Results 61 to 70 of about 21,150,821 (215)
Reducing Gender Bias in Word-Level Language Models with a Gender-Equalizing Loss Function [PDF]
Annual Meeting of the Association for Computational Linguistics, 2019 Gender bias exists in natural language datasets, which neural language models tend to learn, resulting in biased text generation. In this research, we propose a debiasing approach based on the loss function modification.
Yusu Qian, Urwa Muaz, Ben Zhang, J. Hyun
semanticscholar +1 more source
Vehicle-Damage-Detection Segmentation Algorithm Based on Improved Mask RCNN
IEEE Access, 2020 Traffic congestion due to vehicular accidents seriously affects normal travel, and accurate and effective mitigating measures and methods must be studied.
Qinghui Zhang +2 more
doaj +1 more source
A Fusion Method of Optical Image and SAR Image Based on Dense-UGAN and Gram–Schmidt Transformation
Remote Sensing, 2021 To solve the problems such as obvious speckle noise and serious spectral distortion when existing fusion methods are applied to the fusion of optical and SAR images, this paper proposes a fusion method for optical and SAR images based on Dense-UGAN and ...
Yingying Kong +3 more
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Weather Radar Echo Extrapolation Method Based on Deep Learning
Atmosphere, 2022 In order to forecast some high intensity and rapidly changing phenomena, such as thunderstorms, heavy rain, and hail within 2 h, and reduce the influence brought by destructive weathers, this paper proposes a weather radar echo extrapolation method based
Fugui Zhang, Can Lai, Wanjun Chen
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Applied Sciences, 2019 We propose a high-performance algorithm while using a promoted and modified form of the You Only Look Once (YOLO) model, which is based on the TensorFlow framework, to enhance the real-time monitoring of traffic-flow problems by an intelligent ...
Chang-Yu Cao +4 more
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Vehicle Re-Identification in Aerial Imagery Based on Normalized Virtual Softmax Loss
Applied Sciences, 2022 With the development and popularization of unmanned aerial vehicles (UAVs) and surveillance cameras, vehicle re-identification (ReID) task plays an important role in the field of urban safety.
Wenzuo Qiao, Wenjuan Ren, Liangjin Zhao
doaj +1 more source
Entropy, 2020 We consider selection of random predictors for a high-dimensional regression problem with a binary response for a general loss function. An important special case is when the binary model is semi-parametric and the response function is misspecified under
Mariusz Kubkowski, Jan Mielniczuk
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Approximating the Gradient of Cross-Entropy Loss Function
IEEE Access, 2020 A loss function has two crucial roles in training a conventional discriminant deep neural network (DNN): (i) it measures the goodness of classification and (ii) generates the gradients that drive the training of the network. In this paper, we approximate
Li Li, M. Doroslovački, M. Loew
semanticscholar +1 more source
Using Physics-Informed Neural Networks (PINNs) for Tumor Cell Growth Modeling
MathematicsThis paper presents a comprehensive investigation into the applicability and performance of two prominent growth models, namely, the Verhulst model and the Montroll model, in the context of modeling tumor cell growth dynamics.
José Alberto Rodrigues
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Developing Novel Robust Loss Functions-Based Classification Layers for DLLSTM Neural Networks
IEEE Access, 2023 In this paper, we suggest improving the performance of developed activation function-based Deep Learning Long Short-Term Memory (DLLSTM) structures by employing robust loss functions like Mean Absolute Error $(MAE)$ and Sum Squared Error $(SSE)$ to ...
Mohamad Abou Houran +5 more
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