Artículos de revistas sobre el tema "DNN architecture"
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Roorda, Esther, Seyedramin Rasoulinezhad, Philip H. W. Leong y Steven J. E. Wilton. "FPGA Architecture Exploration for DNN Acceleration". ACM Transactions on Reconfigurable Technology and Systems 15, n.º 3 (30 de septiembre de 2022): 1–37. http://dx.doi.org/10.1145/3503465.
Texto completoElola, Andoni, Elisabete Aramendi, Unai Irusta, Artzai Picón, Erik Alonso, Pamela Owens y Ahamed Idris. "Deep Neural Networks for ECG-Based Pulse Detection during Out-of-Hospital Cardiac Arrest". Entropy 21, n.º 3 (21 de marzo de 2019): 305. http://dx.doi.org/10.3390/e21030305.
Texto completoTran, Van Duy, Duc Khai Lam y Thi Hong Tran. "Hardware-Based Architecture for DNN Wireless Communication Models". Sensors 23, n.º 3 (23 de enero de 2023): 1302. http://dx.doi.org/10.3390/s23031302.
Texto completoTurner, Daniel, Pedro J. S. Cardoso y João M. F. Rodrigues. "Modular Dynamic Neural Network: A Continual Learning Architecture". Applied Sciences 11, n.º 24 (18 de diciembre de 2021): 12078. http://dx.doi.org/10.3390/app112412078.
Texto completoLee, Junghwan, Huanli Sun, Yuxia Liu, Xue Li, Yixin Liu y Myungjun Kim. "State-of-Health Estimation and Anomaly Detection in Li-Ion Batteries Based on a Novel Architecture with Machine Learning". Batteries 9, n.º 5 (8 de mayo de 2023): 264. http://dx.doi.org/10.3390/batteries9050264.
Texto completoMudgil, Pooja, Pooja Gupta, Iti Mathur y Nisheeth Joshi. "An ontological architecture for context data retrieval and ranking using SVM and DNN". Journal of Information and Optimization Sciences 44, n.º 3 (2023): 369–82. http://dx.doi.org/10.47974/jios-1347.
Texto completoElsisi, Mahmoud y Minh-Quang Tran. "Development of an IoT Architecture Based on a Deep Neural Network against Cyber Attacks for Automated Guided Vehicles". Sensors 21, n.º 24 (18 de diciembre de 2021): 8467. http://dx.doi.org/10.3390/s21248467.
Texto completoP, Shanmugavadivu, Mary Shanthi Rani M, Chitra P, Lakshmanan S, Nagaraja P y Vignesh U. "Bio-Optimization of Deep Learning Network Architectures". Security and Communication Networks 2022 (20 de septiembre de 2022): 1–11. http://dx.doi.org/10.1155/2022/3718340.
Texto completoKrishnan, Gokul, Sumit K. Mandal, Chaitali Chakrabarti, Jae-Sun Seo, Umit Y. Ogras y Yu Cao. "Impact of On-chip Interconnect on In-memory Acceleration of Deep Neural Networks". ACM Journal on Emerging Technologies in Computing Systems 18, n.º 2 (30 de abril de 2022): 1–22. http://dx.doi.org/10.1145/3460233.
Texto completoZhao, Jiaqi, Ming Xu, Yunzhi Chen y Guoliang Xu. "A DNN Architecture Generation Method for DDoS Detection via Genetic Alogrithm". Future Internet 15, n.º 4 (26 de marzo de 2023): 122. http://dx.doi.org/10.3390/fi15040122.
Texto completoKulkarni, Uday, Shreya B. Devagiri, Rohit B. Devaranavadagi, Sneha Pamali, Nishanth R. Negalli y V. Prabakaran. "Depth Estimation using DNN Architecture and Vision-Based Transformers". ITM Web of Conferences 53 (2023): 02010. http://dx.doi.org/10.1051/itmconf/20235302010.
Texto completoAspri, Maria, Grigorios Tsagkatakis y Panagiotis Tsakalides. "Distributed Training and Inference of Deep Learning Models for Multi-Modal Land Cover Classification". Remote Sensing 12, n.º 17 (19 de agosto de 2020): 2670. http://dx.doi.org/10.3390/rs12172670.
Texto completoShu, Deqin, Hao Fan y Liang Zhang. "Research on the Overview of Image Processing Architecture of Computer Based Deep Neural Network Accelerator". Journal of Physics: Conference Series 2074, n.º 1 (1 de noviembre de 2021): 012010. http://dx.doi.org/10.1088/1742-6596/2074/1/012010.
Texto completoTao, Zhe, Stephanie Nawas, Jacqueline Mitchell y Aditya V. Thakur. "Architecture-Preserving Provable Repair of Deep Neural Networks". Proceedings of the ACM on Programming Languages 7, PLDI (6 de junio de 2023): 443–67. http://dx.doi.org/10.1145/3591238.
Texto completoKapočiūtė-Dzikienė, Jurgita, Kaspars Balodis y Raivis Skadiņš. "Intent Detection Problem Solving via Automatic DNN Hyperparameter Optimization". Applied Sciences 10, n.º 21 (22 de octubre de 2020): 7426. http://dx.doi.org/10.3390/app10217426.
Texto completoLi, Guihong, Sumit K. Mandal, Umit Y. Ogras y Radu Marculescu. "FLASH: F ast Neura l A rchitecture S earch with H ardware Optimization". ACM Transactions on Embedded Computing Systems 20, n.º 5s (31 de octubre de 2021): 1–26. http://dx.doi.org/10.1145/3476994.
Texto completoSingh, Manu y Vibhakar Shrimali. "Classification of Brain Tumor using Hybrid Deep Learning Approach". BRAIN. Broad Research in Artificial Intelligence and Neuroscience 13, n.º 2 (30 de junio de 2022): 308–27. http://dx.doi.org/10.18662/brain/13.2/345.
Texto completoPandey, Pramesh, Noel Daniel Gundi, Prabal Basu, Tahmoures Shabanian, Mitchell Craig Patrick, Koushik Chakraborty y Sanghamitra Roy. "Challenges and Opportunities in Near-Threshold DNN Accelerators around Timing Errors". Journal of Low Power Electronics and Applications 10, n.º 4 (16 de octubre de 2020): 33. http://dx.doi.org/10.3390/jlpea10040033.
Texto completoGalitsky, Boris, Dmitry Ilvovsky y Saveli Goldberg. "Shaped-Charge Learning Architecture for the Human–Machine Teams". Entropy 25, n.º 6 (12 de junio de 2023): 924. http://dx.doi.org/10.3390/e25060924.
Texto completoGreif, Kevin y Kevin Lannon. "Physics Inspired Deep Neural Networks for Top Quark Reconstruction". EPJ Web of Conferences 245 (2020): 06029. http://dx.doi.org/10.1051/epjconf/202024506029.
Texto completoKanimozhi, G. y P. Shanmugavadivu. "OPTIMIZED DEEP NEURAL NETWORKS ARCHITECTURE MODEL FOR BREAST CANCER DIAGNOSIS". YMER Digital 20, n.º 11 (16 de noviembre de 2021): 161–75. http://dx.doi.org/10.37896/ymer20.11/15.
Texto completoKavitha, S. y J. Manikandan. "Design of a Bottleneck Layered DNN Algorithm for Intrusion Detection System". IRO Journal on Sustainable Wireless Systems 3, n.º 4 (16 de mayo de 2022): 242–58. http://dx.doi.org/10.36548/jsws.2021.4.004.
Texto completoMei, Linyan, Pouya Houshmand, Vikram Jain, Sebastian Giraldo y Marian Verhelst. "ZigZag: Enlarging Joint Architecture-Mapping Design Space Exploration for DNN Accelerators". IEEE Transactions on Computers 70, n.º 8 (1 de agosto de 2021): 1160–74. http://dx.doi.org/10.1109/tc.2021.3059962.
Texto completoShamasundar, Bharath y Ananthanarayanan Chockalingam. "A DNN Architecture for the Detection of Generalized Spatial Modulation Signals". IEEE Communications Letters 24, n.º 12 (diciembre de 2020): 2770–74. http://dx.doi.org/10.1109/lcomm.2020.3018260.
Texto completoLong, Yun, Daehyun Kim, Edward Lee, Priyabrata Saha, Burhan Ahmad Mudassar, Xueyuan She, Asif Islam Khan y Saibal Mukhopadhyay. "A Ferroelectric FET-Based Processing-in-Memory Architecture for DNN Acceleration". IEEE Journal on Exploratory Solid-State Computational Devices and Circuits 5, n.º 2 (diciembre de 2019): 113–22. http://dx.doi.org/10.1109/jxcdc.2019.2923745.
Texto completoYu, Ye, Yingmin Li, Shuai Che, Niraj K. Jha y Weifeng Zhang. "Software-Defined Design Space Exploration for an Efficient DNN Accelerator Architecture". IEEE Transactions on Computers 70, n.º 1 (1 de enero de 2021): 45–56. http://dx.doi.org/10.1109/tc.2020.2983694.
Texto completoKulkarni, Uday, Abhishek Patil, Rohit Devaranavadagi, Shreya B. Devagiri, Sneha K. Pamali y Raunak Ujawane. "Vision-Based Quality Control Check of Tube Shaft using DNN Architecture". ITM Web of Conferences 53 (2023): 02009. http://dx.doi.org/10.1051/itmconf/20235302009.
Texto completoZhou, Siqi, Mohamed K. Helwa y Angela P. Schoellig. "Deep neural networks as add-on modules for enhancing robot performance in impromptu trajectory tracking". International Journal of Robotics Research 39, n.º 12 (11 de septiembre de 2020): 1397–418. http://dx.doi.org/10.1177/0278364920953902.
Texto completoKao, Hsu-Yu, Shih-Hsu Huang y Wei-Kai Cheng. "Design Framework for ReRAM-Based DNN Accelerators with Accuracy and Hardware Evaluation". Electronics 11, n.º 13 (5 de julio de 2022): 2107. http://dx.doi.org/10.3390/electronics11132107.
Texto completoUto, Masaki. "A review of deep-neural automated essay scoring models". Behaviormetrika 48, n.º 2 (julio de 2021): 459–84. http://dx.doi.org/10.1007/s41237-021-00142-y.
Texto completoHosseini, Fateme S., Fanruo Meng, Chengmo Yang, Wujie Wen y Rosario Cammarota. "Tolerating Defects in Low-Power Neural Network Accelerators Via Retraining-Free Weight Approximation". ACM Transactions on Embedded Computing Systems 20, n.º 5s (31 de octubre de 2021): 1–21. http://dx.doi.org/10.1145/3477016.
Texto completoPham, Tuan Anh, Van Quan Tran y Huong-Lan Thi Vu. "Evolution of Deep Neural Network Architecture Using Particle Swarm Optimization to Improve the Performance in Determining the Friction Angle of Soil". Mathematical Problems in Engineering 2021 (7 de mayo de 2021): 1–17. http://dx.doi.org/10.1155/2021/5570945.
Texto completoAhmad, Zeeshan, Adnan Shahid Khan, Kashif Nisar, Iram Haider, Rosilah Hassan, Muhammad Reazul Haque, Seleviawati Tarmizi y Joel J. P. C. Rodrigues. "Anomaly Detection Using Deep Neural Network for IoT Architecture". Applied Sciences 11, n.º 15 (30 de julio de 2021): 7050. http://dx.doi.org/10.3390/app11157050.
Texto completoПаршин, А. И., М. Н. Аралов, В. Ф. Барабанов y Н. И. Гребенникова. "RANDOM MULTI-MODAL DEEP LEARNING IN THE PROBLEM OF IMAGE RECOGNITION". ВЕСТНИК ВОРОНЕЖСКОГО ГОСУДАРСТВЕННОГО ТЕХНИЧЕСКОГО УНИВЕРСИТЕТА, n.º 4 (20 de octubre de 2021): 21–26. http://dx.doi.org/10.36622/vstu.2021.17.4.003.
Texto completoQasrina Ann, Nurnajmin, Dwi Pebrianti, Mohd Fadhil Abas y Luhur Bayuaji. "Automated-tuned hyper-parameter deep neural network by using arithmetic optimization algorithm for Lorenz chaotic system". International Journal of Electrical and Computer Engineering (IJECE) 13, n.º 2 (1 de abril de 2023): 2167. http://dx.doi.org/10.11591/ijece.v13i2.pp2167-2176.
Texto completoCho, Hyungmin. "RiSA: A Reinforced Systolic Array for Depthwise Convolutions and Embedded Tensor Reshaping". ACM Transactions on Embedded Computing Systems 20, n.º 5s (31 de octubre de 2021): 1–20. http://dx.doi.org/10.1145/3476984.
Texto completoLei, Hong, Yue Xiao, Yanchun Liang, Dalin Li y Heow Pueh Lee. "DLD: An Optimized Chinese Speech Recognition Model Based on Deep Learning". Complexity 2022 (2 de mayo de 2022): 1–8. http://dx.doi.org/10.1155/2022/6927400.
Texto completoWang, Yi-Ren y Yi-Jyun Wang. "Flutter speed prediction by using deep learning". Advances in Mechanical Engineering 13, n.º 11 (noviembre de 2021): 168781402110622. http://dx.doi.org/10.1177/16878140211062275.
Texto completoPedram, Ardavan, Ali Shafie Ardestani, Ling Li, Hamzah Abdelaziz, Jun Fang y Joseph Hassoun. "Algorithm/architecture solutions to improve beyond uniform quantization in embedded DNN accelerators". Journal of Systems Architecture 126 (mayo de 2022): 102454. http://dx.doi.org/10.1016/j.sysarc.2022.102454.
Texto completoGowda, Kavitha Malali Vishveshwarappa, Sowmya Madhavan, Stefano Rinaldi, Parameshachari Bidare Divakarachari y Anitha Atmakur. "FPGA-Based Reconfigurable Convolutional Neural Network Accelerator Using Sparse and Convolutional Optimization". Electronics 11, n.º 10 (22 de mayo de 2022): 1653. http://dx.doi.org/10.3390/electronics11101653.
Texto completoNabavinejad, Seyed Morteza y Sherief Reda. "BayesTuner: Leveraging Bayesian Optimization For DNN Inference Configuration Selection". IEEE Computer Architecture Letters 20, n.º 2 (1 de julio de 2021): 166–70. http://dx.doi.org/10.1109/lca.2021.3123695.
Texto completoKwon, Hyoukjun, Michael Pellauer, Angshuman Parashar y Tushar Krishna. "Flexion: A Quantitative Metric for Flexibility in DNN Accelerators". IEEE Computer Architecture Letters 20, n.º 1 (1 de enero de 2021): 1–4. http://dx.doi.org/10.1109/lca.2020.3044607.
Texto completoAnahid Robert Safavi, Alberto G. Perotti, Branislav M. Popovic, Mahdi Boloursaz Mashhadi y Deniz G�nd�z. "Deep extended feedback codes". ITU Journal on Future and Evolving Technologies 2, n.º 6 (13 de septiembre de 2021): 33–41. http://dx.doi.org/10.52953/snlm1743.
Texto completoMateen, Muhammad, Junhao Wen, Nasrullah, Sun Song y Zhouping Huang. "Fundus Image Classification Using VGG-19 Architecture with PCA and SVD". Symmetry 11, n.º 1 (20 de diciembre de 2018): 1. http://dx.doi.org/10.3390/sym11010001.
Texto completoWang, Jihong, Hao Wang, Xiaodan Wang y Huiyou Chang. "Predicting Drug-target Interactions via FM-DNN Learning". Current Bioinformatics 15, n.º 1 (6 de febrero de 2020): 68–76. http://dx.doi.org/10.2174/1574893614666190227160538.
Texto completoZhang, Tunhou, Hsin-Pai Cheng, Zhenwen Li, Feng Yan, Chengyu Huang, Hai Li y Yiran Chen. "AutoShrink: A Topology-Aware NAS for Discovering Efficient Neural Architecture". Proceedings of the AAAI Conference on Artificial Intelligence 34, n.º 04 (3 de abril de 2020): 6829–36. http://dx.doi.org/10.1609/aaai.v34i04.6163.
Texto completoMunoz-Martinez, Francisco, Jose L. Abellan, Manuel E. Acacio y Tushar Krishna. "STONNE: Enabling Cycle-Level Microarchitectural Simulation for DNN Inference Accelerators". IEEE Computer Architecture Letters 20, n.º 2 (1 de julio de 2021): 122–25. http://dx.doi.org/10.1109/lca.2021.3097253.
Texto completoJang, Yongjoo, Sejin Kim, Daehoon Kim, Sungjin Lee y Jaeha Kung. "Deep Partitioned Training From Near-Storage Computing to DNN Accelerators". IEEE Computer Architecture Letters 20, n.º 1 (1 de enero de 2021): 70–73. http://dx.doi.org/10.1109/lca.2021.3081752.
Texto completoLin, Shaoxiong, Wangyou Zhang y Yanmin Qian. "Two-Stage Single-Channel Speech Enhancement with Multi-Frame Filtering". Applied Sciences 13, n.º 8 (14 de abril de 2023): 4926. http://dx.doi.org/10.3390/app13084926.
Texto completoXiao, Dongwei, Zhibo Liu, Yuanyuan Yuan, Qi Pang y Shuai Wang. "Metamorphic Testing of Deep Learning Compilers". ACM SIGMETRICS Performance Evaluation Review 50, n.º 1 (20 de junio de 2022): 65–66. http://dx.doi.org/10.1145/3547353.3522655.
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