* Add Squeezenet support in ONNX

* Add AlexNet support in ONNX

* Add Googlenet support in ONNX

* Add CaffeNet and RCNN support in ONNX

* Add VGG16 and VGG16 with batch normalization support in ONNX

* Add RCNN, ZFNet, ResNet18v1 and ResNet50v1 support in ONNX

* Add ResNet101_DUC_HDC

* Add Tiny Yolov2

* Add CNN_MNIST, MobileNetv2 and LResNet100 support in ONNX

* Add ONNX models for emotion recognition

* Add DenseNet121 support in ONNX

* Add Inception v1 support in ONNX

* Refactoring

* Fix tests

* Fix tests

* Skip unstable test

* Modify Reshape operation

* Remove a forward method in dnn::Layer

* Add a test

* Fix tests

* Mark multiple dnn::Layer::finalize methods as deprecated

* Replace back dnn's inputBlobs to vector of pointers

* Remove Layer::forward_fallback from CV_OCL_RUN scopes

* Include preprocessing nodes to object detection TensorFlow networks

* Enable more fusion

* faster_rcnn_resnet50_coco_2018_01_28 test

Multi-argument CV_Assert() is accessible via CV_Assert_N() (with malformed messages).

Enable Torch layers tests with Intel's Inference Engine backend.

Signed-off-by: NLi Peng <peng.li@intel.com>

set global size with real output size, also optimize

max pooling index computation if necessary.
Signed-off-by: NLi Peng <peng.li@intel.com>

to control DNN_BACKEND_DEFAULT enumeration value behavior

* Update Intel's Inference Engine deep learning backend

* Remove cpu_extension dependency

* Update Darknet accuracy tests

- eliminate rand() calls
- non initialized members/ variables
- unused return values
- missing/useless NULL checks

Signed-off-by: NLi Peng <peng.li@intel.com>

  * let OpenCL kernel run only on Intel GPU
  * brush up the workaround based on 9a2b028 from alalek

* Custom deep learning layers support

* Stack custom deep learning layers

Enable FP16 GPU target for DL Inference Engine backend.