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Protective clothing 1860

Shanghai Sunland Industrial Co., Ltd is the top manufacturer of Personal Protect Equipment in China, with 20 years’experience. We are the Chinese government appointed manufacturer for government power,personal protection equipment , medical instruments,construction industry, etc. All the products get the CE, ANSI and related Industry Certificates. All our safety helmets use the top-quality raw material without any recycling material.

Why Choose Us
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Solutions to meet different needs

We provide exclusive customization of the products logo, using advanced printing technology and technology, not suitable for fading, solid and firm, scratch-proof and anti-smashing, and suitable for various scenes such as construction, mining, warehouse, inspection, etc. Our goal is to satisfy your needs. Demand, do your best.

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Highly specialized team and products

Professional team work and production line which can make nice quality in short time.

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We trade with an open mind

We abide by the privacy policy and human rights, follow the business order, do our utmost to provide you with a fair and secure trading environment, and look forward to your customers coming to cooperate with us, openly mind and trade with customers, promote common development, and work together for a win-win situation.

04
24 / 7 guaranteed service

The professional team provides 24 * 7 after-sales service for you, which can help you solve any problems

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Protective clothing 1860
Building a Recommender System Part 2
Building a Recommender System Part 2

The output of this block of code is two objects: prefs, which is a dataframe of preferences indexed by movieid and userid; and pref_matrix, which is a matrix whose th entry corresponds to the rating user gives movie (i.e. the columns are movies and each row is a user). In cases where the user hasn’t rated the item, this matrix will have a NaN.. The maximum and minimum preferences in this ...

Attention as Adaptive Tf-Idf for Deep Learning – Data ...
Attention as Adaptive Tf-Idf for Deep Learning – Data ...

22/7/2019, · 2.1 Without ,masking,. While the equations are straightforward, implementing attention in ,Keras, is a bit tricky. When ,masking, is not used – that is when every sentence has exactly the same number of words, it is a bit easier and we can implement it with the functional API.

Using Constant Padding Reflection Padding and Replication ...
Using Constant Padding Reflection Padding and Replication ...

10/2/2020, · Unfortunately, ,Keras, does not support this, as it only supports zero padding. That’s why the rest of this blog will introduce constant padding, reflection padding and replication padding to ,Keras,. The code below is compatible with TensorFlow 2.0 based ,Keras, and …

Mixed precision | TensorFlow Core
Mixed precision | TensorFlow Core

30/10/2020, · Mixed precision is the use of both 16-bit and 32-bit floating-point types in a model during training to make it run faster and use less memory. By keeping certain parts of the model in the 32-bit types for numeric stability, the model will have a lower step time and train equally as well in terms of ...

How to Perform Object Detection in Photographs Using Mask ...
How to Perform Object Detection in Photographs Using Mask ...

Most notably is the R-CNN, or Region-Based Convolutional Neural Networks, and the most recent ,technique, called ,Mask, R-CNN that is capable of achieving state-of-the-art results on a range of object detection tasks. ... The best-of-breed open source library implementation of the ,Mask, R-CNN for the ,Keras, deep learning library.

Keras Pose Estimation
Keras Pose Estimation

Image segmentation deep learning ,keras,. ,Mask, R-CNN is simple to train and adds only a small overhead to Faster R-CNN, running at 5 fps. , action recogni-tion, sports video analytics, surveillance, and human com-puter interaction. Precisely estimating the pose of objects is fundamental to many industries. , 2D images of humans annotated with 3D ...

Color Detection and Segmentation with OpenCV | Learn OpenCV
Color Detection and Segmentation with OpenCV | Learn OpenCV

The inRange function simply returns a binary ,mask,, where white pixels (255) represent pixels that fall into the upper and lower limit range and black pixels (0) do not. The Hue values are actually distributed over a circle (range between 0-360 degrees) but in OpenCV to fit into 8bit value the range is from 0-180.

[PDF] advanced deep learning with tensorflow 2 and keras eBook
[PDF] advanced deep learning with tensorflow 2 and keras eBook

Download Advanced Deep Learning With Tensorflow 2 And ,Keras, books, Updated and revised second edition of the bestselling guide to advanced deep learning with TensorFlow 2 and ,Keras, Key Features Explore the most advanced deep learning ,techniques, that drive modern AI results New coverage of unsupervised deep learning using mutual information, object detection, and semantic segmentation ...

Distributed training: TensorFlow and Keras models with ...
Distributed training: TensorFlow and Keras models with ...

22/10/2020, · CERN dist-,keras,. The CERN Database Group (indeed, the European Organization for Nuclear Research, which produced the Large Hadron Collider) created dist-,keras,, which can be used for distributed optimization of your ,Keras,-based deep learning model.In fact: Distributed ,Keras, is a distributed deep learning framework built op top of Apache Spark and ,Keras,, with a focus on “state-of …

Keras LSTM tutorial - How to easily build a powerful deep ...
Keras LSTM tutorial - How to easily build a powerful deep ...

In previous posts, I introduced ,Keras, for building convolutional neural networks and performing word embedding.The next natural step is to talk about implementing recurrent neural networks in ,Keras,. In a previous tutorial of mine, I gave a very comprehensive introduction to recurrent neural networks and long short term memory (LSTM) networks, implemented in TensorFlow.