Note Transcription using convolutional neural network (CNN) (2020)

As a researcher with experience in machine learning and computer vision, I recently developed a computer vision-based machine learning model that can classify musical notes from spectrogram images. This model was trained using Python, TensorFlow, and OpenCV, and it achieved an accuracy of 90% on the test dataset.

My work on this project involved a range of tasks, including collecting and preparing the training dataset, developing the machine learning model, training and evaluating the model, and implementing the model in a real-time application. I used a variety of techniques and algorithms to improve the performance of the model, including data augmentation, regularization, and hyperparameter optimization.

Overall, my work on this project demonstrates my expertise in machine learning and computer vision, and my ability to develop effective solutions to complex problems. I am confident that my skills and experience make me an ideal candidate for any organization that is looking to develop or improve its machine learning and computer vision capabilities.

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