Deep Learning Approach for COVID-19 Meme Categorization

Authors : S.Rajasree; R.Chinmaya; K.Dharsini Prabha; B. Indujapriya

Volume/Issue : Volume 6 - 2021, Issue 5 - May

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Meme is an image, which contains both text and images. Now-a-days memes are very popular and it becomes viral by sharing the memes in Instagram, Twitter and other social media. Some information from memes may be fake. By sharing the unwanted memes may harm others or may cause some other social issues. COVID-19 dataset has been considered for meme categorization in the proposed work. By classifying the memes, it is easy to find whether the meme is positive or negative or covid related. The dataset used for this project is memes from social media. The memes can be classified by using OCR technique and YOLO technique. Proposed methodology is Text Sentimental Analysis and Image Analysis to categorize the emotion of the memes related to COVID-19. YoloV5 is used for object detection and OCR Technique is used for Text extraction, LSTM is used for Sentimental Analysis from text. OCR is used to recognize and extract the text in the meme and yolov5 is used for object detection and label it. The proposed method can be evaluated using measures such as accuracy and precision.

Keywords : Covid-19 Memes, Text Analysis, Image Processing, Sentimental Analysis


Paper Submission Last Date
30 - September - 2021

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