Wielding Neural Networks to Interpret Facial Emotions in Photographs with Fragmentary Occlusions

Fusion: Practice and Applications FPA 2692-4048 2770-0070 10.54216/FPA https://www.americaspg.com/journals/show/3107 2018 2018 Wielding Neural Networks to Interpret Facial Emotions in Photographs with Fragmentary Occlusions Senior Assistant Professor, Department of Computer Applications, V.R.Siddhartha Engineering College, Vijayawada, India K. K. Associate Professor, Dept. of CSE, Andhra Loyola Institute of Engineering and Technology, Vijayawada, India K. Sivarama Krishna Professor & Head,Department of CSD,KKR & KSR Institute of Technology and Sciences, Guntur, India Bhanu Prakash Battula Sr.Assistant Professor,Lakireddy Bali Reddy College of Engineering (A), Mylavaram, India Bajjuri Usha Rani Associate Professor, Dept. of Computer Science and Engineering, Koneru Lakshmaiah Education Foundation, Vaddeswaram Guntur, Andhra Pradesh, India P. V. V. S. Srinivas For many years, scientists have studied the way people express their emotions through body language and facial expressions. However, it is extremely difficult to accurately interpret the emotions of a person from just a single image. Interpreting facial emotions in photographs is a complex task. It is challenging to accurately detect facial emotions with the help of neural networks when the face is occluded with fragmentary blocks. With the advent of technology, emotion detection has become more accurate and reliable. It is now possible to use facial expression recognition in images to detect emotions such as happiness, sadness, anger, fear, surprise, and more. This research discusses the effectiveness of using neural networks to identify facial emotions in photographs with occlusions present. The datasets like Fer2013 dataset, CREMA-D and RAVDESS were used to train the model and the datasets were altered by implanting occlusions randomly in the images. The altered datasets were also used to evaluate the model. The challenges and opportunities that arise when neural networks are used in this context are explored. Additionally, insight is also provided into the best approach to accomplish the task. 2025 2025 146 158 10.54216/FPA.170111 https://www.americaspg.com/articleinfo/3/show/3107