In this paper, we challenge the conventional belief that supervised ImageNet-trained backbones have strong generalizability and are suitable for use as feature extractors in deepfake detection models. We present a new...
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ISBN:
(纸本)9798350337266
In this paper, we challenge the conventional belief that supervised ImageNet-trained backbones have strong generalizability and are suitable for use as feature extractors in deepfake detection models. We present a new measurement, "backbone separability," for visually and quantitatively assessing a backbone's raw capacity to separate data in an unsupervised manner. We also present a systematic benchmark for determining the correlation between deepfake detection and other computer vision tasks using backbones from pre-trained models. Our analysis shows that before fine-tuning, face recognition backbones are more closely related to deepfake detection than other backbones. Additionally, backbones trained using self-supervised methods are more effective in separating deepfakes than those trained using supervised methods. After fine-tuning all backbones on a small deepfake dataset, we found that self-supervised backbones deliver the best results, but there is a risk of overfitting. Our results provide valuable insights that should help researchers and practitioners develop more effective deepfake detection models.
The developed technology based on the GMDH was applied to solve the problem of choosing the best model that describes the dependence of the cooling temperature. The use of this technology increases the effectiveness o...
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In this work, the modeling and simulation of a mechatronic mechanism with the Arduino UNO board that ensures the security of a box of goods, through the virtual application TINKERCAD, was carried out. For the modeling...
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The multi-beam measurement system plays a crucial role in ocean mapping and underwater terrain detection. By simultaneously transmitting multiple beams, the system can accurately receive sound waves reflected from the...
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Hand gesture recognition is highly significant and a natural means of human-computer interaction. This detection is carried out by using the MPU- 6050 sensor, a widely available Inertial measurement Unit (IMU). MPU-60...
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This study presents a method for predicting the deformation of hydrogel models fabricated by four-dimensional printing technology using deep learning. In this method, a large number of hydrogel models with the same sh...
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As the functions of automobiles continue to increase and become more intelligent, the data exchange and communication between onboard electronic devices have become increasingly important. To ensure the reliability an...
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In the post-harvest stages of agricultural products, labor shortages and poor-quality control lead to significant market losses. The automated industries for agricultural products that use machine learning are evolvin...
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Mathematical modeling of surface water dynamics allows us to make forecasts of the hydrological regime of a territory for a wide variety of hydrological, environmental, and geophysical applications. The such simulatio...
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Smart farming technology allows farmers to control and analyse variables in real-time, helping them optimize crop growth and manage their operations more efficiently. The use of specialized sensors, data collection to...
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