Results 31 to 40 of about 117,293 (275)
S-ResNet: An improved ResNet neural model capable of the identification of small insects
Frontiers in Plant Science, 2022 IntroductionPrecise identification of crop insects is a crucial aspect of intelligent plant protection. Recently, with the development of deep learning methods, the efficiency of insect recognition has been significantly improved. However, the recognition rate of existing models for small insect targets is still insufficient for insect early warning or
Pei Wang +10 more
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HeunNet: Extending ResNet using Heun’s Method
2021 32nd Irish Signals and Systems Conference (ISSC), 2021 Irish Signals & Systems Conference ...
Maleki, Mehrdad +2 more
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pFISTA-SENSE-ResNet for parallel MRI reconstruction [PDF]
Journal of Magnetic Resonance, 2020 Magnetic resonance imaging has been widely applied in clinical diagnosis, however, is limited by its long data acquisition time. Although imaging can be accelerated by sparse sampling and parallel imaging, achieving promising reconstruction images with a fast reconstruction speed remains a challenge.
Tieyuan Lu +10 more
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A pruning-then-quantization model compression framework for facial emotion recognition
Intelligent and Converged Networks, 2023 Facial emotion recognition achieves great success with the help of large neural models but also fails to be applied in practical situations due to the large model size of neural methods.
Han Sun +5 more
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Identity Mappings in Deep Residual Networks
, 2016 Deep residual networks have emerged as a family of extremely deep architectures showing compelling accuracy and nice convergence behaviors. In this paper, we analyze the propagation formulations behind the residual building blocks, which suggest that the
He, Kaiming +3 more
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, 2016 The Residual Network (ResNet), proposed in He et al. (2015), utilized shortcut connections to significantly reduce the difficulty of training, which resulted in great performance boosts in terms of both training and generalization error. It was empirically observed in He et al. (2015) that stacking more layers of residual blocks with shortcut 2 results
Li, Sihan +3 more
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Benchmark Analysis of Representative Deep Neural Network Architectures
, 2018 This work presents an in-depth analysis of the majority of the deep neural networks (DNNs) proposed in the state of the art for image recognition. For each DNN multiple performance indices are observed, such as recognition accuracy, model complexity ...
Bianco, Simone +3 more
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Speed/accuracy trade-offs for modern convolutional object detectors
, 2017 The goal of this paper is to serve as a guide for selecting a detection architecture that achieves the right speed/memory/accuracy balance for a given application and platform.
Fathi, Alireza +10 more
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Deep Residual Learning for Image Recognition
, 2015 Deeper neural networks are more difficult to train. We present a residual learning framework to ease the training of networks that are substantially deeper than those used previously.
He, Kaiming +3 more
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Adenoma Dysplasia Grading of Colorectal Polyps Using Fast Fourier Convolutional ResNet (FFC-ResNet)
IEEE Access, 2023 Colorectal polyps are precursor lesions of colorectal cancer; hence, early detection and dysplasia grading of polyps are essential for determining cancer risk, the possibility of developing subsequent polyps, and follow-up recommendations. The significant contribution of this study is the development of an enhanced deep-learning model called Fast ...
May Phu Paing, Chuchart Pintavirooj
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