Results 21 to 30 of about 368,302 (254)
Frontiers in Physics, 2021 For ensuring the safety and reliability of electronic equipment, it is a necessary task to detect the surface defects of the printed circuit board (PCB).
Siyu Xia +8 more
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AdaFocal: Calibration-Aware Adaptive Focal Loss
Advances in Neural Information Processing Systems 35, 2022 Published in NeurIPS 2022.
Arindam Ghosh +2 more
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Focal Loss for Dense Object Detection [PDF]
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2017 The highest accuracy object detectors to date are based on a two-stage approach popularized by R-CNN, where a classifier is applied to a sparse set of candidate object locations. In contrast, one-stage detectors that are applied over a regular, dense sampling of possible object locations have the potential to be faster and simpler, but have trailed the
Tsung-Yi Lin +4 more
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Diabetic Retinopathy Detection From Fundus Images Using Multi-Tasking Model With EfficientNet B5 [PDF]
ITM Web of Conferences, 2022 Diabetic Retinopathy (DR) is a common eye disease that affects over 3 million people annually. People with diabetes are more prone to suffer from Diabetic Retinopathy. This condition can cause blurring of vision and blindness.
Bhawarkar Yash +3 more
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Focal loss dense detector for vehicle surveillance [PDF]
2018 International Conference on Intelligent Systems and Computer Vision (ISCV), 2018 Deep learning has been widely recognized as a promising approach in different computer vision applications. Specifically, one-stage object detector and two-stage object detector are regarded as the most important two groups of Convolutional Neural Network based object detection methods.
Xiaoliang Wang 0003 +3 more
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Remote Sensing, 2021 Pine wilt disease (PWD) is a serious threat to pine forests. Combining unmanned aerial vehicle (UAV) images and deep learning (DL) techniques to identify infected pines is the most efficient method to determine the potential spread of PWD over a large ...
Lang Xia +7 more
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Nested Dilation Network (NDN) for Multi-Task Medical Image Segmentation
IEEE Access, 2019 The deep convolutional network has shown excellent performance in medical image analysis. However, almost all network variants are presented for one specific task, e.g., segment pancreas on computerized tomography (CT). In this paper, we propose a nested
Liansheng Wang +5 more
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Animals, 2023 The efficient detection and counting of pig populations is critical for the promotion of intelligent breeding. Traditional methods for pig detection and counting mainly rely on manual labor, which is either time-consuming and inefficient or lacks ...
Wangli Hao +6 more
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Sentiment Analysis of Review Text Based on BiGRU-Attention and Hybrid CNN
IEEE Access, 2021 Convolutional neural networks (CNN), recurrent neural networks (RNN), attention, and their variants are extensively applied in the sentiment analysis, and the effect of fusion model is expected to be better.
Qiannan Zhu, Xiaofan Jiang, Renzhen Ye
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CAPTCHA Recognition Method Based on CNN with Focal Loss [PDF]
Complexity, 2021 In order to distinguish between computers and humans, CAPTCHA is widely used in links such as website login and registration. The traditional CAPTCHA recognition method has poor recognition ability and robustness to different types of verification codes.
Zhong Wang 0008, Peibei Shi
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