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ORCIDChristos-Savvas Bouganis
Christos Bouganis
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- affiliation: Imperial College London, UK
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2020 – today
- 2024
[j35]Guoxuan Xia
, Christos-Savvas Bouganis:
Augmenting the Softmax with Additional Confidence Scores for Improved Selective Classification with Out-of-Distribution Data. Int. J. Comput. Vis. 132(9): 3714-3752 (2024)- [c116]Omar Sharif, Christos-Savvas Bouganis:
A Framework for Designing Scalable Gaussian Belief Propagation Accelerators for use in SLAM. DATE 2024: 1-2 - [c115]Zhewen Yu, Christos-Savvas Bouganis:
Auto WS: Automate Weights Streaming in Layer-Wise Pipelined DNN Accelerators. DATE 2024: 1-6 - [c114]Petros Toupas, Zhewen Yu, Christos-Savvas Bouganis, Dimitrios Tzovaras:
SMOF: Streaming Modern CNNs on FPGAs with Smart Off-Chip Eviction. FCCM 2024: 185-196 - [c113]Zhewen Yu, Sudarshan Sreeram, Krish Agrawal, Junyi Wu, Alexander Montgomerie-Corcoran, Cheng Zhang, Jianyi Cheng, Christos-Savvas Bouganis, Yiren Zhao:
HASS: Hardware-Aware Sparsity Search for Dataflow DNN Accelerator. FPL 2024: 257-263 - [c112]Georgios Zampokas, Christos-Savvas Bouganis, Dimitrios Tzovaras:
Latency Driven Spatially Sparse Optimization for Multi-Branch CNNs for Semantic Segmentation. WACV (Workshops) 2024: 949-957 - [i35]Guoxuan Xia, Olivier Laurent, Gianni Franchi, Christos-Savvas Bouganis:
Understanding Why Label Smoothing Degrades Selective Classification and How to Fix It. CoRR abs/2403.14715 (2024) - [i34]Petros Toupas, Zhewen Yu, Christos-Savvas Bouganis, Dimitrios Tzovaras:
SMOF: Streaming Modern CNNs on FPGAs with Smart Off-Chip Eviction. CoRR abs/2403.18921 (2024) - [i33]Pengtao Chen, Mingzhu Shen, Peng Ye, Jianjian Cao, Chongjun Tu, Christos-Savvas Bouganis, Yiren Zhao, Tao Chen:
Δ-DiT: A Training-Free Acceleration Method Tailored for Diffusion Transformers. CoRR abs/2406.01125 (2024) - [i32]Zhewen Yu, Sudarshan Sreeram, Krish Agrawal, Junyi Wu, Alexander Montgomerie-Corcoran, Cheng Zhang, Jianyi Cheng, Christos-Savvas Bouganis, Yiren Zhao:
HASS: Hardware-Aware Sparsity Search for Dataflow DNN Accelerator. CoRR abs/2406.03088 (2024) - 2023
- [j34]Stylianos I. Venieris, Christos-Savvas Bouganis, Nicholas D. Lane:
Multiple-Deep Neural Network Accelerators for Next-Generation Artificial Intelligence Systems. Computer 56(3): 70-79 (2023) - [c111]Petros Toupas, Christos-Savvas Bouganis, Dimitrios Tzovaras:
FMM-X3D: FPGA-Based Modeling and Mapping of X3D for Human Action Recognition. ASAP 2023: 119-126 - [c110]Benjamin Biggs, Christos-Savvas Bouganis, George A. Constantinides:
ATHEENA: A Toolflow for Hardware Early-Exit Network Automation. FCCM 2023: 121-132 - [c109]Petros Toupas, Alexander Montgomerie-Corcoran, Christos-Savvas Bouganis, Dimitrios Tzovaras:
HARFLOW3D: A Latency-Oriented 3D-CNN Accelerator Toolflow for HAR on FPGA Devices. FCCM 2023: 144-154 - [c108]Petros Toupas, Christos-Savvas Bouganis, Dimitrios Tzovaras:
fpgaHART: A Toolflow for Throughput-Oriented Acceleration of 3D CNNs for HAR onto FPGAs. FPL 2023: 86-92 - [c107]Zhewen Yu, Christos-Savvas Bouganis:
Mixed-TD: Efficient Neural Network Accelerator with Layer-Specific Tensor Decomposition. FPL 2023: 204-211 - [c106]Alexander Montgomerie-Corcoran, Zhewen Yu, Jianyi Cheng, Christos-Savvas Bouganis:
PASS: Exploiting Post-Activation Sparsity in Streaming Architectures for CNN Acceleration. FPL 2023: 288-293 - [c105]Alexander Montgomerie-Corcoran, Petros Toupas, Zhewen Yu, Christos-Savvas Bouganis:
SATAY: A Streaming Architecture Toolflow for Accelerating YOLO Models on FPGA Devices. ICFPT 2023: 179-187 - [c104]Guoxuan Xia, Christos-Savvas Bouganis:
Window-Based Early-Exit Cascades for Uncertainty Estimation: When Deep Ensembles are More Efficient than Single Models. ICCV 2023: 17322-17334 - [c103]Zhewen Yu, Christos-Savvas Bouganis:
SVD-NAS: Coupling Low-Rank Approximation and Neural Architecture Search. WACV 2023: 1503-1512 - [i31]Guoxuan Xia, Christos-Savvas Bouganis:
Window-Based Early-Exit Cascades for Uncertainty Estimation: When Deep Ensembles are More Efficient than Single Models. CoRR abs/2303.08010 (2023) - [i30]Petros Toupas, Alexander Montgomerie-Corcoran, Christos-Savvas Bouganis, Dimitrios Tzovaras:
HARFLOW3D: A Latency-Oriented 3D-CNN Accelerator Toolflow for HAR on FPGA Devices. CoRR abs/2303.17218 (2023) - [i29]Benjamin Biggs, Christos-Savvas Bouganis, George A. Constantinides:
ATHEENA: A Toolflow for Hardware Early-Exit Network Automation. CoRR abs/2304.08400 (2023) - [i28]Petros Toupas, Christos-Savvas Bouganis, Dimitrios Tzovaras:
FMM-X3D: FPGA-based modeling and mapping of X3D for Human Action Recognition. CoRR abs/2305.18479 (2023) - [i27]Petros Toupas, Christos-Savvas Bouganis, Dimitrios Tzovaras:
fpgaHART: A toolflow for throughput-oriented acceleration of 3D CNNs for HAR onto FPGAs. CoRR abs/2305.19896 (2023) - [i26]Zhewen Yu, Christos-Savvas Bouganis:
Mixed-TD: Efficient Neural Network Accelerator with Layer-Specific Tensor Decomposition. CoRR abs/2306.05021 (2023) - [i25]Alexander Montgomerie-Corcoran, Zhewen Yu, Jianyi Cheng, Christos-Savvas Bouganis:
PASS: Exploiting Post-Activation Sparsity in Streaming Architectures for CNN Acceleration. CoRR abs/2307.07821 (2023) - [i24]Jianyi Cheng, Cheng Zhang, Zhewen Yu, Alexander Montgomerie-Corcoran, Can Xiao, Christos-Savvas Bouganis, Yiren Zhao:
Fast Prototyping Next-Generation Accelerators for New ML Models using MASE: ML Accelerator System Exploration. CoRR abs/2307.15517 (2023) - [i23]Alexander Montgomerie-Corcoran, Petros Toupas, Zhewen Yu, Christos-Savvas Bouganis:
SATAY: A Streaming Architecture Toolflow for Accelerating YOLO Models on FPGA Devices. CoRR abs/2309.01587 (2023) - [i22]Zhewen Yu, Christos-Savvas Bouganis:
AutoWS: Automate Weights Streaming in Layer-wise Pipelined DNN Accelerators. CoRR abs/2311.04764 (2023) - 2022
- [j33]Nur Ahmadi, Trio Adiono, Ayu Purwarianti, Timothy G. Constandinou, Christos-Savvas Bouganis:
Improved Spike-Based Brain-Machine Interface Using Bayesian Adaptive Kernel Smoother and Deep Learning. IEEE Access 10: 29341-29356 (2022) - [c102]Guoxuan Xia, Christos-Savvas Bouganis:
Augmenting Softmax Information for Selective Classification with Out-of-Distribution Data. ACCV (6) 2022: 664-680 - [c101]Alexander Montgomerie-Corcoran, Zhewen Yu, Christos-Savvas Bouganis:
SAMO: Optimised Mapping of Convolutional Neural Networks to Streaming Architectures. FPL 2022: 418-424 - [c100]Sina Boroumand, Christos-Savvas Bouganis, George A. Constantinides:
MIDAS: Mutual Information Driven Approximate Synthesis. ISVLSI 2022: 50-55 - [c99]Georgios Zampokas, Christos-Savvas Bouganis, Dimitrios Tzovaras:
Pushing the Efficiency of StereoNet: Exploiting Spatial Sparsity. VISIGRAPP (5: VISAPP) 2022: 757-766 - [i21]Aditya Rajagopal, Christos-Savvas Bouganis:
Low-Cost On-device Partial Domain Adaptation (LoCO-PDA): Enabling efficient CNN retraining on edge devices. CoRR abs/2203.00772 (2022) - [i20]Stylianos I. Venieris, Christos-Savvas Bouganis, Nicholas D. Lane:
Multi-DNN Accelerators for Next-Generation AI Systems. CoRR abs/2205.09376 (2022) - [i19]Guoxuan Xia, Christos-Savvas Bouganis:
Augmenting Softmax Information for Selective Classification with Out-of-Distribution Data. CoRR abs/2207.07506 (2022) - [i18]Guoxuan Xia, Christos-Savvas Bouganis:
On the Usefulness of Deep Ensemble Diversity for Out-of-Distribution Detection. CoRR abs/2207.07517 (2022) - [i17]Zhewen Yu, Christos-Savvas Bouganis:
SVD-NAS: Coupling Low-Rank Approximation and Neural Architecture Search. CoRR abs/2208.10404 (2022) - 2021
- [j32]Vanderlei Bonato, Christos-Savvas Bouganis:
Class-specific early exit design methodology for convolutional neural networks. Appl. Soft Comput. 107: 107316 (2021) - [j31]Leandro de Souza Rosa, Christos-Savvas Bouganis, Vanderlei Bonato:
Non-iterative SDC modulo scheduling for high-level synthesis. Microprocess. Microsystems 86: 104334 (2021) - [c98]Sina Boroumand, Christos-Savvas Bouganis, George A. Constantinides:
Learning Boolean Circuits from Examples for Approximate Logic Synthesis. ASP-DAC 2021: 524-529 - [c97]Alexander Montgomerie-Corcoran, Christos-Savvas Bouganis:
DEF: Differential Encoding of Featuremaps for Low Power Convolutional Neural Network Accelerators. ASP-DAC 2021: 703-708 - [c96]Alexander Montgomerie-Corcoran, Christos-Savvas Bouganis:
POMMEL: Exploring Off-Chip Memory Energy & Power Consumption in Convolutional Neural Network Accelerators. DSD 2021: 442-448 - [c95]Zhewen Yu, Christos-Savvas Bouganis:
StreamSVD: Low-rank Approximation and Streaming Accelerator Co-design. FPT 2021: 1-9 - [c94]Aditya Rajagopal, Christos-Savvas Bouganis:
perf4sight: A toolflow to model CNN training performance on Edge GPUs. ICCVW 2021: 963-971 - [i16]Panagiotis Miliadis, Christos-Savvas Bouganis, Dionisios N. Pnevmatikatos:
Performance landscape of resource-constrained platforms targeting DNNs. CoRR abs/2107.10047 (2021) - [i15]Aditya Rajagopal, Christos-Savvas Bouganis:
perf4sight: A toolflow to model CNN training performance on Edge GPUs. CoRR abs/2108.05580 (2021) - [i14]Alexander Montgomerie-Corcoran, Zhewen Yu, Christos-Savvas Bouganis:
SAMO: Optimised Mapping of Convolutional Neural Networks to Streaming Architectures. CoRR abs/2112.00170 (2021) - 2020
- [j30]Alexandros Kouris, Stylianos I. Venieris, Michail Rizakis, Christos-Savvas Bouganis:
Approximate LSTMs for Time-Constrained Inference: Enabling Fast Reaction in Self-Driving Cars. IEEE Consumer Electron. Mag. 9(4): 11-26 (2020) - [j29]Jon Olaizola, Christos-Savvas Bouganis, Eneko Sáenz de Argandoña, Aitzol Iturrospe, José Manuel Abete:
Real-Time Servo Press Force Estimation Based on Dual Particle Filter. IEEE Trans. Ind. Electron. 67(5): 4088-4097 (2020) - [c93]Zhewen Yu, Christos-Savvas Bouganis:
A Parameterisable FPGA-Tailored Architecture for YOLOv3-Tiny. ARC 2020: 330-344 - [c92]Aditya Rajagopal, Christos-Savvas Bouganis:
Now that I can see, I can improve: Enabling data-driven finetuning of CNNs on the edge. CVPR Workshops 2020: 3058-3067 - [c91]Alexandros Kouris, Stylianos I. Venieris, Christos-Savvas Bouganis:
A Throughput-Latency Co-Optimised Cascade of Convolutional Neural Network Classifiers. DATE 2020: 1656-1661 - [c90]Diederik Adriaan Vink, Aditya Rajagopal, Stylianos I. Venieris, Christos-Savvas Bouganis:
Caffe Barista: Brewing Caffe with FPGAs in the Training Loop. FPL 2020: 317-322 - [c89]Stefano Ribes, Pedro Trancoso, Ioannis Sourdis, Christos-Savvas Bouganis:
Mapping Multiple LSTM models on FPGAs. FPT 2020: 1-9 - [c88]Aditya Rajagopal, Diederik Adriaan Vink, Stylianos I. Venieris, Christos-Savvas Bouganis:
Multi-Precision Policy Enforced Training (MuPPET) : A Precision-Switching Strategy for Quantised Fixed-Point Training of CNNs. ICML 2020: 7943-7952 - [i13]Aditya Rajagopal, Christos-Savvas Bouganis:
Now that I can see, I can improve: Enabling data-driven finetuning of CNNs on the edge. CoRR abs/2006.08554 (2020) - [i12]Aditya Rajagopal, Diederik Adriaan Vink, Stylianos I. Venieris, Christos-Savvas Bouganis:
Multi-Precision Policy Enforced Training (MuPPET): A precision-switching strategy for quantised fixed-point training of CNNs. CoRR abs/2006.09049 (2020) - [i11]Diederik Adriaan Vink, Aditya Rajagopal, Stylianos I. Venieris, Christos-Savvas Bouganis:
Caffe Barista: Brewing Caffe with FPGAs in the Training Loop. CoRR abs/2006.13829 (2020)
2010 – 2019
- 2019
- [j28]Manolis Vasileiadis, Christos-Savvas Bouganis, Dimitrios Tzovaras:
Multi-person 3D pose estimation from 3D cloud data using 3D convolutional neural networks. Comput. Vis. Image Underst. 185: 12-23 (2019) - [j27]Ioannis Kostavelis, Manolis Vasileiadis, Evangelos Skartados, Andreas Kargakos, Dimitrios Giakoumis, Christos-Savvas Bouganis, Dimitrios Tzovaras:
Understanding of Human Behavior with a Robotic Agent Through Daily Activity Analysis. Int. J. Soc. Robotics 11(3): 437-462 (2019) - [j26]Jianxiong Liu, Christos Bouganis, Peter Y. K. Cheung:
Context-based image acquisition from memory in digital systems. J. Real Time Image Process. 16(4): 1057-1076 (2019) - [j25]Leandro de Souza Rosa, Christos-Savvas Bouganis, Vanderlei Bonato:
Scaling Up Modulo Scheduling for High-Level Synthesis. IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. 38(5): 912-925 (2019) - [j24]Stylianos I. Venieris, Christos-Savvas Bouganis:
fpgaConvNet: Mapping Regular and Irregular Convolutional Neural Networks on FPGAs. IEEE Trans. Neural Networks Learn. Syst. 30(2): 326-342 (2019) - [c87]Konstantinos Boikos, Christos-Savvas Bouganis:
A Scalable FPGA-Based Architecture for Depth Estimation in SLAM. ARC 2019: 181-196 - [c86]Nur Ahmadi, Timothy G. Constandinou, Christos-Savvas Bouganis:
End-to-End Hand Kinematic Decoding from LFPs Using Temporal Convolutional Network. BioCAS 2019: 1-4 - [c85]Manolis Vasileiadis, Christos-Savvas Bouganis, Georgios Stavropoulos, Dimitrios Tzovaras:
Optimising 3D-CNN Design towards Human Pose Estimation on Low Power Devices. BMVC 2019: 42 - [c84]Ameer M. S. Abdelhadi, Christos-Savvas Bouganis, George A. Constantinides:
Accelerated Approximate Nearest Neighbors Search Through Hierarchical Product Quantization. FPT 2019: 90-98 - [c83]Alexander Montgomerie-Corcoran, Stylianos I. Venieris, Christos-Savvas Bouganis:
Power-Aware FPGA Mapping of Convolutional Neural Networks. FPT 2019: 327-330 - [c82]Alexandros Kouris, Christos Kyrkou, Christos-Savvas Bouganis:
Informed Region Selection for Efficient UAV-based Object Detectors: Altitude-aware Vehicle Detection with CyCAR Dataset. IROS 2019: 51-58 - [c81]Alexandros Kouris, Stylianos I. Venieris, Christos-Savvas Bouganis:
Towards Efficient On-Board Deployment of DNNs on Intelligent Autonomous Systems. ISVLSI 2019: 568-573 - [c80]Nur Ahmadi, Timothy G. Constandinou, Christos-Savvas Bouganis:
Decoding Hand Kinematics from Local Field Potentials Using Long Short-Term Memory (LSTM) Network. NER 2019: 415-419 - [c79]Nur Ahmadi, Matthew L. Cavuto, Peilong Feng, Lieuwe B. Leene, Michal Maslik, Federico Mazza, Oscar Savolainen, Katarzyna M. Szostak, Christos-Savvas Bouganis, Jinendra Ekanayake, Andrew Jackson, Timothy G. Constandinou:
Towards a Distributed, Chronically-Implantable Neural Interface. NER 2019: 719-724 - [e3]Ioannis Sourdis, Christos-Savvas Bouganis, Carlos Álvarez, Leonel Antonio Toledo Díaz, Pedro Valero-Lara, Xavier Martorell:
29th International Conference on Field Programmable Logic and Applications, FPL 2019, Barcelona, Spain, September 8-12, 2019. IEEE 2019, ISBN 978-1-7281-4884-7 [contents] - [i10]Konstantinos Boikos, Christos-Savvas Bouganis:
A Scalable FPGA-based Architecture for Depth Estimation in SLAM. CoRR abs/1902.04907 (2019) - [i9]Alexandros Kouris, Stylianos I. Venieris, Michail Rizakis, Christos-Savvas Bouganis:
Approximate LSTMs for Time-Constrained Inference: Enabling Fast Reaction in Self-Driving Cars. CoRR abs/1905.00689 (2019) - 2018
- [j23]Stylianos I. Venieris, Alexandros Kouris, Christos-Savvas Bouganis:
Toolflows for Mapping Convolutional Neural Networks on FPGAs: A Survey and Future Directions. ACM Comput. Surv. 51(3): 56:1-56:39 (2018) - [j22]Christos Kyrkou, Theocharis Theocharides, Christos-Savvas Bouganis, Marios M. Polycarpou:
Boosting the Hardware-Efficiency of Cascade Support Vector Machines for Embedded Classification Applications. Int. J. Parallel Program. 46(6): 1220-1246 (2018) - [c78]Michalis Rizakis, Stylianos I. Venieris, Alexandros Kouris, Christos-Savvas Bouganis:
Approximate FPGA-Based LSTMs Under Computation Time Constraints. ARC 2018: 3-15 - [c77]Muhammad Shafique, Theocharis Theocharides, Christos-Savvas Bouganis, Muhammad Abdullah Hanif, Faiq Khalid, Rehan Hafiz, Semeen Rehman:
An overview of next-generation architectures for machine learning: Roadmap, opportunities and challenges in the IoT era. DATE 2018: 827-832 - [c76]Christos Kyrkou, George Plastiras, Theocharis Theocharides, Stylianos I. Venieris, Christos-Savvas Bouganis:
DroNet: Efficient convolutional neural network detector for real-time UAV applications. DATE 2018: 967-972 - [c75]Nur Ahmadi, Timothy G. Constandinou, Christos-Savvas Bouganis:
Spike Rate Estimation Using Bayesian Adaptive Kernel Smoother (BAKS) and Its Application to Brain Machine Interfaces. EMBC 2018: 2547-2550 - [c74]Alexandros Kouris, Stylianos I. Venieris, Christos-Savvas Bouganis:
Cascade^CNN: Pushing the Performance Limits of Quantisation in Convolutional Neural Networks. FPL 2018: 155-162 - [c73]Stylianos I. Venieris, Christos-Savvas Bouganis:
f-CNNx: A Toolflow for Mapping Multiple Convolutional Neural Networks on FPGAs. FPL 2018: 381-388 - [c72]Leandro de Souza Rosa, Vanderlei Bonato, Christos-Savvas Bouganis:
Scaling Up Loop Pipelining for High-Level Synthesis: A Non-iterative Approach. FPT 2018: 62-69 - [c71]Alexandros Kouris, Christos-Savvas Bouganis:
Learning to Fly by MySelf: A Self-Supervised CNN-Based Approach for Autonomous Navigation. IROS 2018: 1-9 - [i8]Michalis Rizakis, Stylianos I. Venieris, Alexandros Kouris, Christos-Savvas Bouganis:
Approximate FPGA-based LSTMs under Computation Time Constraints. CoRR abs/1801.02190 (2018) - [i7]Stylianos I. Venieris, Alexandros Kouris, Christos-Savvas Bouganis:
Toolflows for Mapping Convolutional Neural Networks on FPGAs: A Survey and Future Directions. CoRR abs/1803.05900 (2018) - [i6]Alexandros Kouris, Stylianos I. Venieris, Christos-Savvas Bouganis:
CascadeCNN: Pushing the performance limits of quantisation. CoRR abs/1805.08743 (2018) - [i5]Stylianos I. Venieris, Christos-Savvas Bouganis:
f-CNNx: A Toolflow for Mapping Multiple Convolutional Neural Networks on FPGAs. CoRR abs/1805.10174 (2018) - [i4]Stylianos I. Venieris, Alexandros Kouris, Christos-Savvas Bouganis:
Deploying Deep Neural Networks in the Embedded Space. CoRR abs/1806.08616 (2018) - [i3]Alexandros Kouris, Stylianos I. Venieris, Christos-Savvas Bouganis:
CascadeCNN: Pushing the Performance Limits of Quantisation in Convolutional Neural Networks. CoRR abs/1807.05053 (2018) - [i2]Christos Kyrkou, George Plastiras, Stylianos I. Venieris, Theocharis Theocharides, Christos-Savvas Bouganis:
DroNet: Efficient convolutional neural network detector for real-time UAV applications. CoRR abs/1807.06789 (2018) - 2017
- [j21]Grigorios Mingas, Leonardo Bottolo, Christos-Savvas Bouganis:
Particle MCMC algorithms and architectures for accelerating inference in state-space models. Int. J. Approx. Reason. 83: 413-433 (2017) - [j20]Christos-Savvas Bouganis, Marek Gorgon, Vanderlei Bonato:
Special issue on applied reconfigurable computing. Microprocess. Microsystems 52: 1 (2017) - [j19]Shuanglong Liu, Grigorios Mingas, Christos-Savvas Bouganis:
An Unbiased MCMC FPGA-Based Accelerator in the Land of Custom Precision Arithmetic. IEEE Trans. Computers 66(5): 745-758 (2017) - [c70]Shuanglong Liu, Christos-Savvas Bouganis:
Communication-Aware MCMC Method for Big Data Applications on FPGAs. FCCM 2017: 9-16 - [c69]Stylianos I. Venieris, Christos-Savvas Bouganis:
fpgaConvNet: Automated Mapping of Convolutional Neural Networks on FPGAs (Abstract Only). FPGA 2017: 291-292 - [c68]Konstantinos Boikos, Christos-Savvas Bouganis:
A high-performance system-on-chip architecture for direct tracking for SLAM. FPL 2017: 1-7 - [c67]Stylianos I. Venieris, Christos-Savvas Bouganis:
Latency-driven design for FPGA-based convolutional neural networks. FPL 2017: 1-8 - [c66]Manolis Vasileiadis, Sotiris Malassiotis, Dimitrios Giakoumis, Christos-Savvas Bouganis, Dimitrios Tzovaras:
Robust Human Pose Tracking For Realistic Service Robot Applications. ICCV Workshops 2017: 1363-1372 - [i1]Stylianos I. Venieris, Christos-Savvas Bouganis:
fpgaConvNet: A Toolflow for Mapping Diverse Convolutional Neural Networks on Embedded FPGAs. CoRR abs/1711.08740 (2017) - 2016
- [j18]Grigorios Mingas, Christos-Savvas Bouganis:
Population-Based MCMC on Multi-Core CPUs, GPUs and FPGAs. IEEE Trans. Computers 65(4): 1283-1296 (2016) - [j17]Christos Kyrkou, Christos-Savvas Bouganis, Theocharis Theocharides, Marios M. Polycarpou:
Embedded Hardware-Efficient Real-Time Classification With Cascade Support Vector Machines. IEEE Trans. Neural Networks Learn. Syst. 27(1): 99-112 (2016) - [c65]Stylianos I. Venieris, Christos-Savvas Bouganis:
fpgaConvNet: A Framework for Mapping Convolutional Neural Networks on FPGAs. FCCM 2016: 40-47 - [c64]Konstantinos Boikos, Christos-Savvas Bouganis:
Semi-dense SLAM on an FPGA SoC. FPL 2016: 1-4 - [c63]Rui Policarpo Duarte, Christos-Savvas Bouganis:
Variation-Aware Optimisation for Reconfigurable Cyber-Physical Systems. DoCEIS 2016: 237-252 - [c62]Mudhar Bin Rabieah, Christos-Savvas Bouganis:
FPGASVM: A Framework for Accelerating Kernelized Support Vector Machine. BigMine 2016: 68-84 - [c61]Michail S. Vavouras, Christos-Savvas Bouganis:
Area-driven partial reconfiguration for SEU mitigation on SRAM-based FPGAs. ReConFig 2016: 1-6 - [c60]Michail S. Vavouras, Rui Policarpo Duarte, Antonino Armato, Christos-Savvas Bouganis:
A hybrid ASIC/FPGA fault-tolerant artificial pancreas. SAMOS 2016: 261-267 - [e2]Vanderlei Bonato, Christos Bouganis, Marek Gorgon:
Applied Reconfigurable Computing - 12th International Symposium, ARC 2016, Mangaratiba, RJ, Brazil, March 22-24, 2016, Proceedings. Lecture Notes in Computer Science 9625, Springer 2016, ISBN 978-3-319-30480-9 [contents] - 2015
- [j16]Neil Scicluna, Christos-Savvas Bouganis:
ARC 2014: A Multidimensional FPGA-Based Parallel DBSCAN Architecture. ACM Trans. Reconfigurable Technol. Syst. 9(1): 2:1-2:15 (2015) - [j15]Rui Policarpo Duarte, Christos-Savvas Bouganis:
ARC 2014 Over-Clocking KLT Designs on FPGAs under Process, Voltage, and Temperature Variation. ACM Trans. Reconfigurable Technol. Syst. 9(1): 7:1-7:17 (2015) - [c59]