engagement
发表于 2025-3-30 10:23:57
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Harness
发表于 2025-3-30 13:51:16
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不可比拟
发表于 2025-3-30 16:54:14
A CNN-Based Approach for Facial Emotion Detection,e input from the user and predicts the emotion from the given input image. Through this experiment, we are successful in demonstrating how CNN is an appropriate model for this task. Our work is beneficial in many applications such as lie detectors and student assessments to detect facial expressions
forager
发表于 2025-3-30 23:05:17
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Obstreperous
发表于 2025-3-31 04:44:35
Diversified Recommendation Generation Using Graph Convolution Neural Network,of the recommendation. In our proposed method, we cluster users’ nodes based on their dissimilarity, and further, their subgraph is used for their neighborhood-based representation learning using graph convolution neural network (GCN). The novelty of the work is the clustering for the user’s pre-tra
值得
发表于 2025-3-31 06:42:37
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insurrection
发表于 2025-3-31 10:00:41
Different Stages of Watermelon Diseases Detection Using Optimized CNN,e for true positives of 7%. The over-fitting issue is resolved in this study by contrasting two experiments. Different combinations of various hyperparameters make up each experiment. The initialization of the weights and the optimizer were the two key hyperparameters that were changed to enhance th
cumulative
发表于 2025-3-31 15:00:31
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问到了烧瓶
发表于 2025-3-31 20:24:28
Detection of Fraudulent Credit Card Transactions Using Deep Neural Network, under curve (AUC), and precision of 99.93%, 99.99%, and 99.89%, respectively. This technique was compared with various models such as Optimized LightGBM, Multilayer Perceptron (MLP), K-Nearest Neighbor (KNN) and Support Vector Machine (SVM).
antipsychotic
发表于 2025-4-1 00:39:43
Dignet: A Deep Learning-Based Efficient Digit Recognition System,nal methods. For handwritten digit recognition, the current study used a neural network using convolutions as a classifier, MNIST as a set of data with appropriate training and assessment criteria, and an ensemble model in combination with data augmentation technique. The approach achieves a level o