News

Simon Fraser University6y
Architectures, Datasets, and Transfer Learning for CNN-based CAD | Pixels & Predictions - Simon Fraser University
As the title suggests, this paper studies various different deep convolutional neural network architectures and various techniques to use these CNNs for CADe (Computer Aided Detection) tasks. With the ...
Semiconductor Engineering8y
The Evolution Of Deep Learning For ADAS Applications - Semiconductor Engineering
As mentioned earlier, a CNN is not programmed. It is trained. A deep learning framework, like Caffe or TensorFlow, will use large data sets of images to train the CNN graph – refining coefficients ...
GIGAZINE5y
'CNN Explainer' that can understand the image identification process of deep learning method 'CNN' by animation - GIGAZINE（ギガジン）
CNN is a classifier in machine learning and is an algorithm used to identify patterns of data such as images and videos using neural networks. The basic components for understanding CNN are as ...
Semiconductor Engineering3d
Accelerator Architecture For In-Memory Computation of CNN Inferences Using Racetrack Memory
A new technical paper titled “Hardware-software co-exploration with racetrack memory based in-memory computing for CNN inference in embedded systems” was published by researchers at National ...
Columbia University School of Professional Studies9d
The Role of Deep Learning and AI in Disaster Management and Workplace Safety
Applied Analytics professor Siddhartha Dalal discusses the impacts of applied technologies on real-life risk management.