RESEARCH TOPIC PRESENTATION
| Date | Name | Title |
|---|---|---|
| 19.12.10 | Beomsik Kim | SW Framework cFS Porting |
| 19.11.26 | Yukuan Sun | MetaPruning: Meta Learning for Automatic Neural Network Channel Pruning |
| 19.11.12 | Kyusik Choi | Various trials to get high accuracy in multi-phase network |
| 19.11.07 | Jeonggyu Jang | |
| 19.11.07 | Heeji Im | Improvement of CNN-based Road Extraction from Satellite Images via Morphological Image Processing |
| 19.10.01 | Jeonggyu Jang | ESWEEK presentation rehearsal |
| 19.08.29 | Jonghun Jeong | Automatic Convolution Neural Network Model Compression Framework for Resource-Constrained Embedded Systems |
| 19.08.22 | Beomsik Kim | Background of LEON/RTEMS |
| 19.08.09 | Jeonggyu Jang | A SIMD-Aware Pruning Technique for Convolutional Neural Networks with Multi-Sparsity Levels |
| 19.08.09 | Dasom Lee | Framework to Automatically Create Lightweight Neural Networks |
| 19.08.01 | Kyusik Choi | Various progress of Multi-level Network with Runtime Configurable |
| 19.08.01 | Beomsik Kim | NASA core Flight System (cFS) Background and Overview |
| 19.07.26 | Heeji Im | Analysis of Semantic Segmentation in Satellite Images |
| 19.07.26 | Jonghun Jeong | Analysis and Optimization of CNN-based Super-resolution |
| 19.07.18 | Hyunseok Jeong | Context-Aware Dataflow Adaptation Technique for Low-Power Multi-Core Embedded Systems |
| 19.06.20 | Jonghun Jeong | Machine Learning with Low-Power Microprocessor |
| 19.05.24 | Dasom Lee | Machine Learning with Low-Power Microprocessor |
| 19.05.16 | Kyusik Choi | Runtime Configurable method for Multi-level Network |
| 19.05.16 | Beomsik Kim | Lifetime Enhancement of Satellite Embedded Systems via Online Task Mapping and Frequency Assignment |
| 19.05.02 | Hyunseok Jeong | Machine Learning with Low-Power Microprocessor |
| 19.04.04 | Heeji Im | Analysis and Optimization for Satellite Image Semantic Segmentation |
| 19.03.21 | Jeonggyu Jang | Convolution Layer by GEMM with SIMD |
| 19.03.14 | Dasom Lee | Real-Time Schedulability Analysis and Enhancement of Transiently Powered Processors with NVMs |
| 19.02.28 | Jonghun Jeong | Implementing/analyzing super- resolution application |
| 19.02.12 | Hyunseok Jeong | Context-Aware Dataflow Adaption Technique for Low-Power Multi-Core Embedded Systems |
| 19.01.14 | Jeonggyu Jang | Accurate Image Super-Resolution Using Very Deep Convolutional Networks Fully Convolutional Networks for Semantic Segmentation |
| 19.01.03 | Jonghun Jeong | Research Management and Collaboration Tool |
| 18.12.27 | Hoeseok Yang | Welcome to MObile COmputing Lab. |
| 18.12.27 | Beomsik Kim | Thermal Cycling Aware Reliability Improvement for Satellite Payload Embedded Software |
| 18.12.18 | Dasom Lee | Real-Time Schedulability Analysis and Enhancement of Transiently Powered Processors with NVMs |
| 18.12.06 | Kyusik Choi | Introduction and Issue for Adaptive Multi-Phase Network by Pruning-Restoring Train |
| 18.11.14 | Unhee Joh | 구조화된 요구사항 작성을 위한 STK 검사기 |
| 18.10.30 | Heeji Im | Introduction of RISC-V |
| 18.10.18 | Hyunseok Jeong | Real-Time Schedulability Analysis and Enhancement of Transiently Powered Processors with NVMs |
| 18.10.12 | Jeonggyu Jang | Adaptive_Multi-Phase_Network_by_Pruning–Restoring_Train |
| 18.08.30 | Dasom Lee | Real-time scheduling with Non-Volatile Processor |
| 18.07.12 | Jeonggyu Jang | Adaptive Multi-Phase Network by Pruning–Restoring Train |
| 18.06.14 | Jaeseo Noh & Unhe Jo | 융합 전자 연구 발표 리허설 및 토의 |
| 18.06.07 | Hyunseok Jeong | DAC Presentation Draft Feedback |
| 18.06.07 | Dasom Lee | Communication Method Between HPS and FPGA (Wait signal, Burst Transfer) |
| 18.05.31 | Hoeseok Yang | Welcome to Mobile Computing Lab. (Lab Introduction) |
| 18.05.24 | Kyoseung Koo | Experimental Problems in ODROID-XU3 about OpenCV |
| 18.05.17 | Kyusik Choi | Introduction to Neural Network Project and Impact of Changing Dataset |
| 18.05.03 | Kyoseung Koo | Five ways not to fool yourself or: designing experiments for understanding performance |
| 18.04.12 | Dasom Lee | Energy-Aware Memory Mapping for Hybrid FRAM-SRAM MCUs in Intermittently-Powered IoT Device |
| 18.04.05 | Hyunseok Jeong | Introduction to NVM Project & Communication Method Between HPS and FPGA using 32bit-Register |
| 18.03.30 | Jeonggyu Jang | SqueezeNet: AlexNet-level Accuracy with 50x Fewer Parameters and <0.5MB Model Size |
| 18.03.15 | Kyusik Choi | Retraining Inception V3 and Model Management Techniques in Tensorflow |
| 18.03.08 | Kyoseung Koo | Satisfying QoS under Application Interference State |
| 18.03.02 | Dasom Lee | Commucation between ARM core and FPGA |
| 18.02.21 | Hyunseok Jeong | Experiment with Various Mode Switching Methods using DAL |
| 18.01.05~ 18.02.10 | - | 해외 출장으로 인한 온라인 세미나 진행 |
| 17.12.20 | - | RTOS Seminar |
| 17.11.30 | Jeonggyu Jang | Reinforcement learning - Deep Q-Network |
| 17.11.24 | Kyusik Choi | Rocketlogger - Mobile Power Logger for Prototyping IoT Devices |
| 17.11.17 | Kyoseung Koo | Build uCOS-II Application on board with NIOS II Processor |
| 17.11.02 | Dasom Lee | Review: Improving Reliability through Task Recomputation in Heterogeneous Multi-core Embedded Systems (2013) |
| 17.10.27 | Hyunseok Jeong | Analysis and Profiling for OpenCV Parallelization |
| 17.09.28 | Jeonggyu Jang | RTOS (Real-Time Operation System) Wind River - VxWorks |
| 17.09.21 | Kyusik Choi | 현재 연구실 홈페이지에 대한 고찰과 새로운 홈페이지 제작 토의 |
| 17.09.14 | Kyoseung Koo | Internal Adaption with Neural Network |
| 17.09.07 | Dasom Lee | Linux Kernel Camp 2017 - Memory |
| 17.08.17 | Hyunseok Jeong | Improvement of Power Model for Context-Aware Stereo-Vision |
| 17.08.10 | Jeonggyu Jang | NLP with python(NL to controlled NL) |
| 17.07.14 | Kyusik Choi | 경신 과제와 Openpyxl |
| 17.07.07 | Dasom Lee | Controlled Natural Language Survey |
| 17.06.30 | Kyoseung Koo | An Online Self-Adaptive System Management Technique for Multi-Core Systems With Neural Network |
| 17.06.15 | Hyunseok Jeong | Dynamic Profiling Tool using TAU |
| 17.05.19 | Jeonggyu Jang | Executable Dataflow Benchmark Generation Technique for Multi-Core Embedded Systems |
| 17.05.11 | Kyoseung Koo | Agile and Extreme Programming |
| 17.04.05 | Dasom Lee | IEC 62304 review & V model |
| 17.03.22 | Hyunseok Jeong | Modified Stereo Vision Concept and Workload Profiling |
| 17.03.15 | Hojin Ahn | CFS and HMP scheduler |
| 17.03.08 | Jeonggyu Jang | HOPES of Parallel Embedded Software |
| 17.03.03 | Kyoseung Koo | Deep Learning with Caffe and NVIDIA Deep Learning Institute |
| 17.02.24 | Dasom Lee | Faster R-CNN |
| 17.02.16 | Hyunseok Jeong | DAL Specification of Context-Aware Stereo Vision Algorithm at the Ordroid-XU3 |
| 17.02.03 | Hojin Ahn | HMP Migration |
| 16.11.23 | Hyunseok Jeong | Improving Context-Aware Real-Time Stereo Vision using Duo3D |
PAPER REVIEW
| Date | Name | Title |
|---|---|---|
| 19.12.23 | Heeji Im | Beyond the Pixel-Wise Loss for Topology-Aware Delineation |
| 19.12.03 | Seongik Jang | Reliability-Aware Mapping Optimization of Multi-Core Systems with Mixed-Criticality |
| 19.11.26 | Beomsik Kim | Analysis and Optimization of Soft Error Tolerance Strategies for Real-time Systems |
| 19.11.12 | Jonghun Jeong | Efficient Structured Pruning and Architecture Searching for Group Convolution |
| 19.10.08 | Seongik Jang | Task-Level Re-Execution Framework for Improving Fault Tolerance on Symmetry Multiprocessors |
| 19.10.01 | Kyusik Choi | Slimmable Neural Networks |
| 19.08.29 | Heeji Im | Fully Convolutional Network for Automatic Road Extraction from Satellite Imagery |
| 19.08.22 | Hyunseok Jeong | Accuracy vs. Efficiency: Achieving Both through FPGA-Implementation Aware Neural Architecture Search |
| 19.07.18 | Dasom Lee | DeepThings: Distributed Adaptive Deep Learning Inference on Resource-Constrained IoT Edge Clusters |
| 19.07.12 | Kyusik Choi | Filter Pruning via Geometric Median for Deep Convolutional Neural Networks Acceleration |
| 19.06.28 | Heeji Im | Rethinking Atrous Convolution for Semantic Image Segmentation (DeepLab V3) |
| 19.06.28 | Jeonggyu Jang | The Lottery Ticket Hypothesis: Finding Sparse, Trainable Neural Networks |
| 19.06.20 | Hyunseok Jeong | Online Human Activity Recognition using Low-Power Wearable Devices |
| 19.06.07 | Beomsik Kim | High-Reliability FPGA-Based Systems Space, High-Energy |
| 19.06.07 | Jeonggyu Jang | Scalpel: Customizing DNN Pruning to the Underlying Hardware Parallelism |
| 19.05.24 | Jonghun Jeong | Pruning Filters for Efficient Convnets |
| 19.05.09 | Heeji Im | Aerial LaneNet: Lane Marking Semantic Segmentation in Aerial Imagery using Wavelet-Enhanced Cost-sensitive Symmetric Fully Convolutional Neural Networks |
| 19.05.09 | Dasom Lee | CMSIS-NN: Efficient Neural Network Kernels for Arm Cortex-M CPUs |
| 19.05.02 | Kyusik Choi | Channel Prunign for Accelerating Very Deep Neural Network |
| 19.03.28 | Heeji Im | MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications |
| 19.03.28 | Hyunseok Jeong | Dynamic Energy Burst Scaling for Transiently Powered Systems |
| 19.03.21 | Beomsik Kim | Improving System-Level Lifetime Reliability of Multicore Soft Real-Time Systems |
| 19.03.14 | Jonghun Jeong | Fast Training of Convolutional Networks through FFTs |
| 19.03.07 | Kyusik Choi | Characterising Across-Stack Optimisations for Deep Convolutional Neural Networks |
| 19.03.07 | Beomsik Kim | Mitigation of Thermo-cycling effects in Flip-chip FPGA-based Space-borne Systems by Cyclic On-chip Task Relocation |
| 19.02.28 | Dasom Lee | Graceful Performance Modulation for Power-Neutral Transient Computing System, Hibernus++: A Self-Calibrating and Adaptive System for Transiently-Powered Embedded Devices |
| 19.02.12 | Kyusik Choi | Introduction and Issue for Adaptive Multi-Phase Network by Pruning-Restoring Train |
| 19.01.14 | Heeji Im | U-Net : Convolutional Networks for Biomedical Image Segmentation |
| 19.01.03 | Hyunseok Jeong | An Extensible System Simulator for Intermittently Powered Multiple Peripheral IoT Devices |
| 18.12.13 | Jeonggyu Jang | Efficient Sparse-Winograd Convolutional Neural Networks |
| 18.12.06 | Jaeseo Noh | Pruning Convolutional Neural Networks for Resource Efficient Inference |
| 18.11.19 | Dasom Lee | ICCAD PAPER (Dynamic Resource Management for Heterogeneous Many-cores, EMAT: An Efficient Multi-Task Architecture for Transfer Learning using ReRAM) |
| 18.11.14 | Beomsik Kim | Co-Scheduling on Fused CPU-GPU Architectures |
| 18.10.30 | Kyusik Choi | Progress in Adaptive Multi-Phase method in Network Compression and Introduction of ONNX |
| 18.10.18 | Unhee Jo | 구간분할과 논항정보를 이용한 구문분석시스템 구현에 관한 연구 |
| 18.10.12 | Heeji Im | The Component Software Challenge for Real-Time Systems |
| 18.08.30 | Jaeseo Noh | PackNet : Adding Multiple Tasks to a Single Network by Iterative Pruning |
| 18.08.16 | Beomsik Kim | Compact Thermal Modeling for Temperature-Aware Design |
| 18.07.19 | Dasom Lee | Energy-Adaptive Scheduling of Imprecise Computation Tasks for QoS Optimization in Real-Time MPSoC Systems |
| 18.07.12 | Kyusik Choi | DSD : DENSE-SPARSE-DENSE Training For Deep Neural Networks |
| 18.05.24 | Jeonggyu Jang | ResNeXt Aggregated Residual Transformations for Deep Neural Networks |
| 18.05.17 | Jaeseo Noh | Compression of Deep Convolutional Neural Networks for Fast and Low Power Mobile Applications |
| 18.05.03 | Kyusik Choi | LCNN: Lookup-based Convolutional Neural Network |
| 18.04.12 | Kyoseung Koo | Designing Energy-Efficient Convolution Neural Networks using Energy-Aware Pruning |
| 18.03.30 | Dasom Lee | Energy Optimization for Data Allocation with Hybrid SRAM + NVM SPM (TCAS-I, 2018) |
| 18.03.15 | Hyunseok Jeong | Pinatubo: A Processing-in-Memory Architecture for Bulk Bitwise Operations in Emerging Non-volatile Memories |
| 18.03.08 | Jeonggyu Jang | TACLeBench: A Benchmark Collection to Support Worst-Case Execution Time Research |