记成蚂蚁
发表于 2025-3-23 10:36:56
Challenges of Deepfakes,mocratic processes. This paper delves into the multifaceted challenges posed by deepfakes, emphasizing their potential to mislead, manipulate, and disrupt various domains, including politics, national security, and public discourse. The study highlights the complexity of detecting deepfakes, which a
LAVA
发表于 2025-3-23 15:59:24
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破布
发表于 2025-3-23 21:21:39
Predicting Suicide Cases Using Deep Neural Network,, it is imperative to implement effective suicide prevention strategies. In this context, deep neural network (DNN) algorithms have gained prominence and are increasingly applied across various healthcare domains. In our research, we examined the efficacy of employing DNNs for predicting suicide att
表皮
发表于 2025-3-24 00:54:46
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anus928
发表于 2025-3-24 04:43:24
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habile
发表于 2025-3-24 10:14:31
,Deep Feature Discriminability as a Diagnostic Measure of Overfitting in CNN Models,anced Deep Learning architectures. In this study, we present a novel methodology that identifies and analyzes model overfitting by leveraging unsupervised clustering of the features extracted by CNNs. Our research demonstrates that overfitted models exhibit inadequate class discriminability within t
recession
发表于 2025-3-24 14:19:36
,A Meta-VAE for Multi-component Industrial Systems Generation,sign options, providing a cheaper and faster alternative to the trial and failure approaches. Thanks to the flexibility they offer, Deep Generative Models are gaining popularity amongst Generative Design technologies. However, developing and evaluating these models can be challenging. A notable gap
条街道往前推
发表于 2025-3-24 16:20:06
,Analysis of the Computational Complexity of Backpropagation and Neuroevolution,based on stochastic gradient descent, where a network of neurons alter their weights based on an error signal passed back from the output. The second algorithm, called neuroevolution, is based on the genetic algorithm. In it, many weight sets are ranked based on how well the network solves the probl
needle
发表于 2025-3-24 20:25:51
,Indoor Obstacle Avoidance System Design and Evaluation Using Deep Learning and SLAM-Based Approacheates the fusion of 2D LiDAR-based Simultaneous Localization and Mapping (SLAM) with a Rapidly Exploring Random Trees (RRT) algorithm for effective path planning. Furthermore, we propose an innovative and pioneering approach for obstacle avoidance based on deep learning. The deep learning model is tr
discord
发表于 2025-3-25 00:25:38
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