Example: tourism industry
Convolutional Networks For Visual Recognition
Found 2 free book(s)Abstract arXiv:1411.4038v2 [cs.CV] 8 Mar 2015
arxiv.orgConvolutional networks are powerful visual models that yield hierarchies of features. We show that convolu-tional networks by themselves, trained end-to-end, pixels-to-pixels, exceed the state-of-the-art in semantic segmen-tation. Our key insight is to build “fully convolutional” networks that take input of arbitrary size and produce
Eyeriss: A Spatial Architecture for Energy-Efficient ...
people.csail.mit.edudeep convolutional neural networks (CNNs), can be attributed to its ability to achieve unprecedented accuracy for tasks ranging from object recognition [2–5] and detection [6, 7] to scene understanding [8]. These state-of-the-art CNNs [2– 5] are orders of magnitude larger than those used in the