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NTIS 바로가기Engineering applications of artificial intelligence, v.123 pt.A, 2023년, pp.106232 -
Zhang, Yufei , Xu, Hui , Huang, Lixing , Chen, Changlin
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Expert Syst. Appl. Affonso 42 24 9482 2015 10.1016/j.eswa.2015.07.075 Biological image classification using rough-fuzzy artificial neural network
IEEE J. Solid-State Circuits Brandli 49 10 2333 2014 10.1109/JSSC.2014.2342715 A 240× 180 130 db 3 μs latency global shutter spatiotemporal vision sensor
Sci. Rep. Chang 8 1 12324 2018 10.1038/s41598-018-30619-y Hybrid optical-electronic convolutional neural networks with optimized diffractive optics for image classification
IEEE Trans. Circuit Theory Chua 18 5 507 1971 10.1109/TCT.1971.1083337 Memristor-the missing circuit element
Courbariaux, M., Bengio, Y., David, J.P., 2015. BinaryConnect: Training Deep Neural Networks with binary weights during propagations. In: International Conference on Neural Information Processing Systems.
IEEE J. Solid-State Circuits Deng 55 8 2228 2020 10.1109/JSSC.2020.2970709 Tianjic: A unified and scalable chip bridging spike-based and continuous neural computation
IEEE Consum. Electron. Mag. Dong 2022 Memristor-based hierarchical attention network for multimodal affective computing in mental health monitoring
Sensors Furmonas 22 3 1201 2022 10.3390/s22031201 Analytical review of event-based camera depth estimation methods and systems
Transp. Res. Interdisc. Perspect. Gouribhatla 13 2022 Drivers’ behavior when driving vehicles with or without advanced driver assistance systems: A driver simulator-based study
Front. Neurosci. Huang 15 328 2021 10.3389/fnins.2021.639526 Memristor based binary convolutional neural network architecture with configurable neurons
Ivanov 2022 Neuromorphic artificial intelligence systems
Adv. Sci. Jang 9 22 2022 10.1002/advs.202201117 A learning-rate modulable and reliable TiOx memristor array for robust, fast, and accurate neuromorphic computing
10.1109/ICEIC51217.2021.9369724 Kwak, M., Lee, J., Seo, H., Sung, M., Kim, Y., 2021. Training and Inference using Approximate Floating-Point Arithmetic for Energy Efficient Spiking Neural Network Processors. In: 2021 International Conference on Electronics, Information, and Communication. ICEIC, pp. 1-2.
10.1109/ITC-CSCC52171.2021.9501427 Lee, K., Choi, S., Lew, D., Park, J., 2021. Optimization Techniques for Conversion of Quantization Aware Trained Deep Neural Networks to Lightweight Spiking Neural Networks. In: 2021 36th International Technical Conference on Circuits/Systems, Computers and Communications. ITC-CSCC, pp. 1-3.
Front. Neurosci. Lele 16 2022 10.3389/fnins.2022.1010302 Bio-mimetic high-speed target localization with fused frame and event vision for edge application
Li 2017 Traffic Sign Recognition Based on Combined CNN with Color and Hierarchical Dataset
Front. Neurosci. Li 1055 2022 Quantization framework for fast spiking neural networks
IEEE Trans. Cogn. Dev. Syst. Li PP 99 1 2021 In-situ learning in hardware compatible multi-layer memristive spiking neural network
ACS Appl. Mater. Interfaces Ma 14 42 47941 2022 10.1021/acsami.2c14809 Analog tunnel memory based on programmable metallization for passive neuromorphic circuits
Int. J. Transp. Sci. Technol. Megalingam 2022 Indian traffic sign detection and recognition using deep learning
Comput. Geosci. Ngo 83 1 2015 10.1016/j.cageo.2015.06.011 Semi-supervising interval type-2 fuzzy C-means clustering with spatial information for multi-spectral satellite image classification and change detection
IEEE Signal Process. Lett. Pei 20 3 241 2013 10.1109/LSP.2013.2241760 Supervised low-rank matrix recovery for traffic sign recognition in image sequences
Pattern Recognit. Qin 105 2020 10.1016/j.patcog.2020.107281 Binary neural networks: A survey
IEEE Trans. Neural Netw. Learn. Syst. Shen 1 2021 HybridSNN: Combining bio-machine strengths by boosting adaptive spiking neural networks
Shouyi 124 2020 Design of Artificial Intelligence Chip Chapter 8 - software and hardware co-design of artificial intelligence chip
Neural Netw. Stallkamp 32 323 2012 10.1016/j.neunet.2012.02.016 Man vs. computer: Benchmarking machine learning algorithms for traffic sign recognition
Sun 574 2018 2018 23rd Asia and South Pacific Design Automation Conference Fully parallel RRAM synaptic array for implementing binary neural network with (+ 1,- 1) weights and (+ 1, 0) neurons
Open Phys. Versaci 18 1 230 2020 10.1515/phys-2020-0159 Joint use of eddy current imaging and fuzzy similarities to assess the integrity of steel plates
Nature Wan 608 7923 504 2022 10.1038/s41586-022-04992-8 A compute-in-memory chip based on resistive random-access memory
IEEE Trans. Neural Netw. Learn. Syst. Wang 2022 Efficient spiking neural networks with radix encoding
Wang 255 2022 2022 IEEE Biomedical Circuits and Systems Conference MorphBungee: An edge neuromorphic chip for high-accuracy on-chip learning of multiple-layer spiking neural networks
Nat. Nanotechnol. Wedig 11 67 2016 10.1038/nnano.2015.221 Nanoscale cation motion in TaOx, HfOx and TiOx memristive systems
Int. J. Comput. Vis. Y. Cao 113 54 2015 10.1007/s11263-014-0788-3 Spiking deep convolutional neural networks for energy-efficient object recognition
Nature Yao 577 641 2020 10.1038/s41586-020-1942-4 Fully hardware-implemented memristor convolutional neural network
Heliyon Youssouf 8 12 2022 10.1016/j.heliyon.2022.e11792 Traffic sign classification using CNN and detection using faster-RCNN and YOLOV4
Zhao 2021 A battle of network structures: An empirical study of cnn, transformer, and mlp
Zhou 111 2022 Deep Learning on Edge Computing Devices Chapter 7 - algorithm and hardware codesign of sparse binary network on-chip
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