scholarly journals Research Progress of Deep Learning in the Diagnosis and Prevention of Stroke

2021 ◽  
Vol 2021 ◽  
pp. 1-5
Author(s):  
Siqi Zhang ◽  
Miao Zhang ◽  
Shuai Ma ◽  
Qingyong Wang ◽  
Youyang Qu ◽  
...  
Keyword(s):  
Deep Learning ◽  
Future Development ◽  
Relevant Literature ◽  
Research Progress ◽  
Learning Technology ◽  
Learning Techniques ◽  
The Future ◽  
Development Prospects

In order to evaluate the importance of deep learning techniques in stroke diseases, this paper systematically reviews the relevant literature. Deep learning techniques have a significant impact on the diagnosis, treatment, and prediction of stroke. In addition, this study also discusses the current bottlenecks and the future development prospects of deep learning technology.

INTELLECTUAL PROPERTY SECURITIZATION

2019 ◽  
pp. 42-48
Author(s):  
Angelina Ivanova
Keyword(s):  
Intellectual Property ◽  
Future Development ◽  
Legal Framework ◽  
Foreign Countries ◽  
The Future ◽  
Pros And Cons ◽  
Development Prospects

The article analyzes a legal framework for the intellectual property securitization based on experience of foreign countries. The structure of a securitization transaction is depicted, including the different players and tools in the securitization process. The concluding part summarizes the pros and cons of the funding instrument and the future development prospects

Research Status of Copper Foil Surface Treatment and Development of Novel Process

2017 ◽  
Vol 727 ◽  
pp. 43-51
Author(s):  
Wen Jing Wang ◽  
Xue Feng Liu
Keyword(s):  
Surface Treatment ◽  
Future Development ◽  
Copper Foil ◽  
Science Research ◽  
Research Progress ◽  
Foil Surface ◽  
Research Status ◽  
New Process ◽  
The Future ◽  
Brush Plating

Surface treated copper foil and its preparation is very important and widely used. The science research and enterprise competition always focus on the surface treated methods in the copper foil field. This paper summarized the typical surface treated processes of copper foil, and emphasized on research progress and problems of copper foil surface treated processes. The brush plating-dealloying treated process of copper foil was proposed based on the problems. The principle and research status of new process was introduced. At last, the future development of surface treated process and application prospect were forecast.

scholarly journals Share Market Prediction using Deep Neural Network

2019 ◽  
Vol 8 (3) ◽  
pp. 8619-8622
Keyword(s):  
Neural Network ◽  
Machine Learning ◽  
Deep Learning ◽  
Reinforcement Learning ◽  
Stock Market ◽  
Deep Neural Network ◽  
Learning Technology ◽  
Financial Investment ◽  
The Future ◽  
Future Prediction

People, due to their complexity and volatile actions, are constantly faced with challenges in understanding the situation in the market share and the forecast for the future. For any financial investment, the stock market is a very important aspect. It is necessary to study while understanding the price fluctuations of the stock market. In this paper, the stock market prediction model using the Recurrent Digital natural Network (RDNN) is described. The model is designed using two important machine learning concepts: the recurrent neural network (RNN), multilayer perceptron (MLP) and reinforcement learning (RL). Deep learning is used to automatically extract important functions of the stock market; reinforcement learning of these functions will be useful for future prediction of the stock market, the system uses historical stock market data to understand the dynamic market behavior when you make decisions in an unknown environment. In this paper, the understanding of the dynamic stock market and the deep learning technology for predicting the price of the future stock market are described.

scholarly journals Deep Learning for Visual SLAM in Transportation Robotics: A review

2019 ◽  
Vol 1 (3) ◽  
pp. 177-184
Author(s):  
Chao Duan ◽  
Steffen Junginger ◽  
Jiahao Huang ◽  
Kairong Jin ◽  
Kerstin Thurow
Keyword(s):  
Computer Vision ◽  
Deep Learning ◽  
Future Development ◽  
Research Progress ◽  
Visual Slam ◽  
Learning Methods ◽  
Research Results ◽  
The Past ◽  
Localization And Mapping ◽  
Challenging Environment

Abstract Visual SLAM (Simultaneously Localization and Mapping) is a solution to achieve localization and mapping of robots simultaneously. Significant achievements have been made during the past decades, geography-based methods are becoming more and more successful in dealing with static environments. However, they still cannot handle a challenging environment. With the great achievements of deep learning methods in the field of computer vision, there is a trend of applying deep learning methods to visual SLAM. In this paper, the latest research progress of deep learning applied to the field of visual SLAM is reviewed. The outstanding research results of deep learning visual odometry and deep learning loop closure detect are summarized. Finally, future development directions of visual SLAM based on deep learning is prospected.

scholarly journals A számítógépes mélytanulási technológia várható megjelenése a hazai mammográfiában

2019 ◽  
Vol 160 (4) ◽  
pp. 138-143
Author(s):  
Dezső Ribli ◽  
Richárd Zsuppán ◽  
Péter Pollner ◽  
Anna Horváth ◽  
Zoltán Bánsághi ◽  
...  
Keyword(s):  
Health Care ◽  
Deep Learning ◽  
Health Care Providers ◽  
Promising Result ◽  
Immune Therapy ◽  
Learning Technology ◽  
Care Providers ◽  
Doctor Visits ◽  
Learning Techniques ◽  
Great Mind

Abstract: Introduction and aim: The technology, named ‘deep learning’ is the promising result of the last two decades of development in computer science. It poses an unavoidable challenge for medicine, how to understand, apply and adopt the – today not fully explored – possibilities that have become available by these new methods. Method: It is a gift and a mission, since the exponentially growing volume of raw data (from imaging, laboratory, therapy diagnostics or therapy interactions, etc.) did not solve until now our wished and aimed goal to treat patients according to their personal status and setting or specific to their tumor and disease. Results: Currently, as a responsible health care provider and financier, we face the problem of supporting suboptimal procedures and protocols either at individual or at community level. The problem roots in the overwhelming amount of data and, at the same time, the lack of targeted information for treatment. We expect from the deep learning technology an aid which helps to reinforce and extend the human–human cooperations in patient–doctor visits. We expect that computers take over the tedious work allowing to revive the core of healing medicine: the insightful meeting and discussion between patients and medical experts. Conclusion: We should learn the revelational possibilities of deep learning techniques that can help to overcome our recognized finite capacities in data processing and integration. If we, doctors and health care providers or decision makers, are able to abandon our fears and prejudices, then we can utilize this new tool not only in imaging diagnostics but also for daily therapies (e.g., immune therapy). The paper aims to make a great mind to do this. Orv Hetil. 2019; 160(4): 138–143.

scholarly journals Developing an Open-Source Lightweight Game Engine with DNN Support

Electronics ◽  
2020 ◽  
Vol 9 (9) ◽  
pp. 1421
Author(s):  
Haechan Park ◽  
Nakhoon Baek
Keyword(s):  
Machine Learning ◽  
Deep Learning ◽  
Open Source ◽  
Programming Languages ◽  
Cost Effective ◽  
Machine Learning Techniques ◽  
Learning Technology ◽  
Game Engine ◽  
Learning Techniques ◽  
Technical Issues

With the growth of artificial intelligence and deep learning technology, we have many active research works to apply the related techniques in various fields. To test and apply the latest machine learning techniques in gaming, it will be very useful to have a light-weight game engine for quick prototyping. Our game engine is implemented in a cost-effective way, in comparison to well-known commercial proprietary game engines, by utilizing open source products. Due to its simple internal architecture, our game engine is especially beneficial for modifying and reviewing the new functions through quick and repetitive tests. In addition, the game engine has a DNN (deep neural network) module, with which the proposed game engine can apply deep learning techniques to the game features, through applying deep learning algorithms in real-time. Our DNN module uses a simple C++ function interface, rather than additional programming languages and/or scripts. This simplicity enables us to apply machine learning techniques more efficiently and casually to the game applications. We also found some technical issues during our development with open sources. These issues mostly occurred while integrating various open source products into a single game engine. We present details of these technical issues and our solutions.

scholarly journals Application of deep learning techniques for determining the spatial extent and classification of seagrass beds, Trang, Thailand

2019 ◽  
Vol 62 (4) ◽  
pp. 291-307 ◽  
Author(s):  
Takehisa Yamakita ◽  
Fumiaki Sodeyama ◽  
Napakhwan Whanpetch ◽  
Kentaro Watanabe ◽  
Masahiro Nakaoka
Keyword(s):  
Deep Learning ◽  
Temporal Dynamics ◽  
River Mouth ◽  
Aerial Photographs ◽  
Vegetation Coverage ◽  
Learning Technology ◽  
Seagrass Beds ◽  
Classification Methods ◽  
Learning Techniques

Abstract Few studies have investigated the long-term temporal dynamics of seagrass beds, especially in Southeast Asia. Remote sensing is one of the best methods for observing these dynamic patterns, and the advent of deep learning technology has led to recent advances in this method. This study examined the feasibility of applying image classification methods to supervised classification and deep learning methods for monitoring seagrass beds. The study site was a relatively natural seagrass bed in Hat Chao Mai National Park, Trang Province, Thailand, for which aerial photographs from the 1970s were available. Although we achieved low accuracy in differentiating among various densities of vegetation coverage, classification related to the presence of seagrass was possible with an accuracy of 80% or more using both classification methods. Automatic classification of benthic cover using deep learning provided similar or better accuracy than that of the other methods even when grayscale images were used. The results also demonstrate that it is possible to monitor the temporal dynamics of an entire seagrass area, as well as variations within sub-regions, located in close proximity to a river mouth.

Research Progress of Mg-Al Based Alloys

2013 ◽  
Vol 750-752 ◽  
pp. 583-586 ◽  
Author(s):  
Xiao Jie Song ◽  
Quan An Li ◽  
San Ling Fu ◽  
Wen Jian Liu ◽  
Zhi Chen
Keyword(s):  
Elevated Temperature ◽  
Magnesium Alloys ◽  
Future Development ◽  
Metal Structure ◽  
Research Progress ◽  
Creep Characteristics ◽  
Development Direction ◽  
The Future ◽  
The Way

Magnesium alloys as the emerging commercial metal structure material have excellent specific properties and stability, which is more and more vital for researcher. This paper reviews the creep characteristics and the way to enhance the elevated temperature properties of Mg-Al based alloys. The current Mg-Al based alloys (including AZ, AM, AS, AE, etc.) are summarized. The future development direction is pointed.

Research Progress of Mg-Re Alloys

2014 ◽  
Vol 937 ◽  
pp. 178-181 ◽  
Author(s):  
Quan An Li ◽  
Wen Chuang Liu ◽  
Xiao Jie Song
Keyword(s):  
Rare Earth ◽  
Elevated Temperature ◽  
Magnesium Alloy ◽  
Magnesium Alloys ◽  
Future Development ◽  
Metal Structure ◽  
Research Progress ◽  
Low Density ◽  
Development Direction ◽  
The Future

Magnesium alloys as the emerging commercial metal structure material have excellent specific properties, low density, and stability, which are more and more vital for researchers. This paper reviews the behavior of rare earth in magnesium alloy and the way to enhance the elevated temperature properties of Mg-RE alloys. The current Mg-RE alloys are summarized. The future development direction is pointed.

Sign in / Sign up

Export Citation Format

Share Document