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Explainable COVID-19 Detection

  • Deep Learning
  • Python

The “COVID-19 DETECTION USING CT SCAN” is an image processing project utilizing deep learning techniques for enhanced accuracy in diagnosing the novel coronavirus (SARS-CoV-2) based on chest radiographs and computed tomography (CT) scans. The proposed method addresses the limitations of traditional testing, primarily focusing on improving sensitivity and specificity. This study discusses the success of Convolutional Neural Networks (CNNs) in medical image analysis and suggests future work involving model refinement, exploration of additional imaging modalities, and clinical validations. The application of deep learning in COVID-19 detection shows promise for enhancing diagnostic efficiency in the ongoing global pandemic.

  • Computed Tomography
  • Convolutional Neural Networks
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Emotional Detection Using Deep Learning

  • Data Science
  • Deep Learning
  • Machine Learning
  • Python

Facial expression emotion recognition is an intuitive reflection of a person’s mental state, which contains rich emotional information, and is one of the most important forms of interpersonal communication. Facial expression emotion recognition does the task of classifying the expressions on facial images into various categories such as anger, fear, surprise, sadness, happiness and so on. It analyses facial expressions from both static images and videos in order to reveal information on one’s emotional state. FER analysis comprises three steps: a) face detection, b) facial expression detection, and c) expression classification to an emotional state. Emotion detection is based on the analysis of facial landmark positions (e.g. end of the nose, eyebrows). Furthermore, in videos, changes in those positions are also analysed, in order to identify contractions in a group of facial muscles.

  • Emotion Recognition
  • Facial Analysis
  • Video Emotion Analysis
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