The first interview in Melbourne

This algorithm has taught a lot about life. Brilliant algorithm indeed. The more parts of the algorithm I learn, the more I become intrigued. Looking forward to discovering more of it soon.

Faster R-CNN  논문명: Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks (2015) 저자: Shaoqing Ren, Kaiming He, Ross Girshick, and Jian Sun 요약 1. Fast R-CNN의 경우 Regional proposal을 만드는데 너무 많은 시간이 소요됨 - Selective search의 경우 이미지 당 2초가 소요됨. 따라서 Selective Search + Fast R-CNN 조합으로는 real-time analysis가 불가능 함 2. Region Proposal Networks (RPNs)을 통해 이미지당 10ms라는 속도로 proposal 추출 가능하며, RPN + Fast R-CNN 조합을 통해 이미지당 10%의 속도 (대략 198ms)로 구현 가능 함 3. 특히, RPN + Fast R-CNN의 경우 정확도(Accuracy) 또 기존의 Selective Search + Fast R-CNN 보다 더욱 높게 나타남. 즉, 정확도와 속도 모두를 향상 시킬 수 있는 방법 임.  Object proposal    - Grouping super-pixels:  Selective search 등    - Sliding windows: EdgeBoxes 등    - Object proposal은 외부 별도의 모듈로써 도입 되었음  Object detection    -  R-CNN    -  Bounding box 생성:         OverFeat, MultiBox, DeepMask   Faster R-CNN    - ...

#  Copyright 2016 The TensorFlow Authors. All Rights Reserved. # #  Licensed under the Apache License, Version 2.0 (the "License"); #  you may not use this file except in compliance with the License. #  You may obtain a copy of the License at # #   http://www.apache.org/licenses/LICENSE-2.0 # #  Unless required by applicable law or agreed to in writing, software #  distributed under the License is distributed on an "AS IS" BASIS, #  WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. #  See the License for the specific language governing permissions and #  limitations under the License. """Convolutional Neural Network Estimator for MNIST, built with tf.layers.""" from __future__ import absolute_import from __future__ import division from __future__ import print_function import numpy as np import tensorflow as tf tf.logging.set_verbosity(tf.logging.INFO) def cnn_model_fn(features, labels,...