11/9/2023 0 Comments Neural network matlab courseTeams at UCLA built an advanced microscope that yields a high-dimensional data set used to train a deep learning application to accurately identify cancer cells. Medical Research: Cancer researchers are using deep learning to automatically detect cancer cells. In addition, deep learning is used to detect pedestrians, which helps decrease accidents.Īerospace and Defense: Deep learning is used to identify objects from satellites that locate areas of interest, and identify safe or unsafe zones for troops. When combined with clusters or cloud computing, this enables development teams to reduce training time for a deep learning network from weeks to hours or less.ĭeep learning applications are used in industries from automated driving to medical devices.Īutomated Driving: Automotive researchers are using deep learning to automatically detect objects such as stop signs and traffic lights. High-performance GPUs have a parallel architecture that is efficient for deep learning. Deep learning requires substantial computing power.For example, driverless car development requires millions of images and thousands of hours of video. Deep learning requires large amounts of labeled data.While deep learning was first theorized in the 1980s, there are two main reasons it has only recently become useful: Recent advances in deep learning have improved to the point where deep learning outperforms humans in some tasks like classifying objects in images. This helps consumer electronics meet user expectations, and it is crucial for safety-critical applications like driverless cars. Deep learning achieves recognition accuracy at higher levels than ever before. How does deep learning attain such impressive results?
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