Epileptic Seizures

• Tech Stack: Tensorflow, Python, numpy, keras, pandas
• Research Paper: Link
• Github URL: Project Link

This involves gathering the necessary datasets and preparing them for use in the study.

Various algorithms are applied to the data to evaluate their performance.

A new model(ESDCLN) is developed to improve detection accuracy. the model based on CNN and LSTM. While CNN can classify spatial features (like in images), when you have sequential data (e.g., a time series, video, or sensor data), simply classifying each timestep/frame individually might lose critical context. CNNs don't inherently understand how each timestep/frame is related to others, which can lead to suboptimal performance in tasks where order matters. CNN with LSTM: Powerful for tasks where you need both spatial and temporal information, such as video classification, time-series analysis, or any task involving sequential data. By using CNN with LSTM, combining the local feature extraction power of CNN with the memory capabilities of LSTM makes it especially useful for complex tasks with both spatial and temporal components.