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2020 – today
- 2024
[j27]Donghyeon Han
, Junha Ryu, Sangyeob Kim, Sangjin Kim, Jongjun Park, Hoi-Jun Yoo:
MetaVRain: A Mobile Neural 3-D Rendering Processor With Bundle-Frame-Familiarity-Based NeRF Acceleration and Hybrid DNN Computing. IEEE J. Solid State Circuits 59(1): 65-78 (2024)- [j26]Sangjin Kim, Zhiyong Li, Soyeon Um, Wooyoung Jo, Sangwoo Ha, Juhyoung Lee, Sangyeob Kim, Donghyeon Han, Hoi-Jun Yoo:
DynaPlasia: An eDRAM In-Memory Computing-Based Reconfigurable Spatial Accelerator With Triple-Mode Cell. IEEE J. Solid State Circuits 59(1): 102-115 (2024) - [j25]Sangyeob Kim, Soyeon Kim, Seongyon Hong, Sangjin Kim, Donghyeon Han, Jiwon Choi, Hoi-Jun Yoo:
C-DNN: An Energy-Efficient Complementary Deep-Neural-Network Processor With Heterogeneous CNN/SNN Core Architecture. IEEE J. Solid State Circuits 59(1): 157-172 (2024) - [j24]Donghyeon Han, Junha Ryu, Sangyeob Kim, Sangjin Kim, Jongjun Park, Hoi-Jun Yoo:
A Low-Power Artificial-Intelligence-Based 3-D Rendering Processor With Hybrid Deep Neural Network Computing. IEEE Micro 44(1): 17-27 (2024) - [j23]Sangyeob Kim, Soyeon Kim, Seongyon Hong, Sangjin Kim, Jiwon Choi, Donghyeon Han, Hoi-Jun Yoo:
COOL-NPU: Complementary Online Learning Neural Processing Unit. IEEE Micro 44(1): 28-37 (2024) - [c42]Jueun Jung, Seungbin Kim, Bokyoung Seo, Wuyoung Jang, Sangho Lee, Jeongmin Shin, Donghyeon Han, Kyuho Jason Lee:
A Low-power and Real-time Semantic LiDAR SLAM Processor with Point Neural Network Segmentation and kNN Acceleration for Mobile Robots. COOL CHIPS 2024: 1-3 - [c41]Gwangtae Park, Seokchan Song, Haoyang Sang, Dongseok Im, Donghyeon Han, Sangyeob Kim, Hongseok Lee, Hoi-Jun Yoo:
A Low-power and Real-time Neural-Rendering Dense SLAM Processor with 3-Level Hierarchical Sparsity Exploitation. COOL CHIPS 2024: 1-3 - [c40]Junha Ryu, Hankyul Kwon, Wonhoon Park, Zhiyong Li, Beomseok Kwon, Donghyeon Han, Dongseok Im, Sangyeob Kim, Hyungnam Joo, Minsung Kim, Hoi-Jun Yoo:
A Low-Power Neural Graphics System for Instant 3D Modeling and Real-Time Rendering on Mobile AR/VR Devices. COOL CHIPS 2024: 1-3 - [c39]Jueun Jung, Seungbin Kim, Bokyoung Seo, Wuyoung Jang, Sangho Lee, Jeongmin Shin, Donghyeon Han, Kyuho Jason Lee:
LSPU: A 20.7 ms Low-Latency Point Neural Network-Based 3D Perception and Semantic LiDAR SLAM System-on-Chip for Autonomous Driving System. HCS 2024: 1-28 - [c38]Junha Ryu, Hankyul Kwon, Wonhoon Park, Zhiyong Li, Beomseok Kwon, Donghyeon Han, Dongseok Im, Sangyeob Kim, Hyungnam Joo, Minsung Kim, Hoi-Jun Yoo:
NeuGPU: A Neural Graphics Processing Unit for Instant Modeling and Real-Time Rendering on Mobile AR/VR Devices. HCS 2024: 1 - [c37]Seokchan Song, Haoyang Sang, Dongseok Im, Donghyeon Han, Sangyeob Kim, Hongseok Lee, Hoi-Jun Yoo:
Space-Mate: A 303.5mW Real-Time NeRF SLAM Processor with Sparse-Mixture-of-Experts-based Acceleration. HCS 2024: 1 - [c36]Wuyoung Jang, Sangho Lee, Jinhoon Jo, Jueun Jung, Donghyeon Han, Kyuho Lee:
A 422.1 Mpixels/J Tile-based 4K Super Resolution Processor with Variable Bit Compression. ISCAS 2024: 1-5 - [c35]Bokyoung Seo, Jueun Jung, Donghyeon Han, Kyuho Jason Lee:
An Energy-Efficient 3D Point Neural Network Accelerator with Fine-grained LiDAR-SoC Pipeline Structure. ISLPED 2024: 1-6 - [c34]Jueun Jung, Seungbin Kim, Bokyoung Seo, Wuyoung Jang, Sangho Lee, Jeongmin Shin, Donghyeon Han, Kyuho Jason Lee:
20.6 LSPU: A Fully Integrated Real-Time LiDAR-SLAM SoC with Point-Neural-Network Segmentation and Multi-Level kNN Acceleration. ISSCC 2024: 370-372 - [c33]Junha Ryu, Hankyul Kwon, Wonhoon Park, Zhiyong Li, Beomseok Kwon, Donghyeon Han, Dongseok Im, Sangyeob Kim, Hyungnam Joo, Hoi-Jun Yoo:
20.7 NeuGPU: A 18.5mJ/Iter Neural-Graphics Processing Unit for Instant-Modeling and Real-Time Rendering with Segmented-Hashing Architecture. ISSCC 2024: 372-374 - [c32]Gwangtae Park, Seokchan Song, Haoyang Sang, Dongseok Im, Donghyeon Han, Sangyeob Kim, Hongseok Lee, Hoi-Jun Yoo:
20.8 Space-Mate: A 303.5mW Real-Time Sparse Mixture-of-Experts-Based NeRF-SLAM Processor for Mobile Spatial Computing. ISSCC 2024: 374-376 - 2023
- [j22]Dongseok Im, Gwangtae Park, Junha Ryu, Zhiyong Li, Sanghoon Kang, Donghyeon Han, Jinsu Lee, Wonhoon Park, Hankyul Kwon, Hoi-Jun Yoo:
DSPU: An Efficient Deep Learning-Based Dense RGB-D Data Acquisition With Sensor Fusion and 3-D Perception SoC. IEEE J. Solid State Circuits 58(1): 177-188 (2023) - [j21]Zhiyong Li, Sangjin Kim, Dongseok Im, Donghyeon Han, Hoi-Jun Yoo:
An Efficient Deep-Learning-Based Super-Resolution Accelerating SoC With Heterogeneous Accelerating and Hierarchical Cache. IEEE J. Solid State Circuits 58(3): 614-623 (2023) - [j20]Dongseok Im, Gwangtae Park, Zhiyong Li, Junha Ryu, Sanghoon Kang, Donghyeon Han, Jinsu Lee, Wonhoon Park, Hankyul Kwon, Hoi-Jun Yoo:
A Mobile 3-D Object Recognition Processor With Deep-Learning-Based Monocular Depth Estimation. IEEE Micro 43(3): 74-82 (2023) - [c31]Jongjun Park, Donghyeon Han, Junha Ryu, Dongseok Im, Gwangtae Park, Hoi-Jun Yoo:
A 33.6 FPS Embedding based Real-time Neural Rendering Accelerator with Switchable Computation Skipping Architecture on Edge Device. A-SSCC 2023: 1-3 - [c30]Donghyeon Han, Junha Ryu, Sangyeob Kim, Sangjin Kim, Jongjun Park, Hoi-Jun Yoo:
A Low-power Neural 3D Rendering Processor with Bio-inspired Visual Perception Core and Hybrid DNN Acceleration. COOL CHIPS 2023: 1-3 - [c29]Sangyeob Kim, Soyeon Kim, Seongyon Hong, Sangjin Kim, Donghyeon Han, Jiwon Choi, Hoi-Jun Yoo:
COOL-NPU: Complementary Online Learning Neural Processing Unit with CNN-SNN Heterogeneous Core and Event-driven Backpropagation. COOL CHIPS 2023: 1-3 - [c28]Donghyeon Han, Junha Ryu, Sangyeob Kim, Sangjin Kim, Hoi-Jun Yoo:
MetaVRain: A 133mW Real-Time Hyper-Realistic 3D-NeRF Processor with 1D-2D Hybrid-Neural Engines for Metaverse on Mobile Devices. ISSCC 2023: 50-51 - [c27]Sangjin Kim, Zhiyong Li, Soyeon Um, Wooyoung Jo, Sangwoo Ha, Juhyoung Lee, Sangyeob Kim, Donghyeon Han, Hoi-Jun Yoo:
DynaPlasia: An eDRAM In-Memory-Computing-Based Reconfigurable Spatial Accelerator with Triple-Mode Cell for Dynamic Resource Switching. ISSCC 2023: 256-257 - [c26]Sangyeob Kim, Soyeon Kim, Seongyon Hong, Sangjin Kim, Donghyeon Han, Hoi-Jun Yoo:
C-DNN: A 24.5-85.8TOPS/W Complementary-Deep-Neural-Network Processor with Heterogeneous CNN/SNN Core Architecture and Forward-Gradient-Based Sparsity Generation. ISSCC 2023: 334-335 - [c25]Wooyoung Jo, Sangjin Kim, Juhyoung Lee, Donghyeon Han, Sangyeob Kim, Seungyoon Choi, Hoi-Jun Yoo:
NeRPIM: A 4.2 mJ/frame Neural Rendering Processing-in-memory Processor with Space Encoding Block-wise Mapping for Mobile Devices. VLSI Technology and Circuits 2023: 1-2 - [c24]Seokchan Song, Donghyeon Han, Sangjin Kim, Sangyeob Kim, Gwangtae Park, Hoi-Jun Yoo:
GPPU: A 330.4-μJ/ task Neural Path Planning Processor with Hybrid GNN Acceleration for Autonomous 3D Navigation. VLSI Technology and Circuits 2023: 1-2 - 2022
- [j19]Dongseok Im, Donghyeon Han, Sanghoon Kang, Hoi-Jun Yoo:
A Pipelined Point Cloud Based Neural Network Processor for 3-D Vision With Large-Scale Max Pooling Layer Prediction. IEEE J. Solid State Circuits 57(2): 661-670 (2022) - [j18]Juhyoung Lee, Sangyeob Kim, Sangjin Kim, Wooyoung Jo, Ji-Hoon Kim, Donghyeon Han, Hoi-Jun Yoo:
OmniDRL: An Energy-Efficient Deep Reinforcement Learning Processor With Dual-Mode Weight Compression and Sparse Weight Transposer. IEEE J. Solid State Circuits 57(4): 999-1012 (2022) - [j17]Donghyeon Han, Dongseok Im, Gwangtae Park, Youngwoo Kim, Seokchan Song, Juhyoung Lee, Hoi-Jun Yoo:
A Mobile DNN Training Processor With Automatic Bit Precision Search and Fine-Grained Sparsity Exploitation. IEEE Micro 42(2): 16-25 (2022) - [j16]Sangyeob Kim, Juhyoung Lee, Sanghoon Kang, Donghyeon Han, Wooyoung Jo, Hoi-Jun Yoo:
TSUNAMI: Triple Sparsity-Aware Ultra Energy-Efficient Neural Network Training Accelerator With Multi-Modal Iterative Pruning. IEEE Trans. Circuits Syst. I Regul. Pap. 69(4): 1494-1506 (2022) - [j15]Sangwoo Ha, Sangjin Kim, Donghyeon Han, Soyeon Um, Hoi-Jun Yoo:
A 36.2 dB High SNR and PVT/Leakage-Robust eDRAM Computing-In-Memory Macro With Segmented BL and Reference Cell Array. IEEE Trans. Circuits Syst. II Express Briefs 69(5): 2433-2437 (2022) - [j14]Seokchan Song, Soyeon Kim, Gwangtae Park, Donghyeon Han, Hoi-Jun Yoo:
A 49.5 mW Multi-Scale Linear Quantized Online Learning Processor for Real-Time Adaptive Object Detection. IEEE Trans. Circuits Syst. II Express Briefs 69(5): 2443-2447 (2022) - [c23]Donghyeon Han, Dongseok Im, Gwangtae Park, Youngwoo Kim, Seokchan Song, Juhyoung Lee, Hoi-Jun Yoo:
A 0.95 mJ/frame DNN Training Processor for Robust Object Detection with Real-World Environmental Adaptation. AICAS 2022: 37-40 - [c22]Donghyeon Han, Dongseok Im, Gwangtae Park, Youngwoo Kim, Seokchan Song, Juhyoung Lee, Hoi-Jun Yoo:
A DNN Training Processor for Robust Object Detection with Real-World Environmental Adaptation. AICAS 2022: 501 - [c21]Zhiyong Li, Sangjin Kim, Dongseok Im, Donghyeon Han, Hoi-Jun Yoo:
An 0.92 mJ/frame High-quality FHD Super-resolution Mobile Accelerator SoC with Hybrid-precision and Energy-efficient Cache. CICC 2022: 1-2 - [c20]Dongseok Im, Gwangtae Park, Junha Ryu, Zhiyong Li, Sanghoon Kang, Donghyeon Han, Jinsu Lee, Wonhoon Park, Hankyul Kwon, Hoi-Jun Yoo:
A Low-power and Real-time 3D Object Recognition Processor with Dense RGB-D Data Acquisition in Mobile Platforms. COOL CHIPS 2022: 1-3 - [c19]Donghyeon Han, Dongseok Im, Gwangtae Park, Youngwoo Kim, Seokchan Song, Juhyoung Lee, Hoi-Jun Yoo:
HNPU-V2: A 46.6 FPS DNN Training Processor for Real-World Environmental Adaptation based Robust Object Detection on Mobile Devices. HCS 2022: 1-18 - [c18]Dongseok Im, Gwangtae Park, Zhiyong Li, Junha Ryu, Sanghoon Kang, Donghyeon Han, Jinsu Lee, Wonhoon Park, Hankyul Kwon, Hoi-Jun Yoo:
DSPU: A 281.6mW Real-Time Deep Learning-Based Dense RGB-D Data Acquisition with Sensor Fusion and 3D Perception System-on-Chip. HCS 2022: 1-25 - [c17]Zhiyong Li, Sangjin Kim, Dongseok Im, Donghyeon Han, Hoi-Jun Yoo:
An Efficient High-quality FHD Super-resolution Mobile Accelerator SoC with Hybrid-precision and Energy-efficient Cache. HCS 2022: 1-26 - [c16]Dongseok Im, Gwangtae Park, Zhiyong Li, Junha Ryu, Sanghoon Kang, Donghyeon Han, Jinsu Lee, Hoi-Jun Yoo:
DSPU: A 281.6mW Real-Time Depth Signal Processing Unit for Deep Learning-Based Dense RGB-D Data Acquisition with Depth Fusion and 3D Bounding Box Extraction in Mobile Platforms. ISSCC 2022: 510-512 - 2021
- [j13]Sanghoon Kang, Gwangtae Park, Sangjin Kim, Soyeon Kim, Donghyeon Han, Hoi-Jun Yoo:
An Overview of Sparsity Exploitation in CNNs for On-Device Intelligence With Software-Hardware Cross-Layer Optimizations. IEEE J. Emerg. Sel. Topics Circuits Syst. 11(4): 634-648 (2021) - [j12]Donghyeon Han, Jinsu Lee, Hoi-Jun Yoo:
DF-LNPU: A Pipelined Direct Feedback Alignment-Based Deep Neural Network Learning Processor for Fast Online Learning. IEEE J. Solid State Circuits 56(5): 1630-1640 (2021) - [j11]Sanghoon Kang, Donghyeon Han, Juhyoung Lee, Dongseok Im, Sangyeob Kim, Soyeon Kim, Junha Ryu, Hoi-Jun Yoo:
GANPU: An Energy-Efficient Multi-DNN Training Processor for GANs With Speculative Dual-Sparsity Exploitation. IEEE J. Solid State Circuits 56(9): 2845-2857 (2021) - [j10]Donghyeon Han, Dongseok Im, Gwangtae Park, Youngwoo Kim, Seokchan Song, Juhyoung Lee, Hoi-Jun Yoo:
HNPU: An Adaptive DNN Training Processor Utilizing Stochastic Dynamic Fixed-Point and Active Bit-Precision Searching. IEEE J. Solid State Circuits 56(9): 2858-2869 (2021) - [j9]Soyeon Kim, Sanghoon Kang, Donghyeon Han, Sangjin Kim, Sangyeob Kim, Hoi-Jun Yoo:
An Energy-Efficient GAN Accelerator With On-Chip Training for Domain-Specific Optimization. IEEE J. Solid State Circuits 56(10): 2968-2980 (2021) - [j8]Soyeon Kim, Sangjin Kim, Sangyeob Kim, Donghyeon Han, Hoi-Jun Yoo:
A 64.1mW Accurate Real-Time Visual Object Tracking Processor With Spatial Early Stopping on Siamese Network. IEEE Trans. Circuits Syst. II Express Briefs 68(5): 1675-1679 (2021) - [c15]Juhyoung Lee, Changhyeon Kim, Donghyeon Han, Sangyeob Kim, Sangjin Kim, Hoi-Jun Yoo:
Energy-Efficient Deep Reinforcement Learning Accelerator Designs for Mobile Autonomous Systems. AICAS 2021: 1-4 - [c14]Surin Gweon, Sanghoon Kang, Donghyeon Han, Kyoung-Rog Lee, Kwantae Kim, Hoi-Jun Yoo:
FlashMAC: An Energy-Efficient Analog-Digital Hybrid MAC with Variable Latency-Aware Scheduling. A-SSCC 2021: 1-3 - [c13]Donghyeon Han, Dongseok Im, Gwangtae Park, Youngwoo Kim, Seokchan Song, Juhyoung Lee, Hoi-Jun Yoo:
An Energy-Efficient Deep Neural Network Training Processor with Bit-Slice-Level Reconfigurability and Sparsity Exploitation. COOL CHIPS 2021: 1-3 - [c12]Juhyoung Lee, Jihoon Kim, Wooyoung Jo, Sangyeob Kim, Sangjin Kim, Donghyeon Han, Jinsu Lee, Hoi-Jun Yoo:
An Energy-efficient Floating-Point DNN Processor using Heterogeneous Computing Architecture with Exponent-Computing-in-Memory. HCS 2021: 1-20 - [c11]Juhyoung Lee, Sangyeob Kim, Ji-Hoon Kim, Sangjin Kim, Wooyoung Jo, Donghyeon Han, Hoi-Jun Yoo:
OmniDRL: An Energy-Efficient Mobile Deep Reinforcement Learning Accelerators with Dual-mode Weight Compression and Direct Processing of Compressed Data. HCS 2021: 1-21 - [c10]Juhyoung Lee, Sangyeob Kim, Sangjin Kim, Wooyoung Jo, Donghyeon Han, Jinsu Lee, Hoi-Jun Yoo:
OmniDRL: A 29.3 TFLOPS/W Deep Reinforcement Learning Processor with Dualmode Weight Compression and On-chip Sparse Weight Transposer. VLSI Circuits 2021: 1-2 - 2020
- [j7]Youngwoo Kim, Donghyeon Han, Changhyeon Kim, Hoi-Jun Yoo:
A 0.22-0.89 mW Low-Power and Highly-Secure Always-On Face Recognition Processor With Adversarial Attack Prevention. IEEE Trans. Circuits Syst. II Express Briefs 67-II(5): 846-850 (2020) - [j6]Gwangtae Park, Dongseok Im, Donghyeon Han, Hoi-Jun Yoo:
A 1.15 TOPS/W Energy-Efficient Capsule Network Accelerator for Real-Time 3D Point Cloud Segmentation in Mobile Environment. IEEE Trans. Circuits Syst. II Express Briefs 67-II(9): 1594-1598 (2020) - [j5]Jinsu Lee, Sanghoon Kang, Jinmook Lee, Dongjoo Shin, Donghyeon Han, Hoi-Jun Yoo:
The Hardware and Algorithm Co-Design for Energy-Efficient DNN Processor on Edge/Mobile Devices. IEEE Trans. Circuits Syst. 67-I(10): 3458-3470 (2020) - [j4]Dongseok Im, Donghyeon Han, Sungpill Choi, Sanghoon Kang, Hoi-Jun Yoo:
DT-CNN: An Energy-Efficient Dilated and Transposed Convolutional Neural Network Processor for Region of Interest Based Image Segmentation. IEEE Trans. Circuits Syst. 67-I(10): 3471-3483 (2020) - [c9]Soyeon Kim, Sanghoon Kang, Donghyeon Han, Sangyeob Kim, Sangjin Kim, Hoi-Jun Yoo:
An Energy-Efficient GAN Accelerator with On-chip Training for Domain Specific Optimization. A-SSCC 2020: 1-4 - [c8]Sanghoon Kang, Donghyeon Han, Juhyoung Lee, Dongseok Im, Sangyeob Kim, Soyeon Kim, Hoi-Jun Yoo:
7.4 GANPU: A 135TFLOPS/W Multi-DNN Training Processor for GANs with Speculative Dual-Sparsity Exploitation. ISSCC 2020: 140-142 - [c7]Dongseok Im, Sanghoon Kang, Donghyeon Han, Sungpill Choi, Hoi-Jun Yoo:
A 4.45 ms Low-Latency 3D Point-Cloud-Based Neural Network Processor for Hand Pose Estimation in Immersive Wearable Devices. VLSI Circuits 2020: 1-2 - [i2]Donghyeon Han, Gwangtae Park, Junha Ryu, Hoi-Jun Yoo:
Extension of Direct Feedback Alignment to Convolutional and Recurrent Neural Network for Bio-plausible Deep Learning. CoRR abs/2006.12830 (2020)
2010 – 2019
- 2019
- [j3]Sungpill Choi, Kyeongryeol Bong, Donghyeon Han, Hoi-Jun Yoo:
CNNP-v2: A Memory-Centric Architecture for Low-Power CNN Processor on Domain-Specific Mobile Devices. IEEE J. Emerg. Sel. Topics Circuits Syst. 9(4): 598-611 (2019) - [j2]Donghyeon Han, Jinsu Lee, Jinmook Lee, Hoi-Jun Yoo:
A Low-Power Deep Neural Network Online Learning Processor for Real-Time Object Tracking Application. IEEE Trans. Circuits Syst. I Regul. Pap. 66-I(5): 1794-1804 (2019) - [c6]Sungpill Choi, Kyeongryeol Bong, Donghyeon Han, Hoi-Jun Yoo:
CNNP-v2: An Energy Efficient Memory-Centric Convolutional Neural Network Processor Architecture. AICAS 2019: 38-41 - [c5]Donghyeon Han, Hoi-Jun Yoo:
Direct Feedback Alignment Based Convolutional Neural Network Training for Low-Power Online Learning Processor. ICCV Workshops 2019: 2445-2452 - [c4]Dongseok Im, Donghyeon Han, Sungpill Choi, Sanghoon Kang, Hoi-Jun Yoo:
DT-CNN: Dilated and Transposed Convolution Neural Network Accelerator for Real-Time Image Segmentation on Mobile Devices. ISCAS 2019: 1-5 - [c3]Jinsu Lee, Juhyoung Lee, Donghyeon Han, Jinmook Lee, Gwangtae Park, Hoi-Jun Yoo:
LNPU: A 25.3TFLOPS/W Sparse Deep-Neural-Network Learning Processor with Fine-Grained Mixed Precision of FP8-FP16. ISSCC 2019: 142-144 - [c2]Donghyeon Han, Jinsu Lee, Jinmook Lee, Hoi-Jun Yoo:
A 1.32 TOPS/W Energy Efficient Deep Neural Network Learning Processor with Direct Feedback Alignment based Heterogeneous Core Architecture. VLSI Circuits 2019: 304- - [i1]Donghyeon Han, Hoi-Jun Yoo:
Efficient Convolutional Neural Network Training with Direct Feedback Alignment. CoRR abs/1901.01986 (2019) - 2018
- [j1]Kyeongryeol Bong, Sungpill Choi, Changhyeon Kim, Donghyeon Han, Hoi-Jun Yoo:
A Low-Power Convolutional Neural Network Face Recognition Processor and a CIS Integrated With Always-on Face Detector. IEEE J. Solid State Circuits 53(1): 115-123 (2018) - [c1]Donghyeon Han, Jinsu Lee, Jinmook Lee, Sungpill Choi, Hoi-Jun Yoo:
A 141.4 mW Low-Power Online Deep Neural Network Training Processor for Real-time Object Tracking in Mobile Devices. ISCAS 2018: 1-5
Coauthor Index
[j27] [j26] [j25] [j24] [j23] [c41] [c40] [c38] [c37] [c33] [c32] [j22] [j21] [j20] [c31] [c30] [c29] [c28] [c27] [c26] [c25] [c24] [j19] [j18] [j17] [j16] [j15] [j14] [c23] [c22] [c21] [c20] [c19] [c18] [c17] [c16] [j13] [j12] [j11] [j10] [j9] [j8] [c15] [c14] [c13] [c12] [c11] [c10] [j7] [j6] [j5] [j4] [c9] [c8] [c7] [i2] [j3] [j2] [c6] [c5] [c4] [c3] [c2] [i1] [j1] [c1]
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