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Convolutional Neural Networks: A Survey
Computers, 2023 Artificial intelligence (AI) has become a cornerstone of modern technology, revolutionizing industries from healthcare to finance. Convolutional neural networks (CNNs) are a subset of AI that have emerged as a powerful tool for various tasks including ...
Moez Krichen
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A Comprehensive Review on the Application of 3D Convolutional Neural Networks in Medical Imaging
Engineering Proceedings, 2023 Convolutional Neural Networks (CNNs) are kinds of deep learning models that were created primarily for processing and evaluating visual input, which makes them extremely applicable in the field of medical imaging.
Satyam Tiwari +5 more
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A Review of Convolutional Neural Networks for Inverse Problems in Imaging [PDF]
, 2017 In this survey paper, we review recent uses of convolution neural networks (CNNs) to solve inverse problems in imaging. It has recently become feasible to train deep CNNs on large databases of images, and they have shown outstanding performance on object
Jin, Kyong Hwan +2 more
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Proceedings of the 2021 Great Lakes Symposium on VLSI, 2021 Memory bandwidth utilization has become the key performance bottleneck for state-of-the-art variants of neural network kernels. Current structures such as depth-wise, point-wise and atrous convolutions have already introduced diverse and discontinuous memory access patterns, which impact efficient activation supply due to more frequent cache misses and
Zheng Wang +12 more
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Convolutional Neural Networks using FPGA-based Pipelining
Iraqi Journal for Computer Science and Mathematics, 2023 In order to speed up convolutional neural networks (CNNs), this study gives a complete overview of the use of FPGA-based pipelining for hardware acceleration of CNNs.
Gheni A. Ali, ahmed hussein ali
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Diagnostics, 2022 (1) Background: The present study aims to evaluate and compare the model performances of different convolutional neural networks (CNNs) used for classifying sagittal skeletal patterns.
Haizhen Li +4 more
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When Face Recognition Meets with Deep Learning: an Evaluation of Convolutional Neural Networks for Face Recognition [PDF]
, 2015 Deep learning, in particular Convolutional Neural Network (CNN), has achieved promising results in face recognition recently. However, it remains an open question: why CNNs work well and how to design a 'good' architecture.
Christmas, William +6 more
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P-CNN: Pose-Based CNN Features for Action Recognition [PDF]
2015 IEEE International Conference on Computer Vision (ICCV), 2015 ICCV, December 2015, Santiago ...
Chéron, Guilhem +2 more
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YodaNN: An Architecture for Ultra-Low Power Binary-Weight CNN Acceleration [PDF]
, 2017 Convolutional neural networks (CNNs) have revolutionized the world of computer vision over the last few years, pushing image classification beyond human accuracy.
Andri, Renzo +3 more
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Evaluation of the benchmark datasets for testing the efficacy of deep convolutional neural networks
Visual Informatics, 2021 In the past decade, deep neural networks, and specifically convolutional neural networks (CNNs), have been becoming a primary tool in the field of biomedical image analysis, and are used intensively in other fields such as object or face recognition ...
Sanchari Dhar, Lior Shamir
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