. Digit. Tech., 2016)

Area- and power-efficient iterative single/double-precision merged floating-point multiplier on FPGA. - Hao Zhang 041; Dongdong Chen 002; Seok-Bum Ko (IET Comput. Digit. Tech., 2017)

Efficient Fixed/Floating-Point Merged Mixed-Precision Multiply-Accumulate Unit for Deep Learning Processors. - Hao Zhang 041; Hyuk Jae Lee; Seok-Bum Ko (ISCAS, 2018)

Retinal blood vessel segmentation using fully convolutional network with transfer learning. - Zhexin Jiang; Hao Zhang 041; Yi Wang 064; Seok-Bum Ko (Comput. Medical Imaging Graph., 2018)

High performance and energy efficient single-precision and double-precision merged floating-point adder on FPGA. - Hao Zhang 041; Dongdong Chen 002; Seok-Bum Ko (IET Comput. Digit. Tech., 2018)

Improved Hybrid Memory Cube for Weight-Sharing Deep Convolutional Neural Networks. - Hao Zhang 041; Jiongrui He; Seok-Bum Ko (AICAS, 2019)

Efficient Posit Multiply-Accumulate Unit Generator for Deep Learning Applications. - Hao Zhang 041; Jiongrui He; Seok-Bum Ko (ISCAS, 2019)

Efficient spiking neural network training and inference with reduced precision memory and computing. - Yi Wang 064; Karim Shahbazi; Hao Zhang 041; Kwang-Il Oh; Jae-Jin Lee; Seok-Bum Ko (IET Comput. Digit. Tech., 2019)

Efficient Multiple-Precision Floating-Point Fused Multiply-Add with Mixed-Precision Support. - Hao Zhang 041; Dongdong Chen 002; Seok-Bum Ko (IEEE Trans. Computers, 2019)

Novel convolutional neural network architecture for improved pulmonary nodule classification on computed tomography. - Yi Wang 064; Hao Zhang 041; Kum Ju Chae; Younhee Choi; Gong Yong Jin; Seok-Bum Ko (Multidimens. Syst. Signal Process., 2020)

New Flexible Multiple-Precision Multiply-Accumulate Unit for Deep Neural Network Training and Inference. - Hao Zhang 041; Dongdong Chen 002; Seok-Bum Ko (IEEE Trans. Computers, 2020)

Design of Power Efficient Posit Multiplier. - Hao Zhang 041; Seok-Bum Ko (IEEE Trans. Circuits Syst. II Express Briefs, 2020)

Efficient Multiple-Precision Posit Multiplier. - Hao Zhang 041; Seok-Bum Ko (ISCAS, 2021)

Energy efficient spiking neural network processing using approximate arithmetic units and variable precision weights. - Yi Wang 064; Hao Zhang 041; Kwang-Il Oh; Jae-Jin Lee; Seok-Bum Ko (J. Parallel Distributed Comput., 2021)

A Real-Time Architecture for Pruning the Effectual Computations in Deep Neural Networks. - Mohammadreza Asadikouhanjani; Hao Zhang 041; Gopalakrishnan Lakshminarayanan; Hyuk-Jae Lee; Seok-Bum Ko (IEEE Trans. Circuits Syst. I Regul. Pap., 2021)

Efficient Approximate DNN Accelerators for Edge Devices: An Experimental Study. - Mohammadreza Asadikouhanjani; Hao Zhang 041; Kyunghwan Cho; Young-Jin Park; Seok-Bum Ko (Approximate Computing, 2022)

Approximate Computing for Efficient Neural Network Computation: A Survey. - Hao Zhang 041; Mohammadreza Asadikouhanjani; Jie Han 001; Deivalakshmi Subbian; Seok-Bum Ko (Approximate Computing, 2022)

Segmentation for document layout analysis: not dead yet. - Logan Markewich; Hao Zhang 041; Yubin Xing; Navid Lambert-Shirzad; Zhexin Jiang; Roy Ka-Wei Lee; Zhi Li; Seok-Bum Ko (Int. J. Document Anal. Recognit., 2022)

Variable-Precision Approximate Floating-Point Multiplier for Efficient Deep Learning Computation. - Hao Zhang 041; Seok-Bum Ko (IEEE Trans. Circuits Syst. II Express Briefs, 2022)

Construction of Hardware Course Group in New Engineering Computer Specialty Facing Complex Engineering Problems. - Yongguo Jiang; Haipeng Qu; Hao Su; Hao Zhang 041 (ACM TUR-C, 2023)

Efficient Approximate Posit Multipliers for Deep Learning Computation. - Hao Zhang 041; Seok-Bum Ko (IEEE J. Emerg. Sel. Topics Circuits Syst., 2023)

Energy Efficient FPGA-Based Binary Transformer Accelerator for Edge Devices. - Congpeng Du; Seok-Bum Ko; Hao Zhang 041 (ISCAS, 2024)

Decoder Reduction Approximation Scheme for Booth Multipliers. - Muhammad Hamis Haider; Hao Zhang 041; Seok-Bum Ko (IEEE Trans. Computers, 2024)

Anterior mediastinal nodular lesion segmentation from chest computed tomography imaging using UNet based neural network with attention mechanisms. - Yi Wang 064; Won Gi Jeong; Hao Zhang 041; Younhee Choi; Gong Yong Jin; Seok-Bum Ko (Multim. Tools Appl., 2024)

Merge Loss Calculation Method for Highly Imbalanced Data Multiclass Classification. - Zehua Du; Hao Zhang 041; Zhiqiang Wei 002; Yuanyuan Zhu; Jiali Xu; Xianqing Huang; Bo Yin (IEEE Trans. Neural Networks Learn. Syst., 2024)