Image classification with Loc-CAT using deep learning Another approach for classification of image patterns is machine learning. Toward this end, we used a deep neural network to create Loc-CAT.

The AttendSeg deep learning model performs semantic segmentation at an accuracy that is almost on-par with RefineNet while cutting down the number of parameters to 1.19 million.

Performance of DeciNets for image classification compared to other deep learning image classification models for Intel Cascade Lake CPUs. Image: Deci.

Deep learning, used to classify images, recognize voices and analyze video images, is emerging as the next big wave of artificial intelligence. Written by Joe McKendrick, Contributing Writer July ...

The Global Mapper Insight and Learning Engine™ (Beta) provides trained models for land cover classification, vehicle identification, and building extraction. This update to Global Mapper ...

Event details about Galvanize San Francisco: Intro to Deep Learning & Image Classification w/ Python, Keras, Tensorflow & AWS in San Francisco on June 6, 2018 - watch, listen, photos and tickets ...

The software supports CNN, DNN and KNN algorithms. The use of CNN and DNN are currently mainstream in the development of deep learning (DL) for ADC classification in the semiconductor industry. We ...