和上面描述的一样,这部分就是一个卷积网络,目的就是得到一个仿射矩阵:\theta。 参考github(https://github.com/oarriaga/STN.keras)上的一份源码: locnet = MaxPool2D(pool_size=(2, 2))(image) locnet = Conv2D(20, (5, 5))(locnet) locnet = MaxPool2D(pool_size=(2, 2))(locnet) locnet =...
Lightweight CRNN for OCR (including handwritten text) with depthwise separable convolutions and spatial transformer module [keras+tf] ocrlstmspatial-transformer-networkhandwritten-text-recognitionkeras-tensorflowstnctc-lossmobilenetcrnncrnn-ocrhandwritten-character-recognition ...
The following core Python libraries are utilized: Keras 2.6, TensorFlow 2.6, Flask 2.2.2, Numpy 1.19.5, Request 2.28, Seaborn, and MatplotLib. Additionally, MS Excel is utilized to store both the raw and final human daily life activity data. Moreover, the specifications 11th Gen Intel(R) ...
We used the “he_normal” initialization method of Keras described in He et al.66, and an elastic net regularization setting L1 and L2 penalties to 1e-4 (the penalty value performing best on the test set compared with two other penalties: 1e-3 and 1e-5). Nucleus-based purity ...
Our model simulations were performed on Python 3.6, Tensorflow 1.15, Keras 2.1.5, Numpy 1.19, Pandas 0.25, etc. Framework Setting: The shallow spatial feature 𝑆𝑚×𝑚Sm×m has an m of 46, the shallow temporal feature 𝑇𝑝𝑛×𝑓𝑛Tpn×fn has a 𝑝𝑛pn of 85 and 𝑓...
The software platform is based on the Tensorflow 2.3.0, Keras 2.4.3, CUDA 10.1 and Python 3.6. Table 4. The network parameter setting of the proposed SFMMNet. 4.2. Experimental Parameters Discussion 4.2.1. Analysis of Different Ratios of the Training, Validation and Test Datasets To explore...
The model is developed based on Python 3.9.7, Tensorflow, and Keras 2.8.0. The selection range of hyper-parameter values for both datasets is determined through extensive experiments in order to produce the optimal results for the evaluation metrics. Hangzhou Metro System: To optimize all metrics...
In addition, the software platform is based on TensorFlow 2.3.0, Keras 2.4.3, CUDA 10.1 and Python 3.6. To analyze the classification effect of the proposed method, four commonly used evaluation indicators are adopted: the accuracy of each category, the overall accuracy (OA), the average ...
All experiments are implemented with an NVIDIA 1060 GPU and a Titan graphics card server, Tensorflow-gpu and Keras with Python 3.6. 4.1. Experimental Data The experiments were conducted on four standard HSIs data sets, including two popular data sets and two contest data sets, that are, ...
All the models are implemented using Keras, which is based on TensorFlow as its backend engine, and optimized via Adam to perform all updated weights. Conventional network parameters are initialized using a uniform distribution with the default parameter. The batch size in our experiment is set to...