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Copy move forgeries are a type of digital retouching that takes place in the field of image modification. This type of retouching occurs when one element of a picture is replicated over to a different segment of the photograph. This is typically done in an effort to mask or cover up undesirable qualities of the photograph thus copy move forgeries are a form of image modification. When it comes to digital picture modalities, copy move forging is by far the most prevalent form of picture manipulation that may take place. This is mainly observed when certain elements or segments of the recorded file are duplicated in the recorded file. The identification and localization of forgeries is a prominent problem that has piqued the attention of scholars working in the field of digital forensics and continues to do so. The identification of photo forgery has previously been the subject of several methodologies and uncountable publications, all of which were created and published. An abridged description of the present methodology and approaches is provided in this document, along with a survey and condensed summaries of current research and successes, among other things.

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Gujarati character recognition has always been a field of study in need of improved techniques to reach a satisfactory degree of accuracy. This study developed a technique for predicting handwritten Gujarati numerals using various feature extraction and classification techniques. Deep learning models, including MobileNet, DenseNet, and NasNetMobile, are components of the feature extraction technique. XGBoost, Random Forest, Logistic Regression, Naive Bayes, Stochastic Gradient Descent, Decision Tree, and K-Nearest Neighbor are some of the techniques used to classify Gujarati numerals. This study used over 14,000 images of Gujarati numerals for an experiment and found significant outcomes.