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SigScatNet: A Siamese + Scattering based Deep Learning Approach for Signature Forgery Detection and Similarity Assessment
This groundbreaking research paper introduces SigScatNet, an innovative solution to combat this issue by harnessing the potential of a Siamese deep learning network, bolstered by Scattering wavelets, to detect signature forgery and assess signature similarity.
L-WaveBlock: A Novel Feature Extractor Leveraging Wavelets for Generative Adversarial Networks
The proposed method performs competently to the state-of-the-art for the image denoising dataset, albeit not better, but still leads to faster convergence than conventional methods.
Advancing Diagnostic Precision: Leveraging Machine Learning Techniques for Accurate Detection of Covid-19, Pneumonia, and Tuberculosis in Chest X-Ray Images
Recall, precision, F1-score, and Area Under Curve (AUC) score are used to evaluate and compare the performance of the proposed model.
RoadScan: A Novel and Robust Transfer Learning Framework for Autonomous Pothole Detection in Roads
The network proposed in this model performs with a 96. 12 % accuracy, 3. 89 % EER, and a 0. 988 AUROC value, which is highly competitive with other state-of-the-art works.
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