| Distributing DNN training over IoT edge devices based on transfer learning | 0 | 0.34 | 2022 |
| LATIM: Loading-Aware Offline Training Method for Inverter-Based Memristive Neural Networks | 1 | 0.36 | 2021 |
| OPTIMA: An Approach for Online Management of Cache Approximation Levels in Approximate Processing Systems | 0 | 0.34 | 2021 |
| An Energy-Efficient Inference Method in Convolutional Neural Networks Based on Dynamic Adjustment of the Pruning Level | 0 | 0.34 | 2021 |
| Loading-Aware Reliability Improvement of Ultra-Low Power Memristive Neural Networks | 0 | 0.34 | 2021 |
| Reliability Enhancement of Inverter-Based Memristor Crossbar Neural Networks Using Mathematical Analysis of Circuit Non-Idealities | 1 | 0.37 | 2021 |
| DART: A Framework for Determining Approximation Levels in an Approximable Memory Hierarchy | 0 | 0.34 | 2020 |
| Low-power Accuracy-configurable Carry Look-ahead Adder Based on Voltage Overscaling Technique | 0 | 0.34 | 2020 |
| EGAN: A Framework for Exploring the Accuracy vs. Energy Efficiency Trade-off in Hardware Implementation of Error Resilient Applications | 1 | 0.37 | 2020 |
| Res-DNN: A Residue Number System-Based DNN Accelerator Unit | 5 | 0.45 | 2020 |
| Design Exploration of Energy-Efficient Accuracy-Configurable Dadda Multipliers With Improved Lifetime Based on Voltage Overscaling | 1 | 0.35 | 2020 |
| Offline Training Improvement Of Inverter-Based Memristive Neural Networks Using Inverter Voltage Characteristic Smoothing | 0 | 0.34 | 2020 |
| Self-Adjusting Monitor for Measuring Aging Rate and Advancement | 2 | 0.51 | 2020 |
| X-CGRA: An Energy-Efficient Approximate Coarse-Grained Reconfigurable Architecture | 2 | 0.42 | 2020 |
| Block-Based Carry Speculative Approximate Adder for Energy-Efficient Applications | 2 | 0.37 | 2020 |
| Circuit-Level Techniques for Logic and Memory Blocks in Approximate Computing Systemsx | 0 | 0.34 | 2020 |
| POLAR: A Pipelined/Overlapped FPGA-Based LSTM Accelerator | 1 | 0.35 | 2020 |
| RandShift: An Energy-Efficient Fault-Tolerant Method in Secure Nonvolatile Main Memory | 1 | 0.35 | 2020 |
| Interstice: Inverter-Based Memristive Neural Networks Discretization for Function Approximation Applications | 0 | 0.34 | 2020 |
| O⁴-DNN: A Hybrid DSP-LUT-Based Processing Unit With Operation Packing and Out-of-Order Execution for Efficient Realization of Convolutional Neural Networks on FPGA Devices | 1 | 0.37 | 2020 |
| TOSAM: An Energy-Efficient Truncation- and Rounding-Based Scalable Approximate Multiplier | 8 | 0.58 | 2019 |
| A Theoretical Framework for Quality Estimation and Optimization of DSP Applications Using Low-Power Approximate Adders. | 4 | 0.40 | 2019 |
| OCTAN: An On-Chip Training Algorithm for Memristive Neuromorphic Circuits | 1 | 0.35 | 2019 |
| ACHILLES: Accuracy-Aware High-Level Synthesis Considering Online Quality Management | 0 | 0.34 | 2019 |
| Space Expansion of Feature Selection for Designing more Accurate Error Predictors. | 0 | 0.34 | 2019 |
| Energy Consumption and Lifetime Improvement of Coarse-Grained Reconfigurable Architectures Targeting Low-Power Error-Tolerant Applications. | 1 | 0.35 | 2018 |
| PX-CGRA: Polymorphic approximate coarse-grained reconfigurable architecture | 4 | 0.43 | 2018 |
| An Efficient False Path-Aware Heuristic Critical Path Selection Method with High Coverage of the Process Variation Space. | 1 | 0.35 | 2018 |
| An Ultra Low-Power Memristive Neuromorphic Circuit for Internet of Things Smart Sensors. | 5 | 0.45 | 2018 |
| An Energy-Efficient, Yet Highly-Accurate, Approximate Non-Iterative Divider | 1 | 0.37 | 2018 |
| TheSPoT: Thermal Stress-Aware Power and Temperature Management for Multiprocessor Systems-on-Chip. | 10 | 0.59 | 2018 |
| RAP-CLA: A Reconfigurable Approximate Carry Look-Ahead Adder. | 11 | 0.62 | 2018 |
| Approximate Reverse Carry Propagate Adder for Energy-Efficient DSP Applications. | 3 | 0.39 | 2018 |
| PHAX: Physical Characteristics Aware Ex-Situ Training Framework for Inverter-Based Memristive Neuromorphic Circuits. | 3 | 0.43 | 2018 |
| Toward Approximate Computing for Coarse-Grained Reconfigurable Architectures. | 1 | 0.48 | 2018 |
| Lifetime improvement by exploiting aggressive voltage scaling during runtime of error-resilient applications. | 4 | 0.44 | 2018 |
| Energy and Reliability Improvement of Voltage-Based, Clustered, Coarse-Grain Reconfigurable Architectures by Employing Quality-Aware Mapping. | 3 | 0.45 | 2018 |
| Dual-Quality 4: 2 Compressors for Utilizing in Dynamic Accuracy Configurable Multipliers. | 10 | 0.64 | 2017 |
| Robust neuromorphic computing in the presence of process variation. | 1 | 0.41 | 2017 |
| LETAM: A low energy truncation-based approximate multiplier. | 2 | 0.39 | 2017 |
| An energy and area efficient yet high-speed square-root carry select adder structure. | 2 | 0.40 | 2017 |
| RoBA Multiplier: A Rounding-Based Approximate Multiplier for High-Speed yet Energy-Efficient Digital Signal Processing. | 15 | 0.76 | 2017 |
| Hybrid TFET-MOSFET circuit: A solution to design soft-error resilient ultra-low power digital circuit. | 0 | 0.34 | 2017 |
| CL-CPA: A hybrid carry-lookahead/carry-propagate adder for low-power or high-performance operation mode. | 0 | 0.34 | 2017 |
| TruncApp: A truncation-based approximate divider for energy efficient DSP applications. | 2 | 0.39 | 2017 |
| Efficient Critical Path Identification Based on Viability Analysis Method Considering Process Variations. | 2 | 0.37 | 2017 |
| All-Region Statistical Model for Delay Variation Based on Log-Skew-Normal Distribution. | 4 | 0.45 | 2016 |
| High-Speed and Energy-Efficient Carry Skip Adder Operating Under a Wide Range of Supply Voltage Levels | 3 | 0.42 | 2016 |
| Seerad: A High Speed Yet Energy-Efficient Rounding-Based Approximate Divider | 4 | 0.48 | 2016 |
| Hybrid TFET-MOSFET circuits: An approach to design reliable ultra-low power circuits in the presence of process variation | 1 | 0.35 | 2016 |
