標題: Titlebook: Deep Learning in Data Analytics; Recent Techniques, P Debi Prasanna Acharjya,Anirban Mitra,Noor Zaman Book 2022 Springer Nature Switzerland [打印本頁] 作者: BROOD 時間: 2025-3-21 18:15
書目名稱Deep Learning in Data Analytics影響因子(影響力)
書目名稱Deep Learning in Data Analytics影響因子(影響力)學科排名
書目名稱Deep Learning in Data Analytics網(wǎng)絡(luò)公開度
書目名稱Deep Learning in Data Analytics網(wǎng)絡(luò)公開度學科排名
書目名稱Deep Learning in Data Analytics被引頻次
書目名稱Deep Learning in Data Analytics被引頻次學科排名
書目名稱Deep Learning in Data Analytics年度引用
書目名稱Deep Learning in Data Analytics年度引用學科排名
書目名稱Deep Learning in Data Analytics讀者反饋
書目名稱Deep Learning in Data Analytics讀者反饋學科排名
作者: 松馳 時間: 2025-3-21 20:57
H.-S. Kim,L. Wiedeman,H. Helvajiansed learning algorithm used in this chapter. Finally, the pre-trained deep convolutional neural network (DCNN) model is used. The experiment is conducted using Geneva multimodal emotion portrayals (GEMEP) corpus dataset. In this dataset, human body movement expressing the five archetypical emotions 作者: 倒轉(zhuǎn) 時間: 2025-3-22 01:20 作者: SPER 時間: 2025-3-22 06:06
Introduction: An Overview of the Book stage, a deep ranking support vector machine (SVM) is used to define a consistent feature label, which will be served as input to a CNN. It reduces the number of channels in the following CNN and allows it to converge on extended detailed segmentation of the optic discs and vessels. In order to gai作者: 笨拙處理 時間: 2025-3-22 09:39
https://doi.org/10.1007/978-1-349-26109-3ed in an increased life span of patients with genetic disabilities. Thus, the affected persons can now live up?to a higher age. The current study aimed to discover hidden patterns from congenital heart databases for future medical diagnosis using a clustering technique to find secret ways. The desig作者: Hallowed 時間: 2025-3-22 14:20 作者: Hallowed 時間: 2025-3-22 17:52 作者: 一小塊 時間: 2025-3-23 00:03
Vorarbeiten zur empirischen Analyse,n concept of security in cloud computing. It also throws light on security to sensitive data, all the four-level authentication authorization, data security, network security, cloud security. Increasing threat of security in the growing demand of clouds is becoming a main issue. This chapter also de作者: Pastry 時間: 2025-3-23 02:19
2197-6503 in topics. All these help researchers motivate towards learning and implementing the concepts in real-life applications..978-3-030-75857-8978-3-030-75855-4Series ISSN 2197-6503 Series E-ISSN 2197-6511 作者: 原告 時間: 2025-3-23 05:40
A Study on Discrete Action Sequences Using Deep Emotional Intelligencesed learning algorithm used in this chapter. Finally, the pre-trained deep convolutional neural network (DCNN) model is used. The experiment is conducted using Geneva multimodal emotion portrayals (GEMEP) corpus dataset. In this dataset, human body movement expressing the five archetypical emotions 作者: Host142 時間: 2025-3-23 12:30 作者: 譏諷 時間: 2025-3-23 15:40
Automatic Image Segmentation by Ranking Based SVM in Convolutional Neural Network on Diabetic Fundus stage, a deep ranking support vector machine (SVM) is used to define a consistent feature label, which will be served as input to a CNN. It reduces the number of channels in the following CNN and allows it to converge on extended detailed segmentation of the optic discs and vessels. In order to gai作者: Occupation 時間: 2025-3-23 18:46
A Predictive Data Analytic Approach to Get Insight of Healthcare Databasesed in an increased life span of patients with genetic disabilities. Thus, the affected persons can now live up?to a higher age. The current study aimed to discover hidden patterns from congenital heart databases for future medical diagnosis using a clustering technique to find secret ways. The desig作者: 兵團 時間: 2025-3-24 00:00
An Extensive Study of Privacy Preserving Recommendation System Using Collaborative Filteringmation in a side recommender system is the main requirement with the best accuracy. This chapter summarizes all privacy-preserving methods for providing security and privacy to the user’s rating of a particular item.作者: abysmal 時間: 2025-3-24 04:26 作者: Slit-Lamp 時間: 2025-3-24 06:46 作者: correspondent 時間: 2025-3-24 13:31
On the Study of Machine Learning Algorithms Towards Healthcare Applicationstion of machine learning in healthcare may help increase the efficiency of diagnosing disease and be time-saving in predicting the device. In this chapter, the different healthcare sectors and how machine learning is useful in different sectors are looked into.作者: 鞠躬 時間: 2025-3-24 17:28 作者: biosphere 時間: 2025-3-24 19:32 作者: Decibel 時間: 2025-3-25 00:19 作者: 軍火 時間: 2025-3-25 04:40
https://doi.org/10.1007/978-1-349-26109-3 fraud in financial transactions and compare the deep learning model with several existing machine learning algorithms. The proposed model is applied on a dataset gathered in Europe in 2 days in September 2013. The accuracy evaluation metric is used to evaluate the ability of the proposed model to detect credit card fraud.作者: 捏造 時間: 2025-3-25 10:00 作者: Noisome 時間: 2025-3-25 12:10 作者: BINGE 時間: 2025-3-25 18:26
https://doi.org/10.1007/978-1-349-26109-3tion of machine learning in healthcare may help increase the efficiency of diagnosing disease and be time-saving in predicting the device. In this chapter, the different healthcare sectors and how machine learning is useful in different sectors are looked into.作者: 加劇 時間: 2025-3-25 23:49 作者: BLINK 時間: 2025-3-26 02:46 作者: 我要威脅 時間: 2025-3-26 08:08 作者: 磨坊 時間: 2025-3-26 09:53
Knowledge Framework for Deep Learning: Congenital Heart Diseaseques for deep learning to assist patient care by information mining methods. The attempt is to prescribe an automated strategy for diagnosing heart diseases in view of earlier information and data. However, purpose of study is to explore, detect patterns and understand the cause effective of congenital heart disease with varied parameters.作者: Libido 時間: 2025-3-26 15:55 作者: 輕快來事 時間: 2025-3-26 20:27 作者: 壁畫 時間: 2025-3-26 21:02
Deep Learning in Healthcareression of disease, develop a personalised treatment plan and for overall patient management. This chapter discusses the architecture and working of deep neural networks and focus on its application in the detection and treatment of various diseases like cancer, diabetes, Alzheimer’s and Parkinson’s disease.作者: peak-flow 時間: 2025-3-27 05:11
Anomaly Credit Card Fraud Detection Using Deep Learning fraud in financial transactions and compare the deep learning model with several existing machine learning algorithms. The proposed model is applied on a dataset gathered in Europe in 2 days in September 2013. The accuracy evaluation metric is used to evaluate the ability of the proposed model to detect credit card fraud.作者: Anticoagulants 時間: 2025-3-27 05:35 作者: 舊式步槍 時間: 2025-3-27 10:35 作者: Reclaim 時間: 2025-3-27 17:36
Debi Prasanna Acharjya,Anirban Mitra,Noor ZamanProvides recent advances in the fields of Deep Learning.Presents theoretical advances and its applications to real-life problems.Offers concepts and techniques of deep learning in a precise and clear 作者: Abrupt 時間: 2025-3-27 20:46 作者: coddle 時間: 2025-3-27 23:12
H.-S. Kim,L. Wiedeman,H. Helvajianis becoming recent research focus on artificial intelligence. A facet of human intelligence is the ability to recognize emotion that is regarded as one of the attribute of emotional intelligence. Although research based on facial expressions or speech is seen in thrive, recognizing emotions from bod作者: 下邊深陷 時間: 2025-3-28 05:41
Despine and the Evolution of Psychologyr biomedical image such as CT image, MRI, X-ray for automatic detection of some deadly diseases. A field of advance deep learning that made available a plethora of architecture as increase the dimension and complexity of the mammogram images has been focused, in this study. Removal of noise is a cru作者: Lyme-disease 時間: 2025-3-28 10:18
Introduction: An Overview of the Bookhumans for external purposes other than thinking. The current functional magnetic resonance imaging (FMRI) technology plays a vital role in the detection and estimation of brain patterns. The idea in this chapter is to analyse the uniqueness of human brain patterns and providing high level security 作者: 多嘴 時間: 2025-3-28 12:39 作者: Presbyopia 時間: 2025-3-28 14:45
Introduction: An Overview of the Bookf the optic disc, fovea, and blood vessels have became essential level for automated diagnosis practices. In diabetic retinopathy, the fundus regions are normally overbright, faint regional boundary and irregular in shape. Besides, the features of fundus region vary from regular tissues and hence, t作者: 債務 時間: 2025-3-28 21:41 作者: 諂媚于性 時間: 2025-3-29 02:51
https://doi.org/10.1007/978-1-349-26109-3, urban areas. To develop a highly sophisticated and automated multimodal biomedical data model, machine learning is highly influenceable. The application of machine learning in healthcare may help increase the efficiency of diagnosing disease and be time-saving in predicting the device. In this cha作者: 艦旗 時間: 2025-3-29 06:34 作者: 尖酸一點 時間: 2025-3-29 08:49 作者: gnarled 時間: 2025-3-29 14:10
Introduction: An Overview of the Bookically collected information according to the user’s choices, interest, or item’s behavior. The collaborative-based filtering recommender system is one of the best filtering approaches, which is very effective in a wide range of applications. The recommender system’s accuracy usually depends on the 作者: 苦笑 時間: 2025-3-29 18:59 作者: outer-ear 時間: 2025-3-29 20:18 作者: Arboreal 時間: 2025-3-30 02:05 作者: 鉤針織物 時間: 2025-3-30 07:45 作者: 和平主義 時間: 2025-3-30 10:23 作者: PATRI 時間: 2025-3-30 13:03
Deep Learning in Data Analytics978-3-030-75855-4Series ISSN 2197-6503 Series E-ISSN 2197-6511 作者: Ophthalmologist 時間: 2025-3-30 19:25
