A three-dimensional magnetotelluric (MT) minimum structure inversion algorithm has been developed based on a data-space variant of the Occam approach. Comp... Weerachai Siripunvaraporn a,Gary Egbert b,Yongwimon Lenbury c,... - 《Physics of the Earth & Planetary Interiors》 被引量: 558发表:...
1 I have a problem gettingtensorflow-gpuworking. I use two CNN models, one for object detection and the second for classification. In project, i needopencv,keras,imageaiandtensorflowat the same time. I can't get them working all at the same time, because of all their dep...
i +=1 #This is the DQN algorithmimportosimportrandomimportnumpyasnpimporttensorflowastffromcollectionsimportdequefromskimage.colorimportrgb2grayfromskimage.transformimportresizefromkeras.modelsimportSequentialfromkeras.layersimportConv2D, Flatten, DensefromkerasimportbackendasK K.set_image_dim_ordering...
We illustrate partitioning using the PageRank algorithm as an example. Choosing the right partitioning for a distributed dataset is similar to choosing the right data structure for a local one—in both cases, data layout can greatly affect performance....
algorithm that calculates ratios—actually, one ratio divided by another. That gives you the R value. But, “when you take two numbers and divide them, you can get some strange effects when the denominator is noisy,” Patwari says. And one of the factors that can increase noisiness is ...
At the moment, the algorithm only works on constant bit rate video. Variable bit rate (VBR) video are considered but may be done in the future with proper programming language. Most (as in 99% of video) are constant bit rate video so VBR support is at least concern. ...
MaskRCNN EfficientDet UNet For these networks, the only task that can run multi-node training is train. To invoke multi-node training, simply add the --multi-node argument to the train command. For example, the multi-GPU training command given above can be issued as a multi-node command:...
The morphological feature vector and pixel set features of the bubble images are then fused for bubble image clustering using the weighted mean-shift algorithm. The frequencies of various types of bubbles in a froth image are calculated to form a bubble frequency set for the froth image. A two...
Users can easily implement their algorithm using quick gradient methods along with functionality of restoring the network (removing weights and excessive neurons, rearranging input data and uniting networks).Networks can be exported to the C functions to be able to be integrated into any program ...
Image algorithm: 3D reconstruction, system correction algorithm, iterative reconstruction, cone beam artifact correction method, CNN neurotic network identification algorithm such as hazardous and chemical products, conveyor speed control, energy spectrum imaging...