Semantic analysis of multimedia content is an on going research area that has gained a lot of attention over the last few years. Additionally, Machine Learning techniques are widely used for multimedia analysis with great success. This work presents a combined approach to semantic adaptation of neural network classifiers in multimedia framework. It is based on a fuzzy reasoning engine which is able to evaluate the outputs and the confidence levels of the neural network classifier, using a knowledge base. Improved image segmentation results are obtained, which are used for adaptation of the network classifier, further increasing its ability to provide accurate classification of the specific content.
標(biāo)簽： multimedia Semantic analysis research
上傳時間： 2016-11-24
上傳用戶：蟲蟲蟲蟲蟲蟲
pdf格式的英文文獻，是關(guān)于認(rèn)知無線電網(wǎng)絡(luò)的，編者是加拿大桂爾夫大學(xué)的Qusay H. Mahmoud。ISBN：978-0-470-06196-1 章節(jié)內(nèi)容： 1 Biologically Inspired Networking 2 The Role of Autonomic Networking in Cognitive Networks 3 Adaptive Networks 4 Self-Managing Networks 5 Machine Learning for Cognitive Networks: Technology Assessment and Research Challenges 6 Cross-Layer Design and Optimization in Wireless Networks 等，共計13章，全書348頁，pdf文件383頁。
標(biāo)簽： 英文
上傳時間： 2014-01-27
上傳用戶：daguda
Text mining tries to solve the crisis of information overload by combining techniques from data mining, Machine Learning, natural language processing, information retrieval, and knowledge management. In addition to providing an in-depth examination of core text mining and link detection algorithms and operations, this book examines advanced pre-processing techniques, knowledge representation considerations, and visualization approaches. Finally, it explores current real-world, mission-critical applications of text mining and link detection in such varied fields as M&A business intelligence, genomics research and counter-terrorism activities.
標(biāo)簽： information techniques combining overload
上傳時間： 2014-01-02
上傳用戶：Late_Li
介紹回歸問題中高斯過程的應(yīng)用，C. E. Rasmussen & C. K. I. Williams, Gaussian Processes for Machine Learning,
上傳時間： 2017-07-25
上傳用戶：skfreeman
Pattern Analysis is the process of fi nding general relations in a set of data, and forms the core of many disciplines, from neural networks to so-called syn- tactical pattern recognition, from statistical pattern recognition to machine learning and data mining. Applications of pattern analysis range from bioin- formatics to document retrieval.
標(biāo)簽： the relations Analysis Pattern
上傳時間： 2017-09-07
上傳用戶：SimonQQ
機器學(xué)習(xí)實戰(zhàn) 英文原版 涵蓋基礎(chǔ)算法的實戰(zhàn)演練和源碼
標(biāo)簽： machine learning
上傳時間： 2015-04-14
上傳用戶：dyd1123
Evolutionary Computation (EC) deals with problem solving, optimization, and machine learning techniques inspired by principles of natural evolution and ge- netics. Just from this basic definition, it is clear that one of the main features of the research community involved in the study of its theory and in its applications is multidisciplinarity. For this reason, EC has been able to draw the attention of an ever-increasing number of researchers and practitioners in several fields.
標(biāo)簽： Applications Evolutionary Computing of
上傳時間： 2020-05-26
上傳用戶：shancjb
This introduction takes a visionary look at ideal cognitive radios (CRs) that inte- grate advanced software-defined radios (SDR) with CR techniques to arrive at radios that learn to help their user using computer vision, high-performance speech understanding, global positioning system (GPS) navigation, sophisticated adaptive networking, adaptive physical layer radio waveforms, and a wide range of Machine Learning processes.
標(biāo)簽： Technology Cognitive Radio
上傳時間： 2020-05-26
上傳用戶：shancjb
Although state of the art in many typical Machine Learning tasks, deep learning algorithmsareverycostly interms ofenergyconsumption,duetotheirlargeamount of required computations and huge model sizes. Because of this, deep learning applications on battery-constrained wearables have only been possible through wireless connections with a resourceful cloud. This setup has several drawbacks. First, there are privacy concerns. Cloud computing requires users to share their raw data—images, video, locations, speech—with a remote system. Most users are not willing to do this. Second, the cloud-setup requires users to be connected all the time, which is unfeasible given current cellular coverage. Furthermore, real-time applications require low latency connections, which cannot be guaranteed using the current communication infrastructure. Finally, wireless connections are very inefficient—requiringtoo much energyper transferredbit for real-time data transfer on energy-constrained platforms.
標(biāo)簽： Embedded_Deep_Learning Algorithms
上傳時間： 2020-06-10
上傳用戶：shancjb
The present era of research and development is all about interdisciplinary studies attempting to better comprehend and model our understanding of this vast universe. The fields of biology and computer science are no exception. This book discusses some of the innumerable ways in which computational methods can be used to facilitate research in biology and medicine—from storing enormous amounts of biological data to solving complex biological problems and enhancing the treatment of various diseases.
標(biāo)簽： Learning Machine IoT and
上傳時間： 2020-06-10
上傳用戶：shancjb
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