標(biāo)題: Titlebook: Concepts and Real-Time Applications of Deep Learning; Smriti Srivastava,Manju Khari,Parul Arora Book 2021 The Editor(s) (if applicable) an [打印本頁] 作者: 不幸的你 時(shí)間: 2025-3-21 18:07
書目名稱Concepts and Real-Time Applications of Deep Learning影響因子(影響力)
書目名稱Concepts and Real-Time Applications of Deep Learning影響因子(影響力)學(xué)科排名
書目名稱Concepts and Real-Time Applications of Deep Learning網(wǎng)絡(luò)公開度
書目名稱Concepts and Real-Time Applications of Deep Learning網(wǎng)絡(luò)公開度學(xué)科排名
書目名稱Concepts and Real-Time Applications of Deep Learning被引頻次
書目名稱Concepts and Real-Time Applications of Deep Learning被引頻次學(xué)科排名
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書目名稱Concepts and Real-Time Applications of Deep Learning讀者反饋
書目名稱Concepts and Real-Time Applications of Deep Learning讀者反饋學(xué)科排名
作者: Awning 時(shí)間: 2025-3-21 23:49
Text-Independent Speaker Recognition Using Deep Learningto text-dependent speaker recognition and text-independent speaker recognition systems. In a text-dependent system, the recognition phrases are fixed (known beforehand). The user can be prompted to read a randomly selected sequence of numbers. However, in a text-independent speaker recognition syste作者: Obstreperous 時(shí)間: 2025-3-22 02:39 作者: eucalyptus 時(shí)間: 2025-3-22 06:21
Emotion Recognition from Speech Signals Using Machine Learning and Deep Learning Techniquesrithms, these can be applied to develop highly accurate speech emotion recognition systems (SER systems). Hence, this paper explores deep neural network (DNN) architectures and machine learning approaches to recognise emotions from speech signals. The project involves multiple steps, starting with t作者: 同義聯(lián)想法 時(shí)間: 2025-3-22 09:32
Micro-expression Detection Using Main Directional Maximal Differential Analysis (MDMD) Methodly a fraction of a second, so it’s difficult to deceit such expressions. The subtleness of these expressions poses a significant challenge to the naked eye; hence, a lot of work and researches has been made to detect and recognize these facial micro-expressions. One of the challenges for the detecti作者: 季雨 時(shí)間: 2025-3-22 14:57 作者: 季雨 時(shí)間: 2025-3-22 19:47 作者: Morsel 時(shí)間: 2025-3-22 22:37
Bone Cancer Survivability Prognosis with KNN and Genetic Algorithmsians in providing more informed decisions specifically in evaluating proper probability attributes (risk) in relation to outcome (impact) and subsequently the overall result (expected outcome) of treatment procedures. Predictability on survival in health care is very much related to a decision-makin作者: neuron 時(shí)間: 2025-3-23 01:42
BeamAtt: Generating Medical Diagnosis from Chest X-Rays Using Sampling-Based Intelligence economically downtrodden nations, this produces opportunity for the poor to acquire world-class treatment from around the globe with an efficient time to market. Chest X-ray images are integral to the task of diagnosis and treatment of respiratory problems. In this paper, we propose BeamAtt: an end作者: Libido 時(shí)間: 2025-3-23 06:55 作者: faultfinder 時(shí)間: 2025-3-23 09:56 作者: 愉快嗎 時(shí)間: 2025-3-23 14:09 作者: ORE 時(shí)間: 2025-3-23 18:28
Matthew M. Peet,Catherine Bonnet,Hitay ?zbays considered are support vector classifier (SVC), decision tree, and random forest. Boosting algorithms are AdaBoost, XGBoost, and CatBoost. Based on accuracy, time of processing and various performance parameters CatBoost was determined as the best algorithm to predict the survival chances of a cancer patient.作者: irradicable 時(shí)間: 2025-3-24 00:37 作者: 無王時(shí)期, 時(shí)間: 2025-3-24 03:00 作者: 饑荒 時(shí)間: 2025-3-24 08:18 作者: Nonporous 時(shí)間: 2025-3-24 11:04 作者: 吞噬 時(shí)間: 2025-3-24 16:54 作者: 袖章 時(shí)間: 2025-3-24 22:18 作者: 詳細(xì)目錄 時(shí)間: 2025-3-25 00:52
Gravitational Radiation Experiments,ed on gait energy image and CNNs which prove that both methods have impressive performances and accuracies given a descriptive dataset. Moreover, it also tackles the above-mentioned challenges to a remarkable extent.作者: 高興一回 時(shí)間: 2025-3-25 06:56 作者: Distribution 時(shí)間: 2025-3-25 11:01 作者: 效果 時(shí)間: 2025-3-25 12:34
https://doi.org/10.1007/978-1-4419-8249-0a considerably sound knowledge base of social science, psychology, and anthropology that helps to train the machine. In this chapter, analysis and classification of speech for emotion recognition is done on RAVDESS dataset. Features are being extracted from speech utterances using Mel-frequency ceps作者: BURSA 時(shí)間: 2025-3-25 19:54
Synchrotron Radiation and Astrophysics, this paper, Mel-frequency cepstral coefficients (MFCC) were extracted from the audio files. These features were then fed a convolutional neural network (CNN). This CNN was then optimized in order to increase model accuracy. Over the span of six runs of varying parameters, a maximum accuracy of appr作者: 橫截,橫斷 時(shí)間: 2025-3-25 22:11
Shock Waves in General Relativity, was noted. Six different models have been mentioned in this paper, and out of all the approaches performed, the multilayer perceptron neural network performed the best, having an average accuracy of 70.65% on three different input variations.作者: engrave 時(shí)間: 2025-3-26 00:27
General Relativity and Quantum Theory, from a video for recognition. The optical flow method was also used with neural networks for their detection. Nowadays, apex frame within a video frame is being used for the spatial-temporal credit, and the 3DCNN model is also being used. This chapter explains the Main Directional Maximal Different作者: V洗浴 時(shí)間: 2025-3-26 05:59
Matthew M. Peet,Catherine Bonnet,Hitay ?zbayed to forecast probable recovery. A common statistical approach used for this purpose is known as the Kaplan-Meier analysis. Survival predictability has become integral to the facilitation of patient care and resource optimization. This paper aims to provide an alternative survivability assessment u作者: Diastole 時(shí)間: 2025-3-26 09:30
The Permeability of Abnormal Skin,ion while generating inferences and argue that a simpler framework with intelligent optimisation is able to successfully achieve higher performance metrics. We show how vivid attention plots can provide deep insight into the region of the image on which the network concentrates to generate a word to作者: 催眠 時(shí)間: 2025-3-26 13:31 作者: 罵人有污點(diǎn) 時(shí)間: 2025-3-26 19:17 作者: mechanism 時(shí)間: 2025-3-26 21:27
Book 2021itectures;.Includes a survey of deep learning problems and solutions,?identifying?the main open issues, innovations and latest technologies;.Shows industrial deep learning in practice with examples/cases, efforts, challenges, and strategic approaches..作者: 逃避系列單詞 時(shí)間: 2025-3-27 03:29 作者: MELD 時(shí)間: 2025-3-27 08:31 作者: anticipate 時(shí)間: 2025-3-27 10:49
Text-Independent Speaker Recognition Using Deep Learning this paper, Mel-frequency cepstral coefficients (MFCC) were extracted from the audio files. These features were then fed a convolutional neural network (CNN). This CNN was then optimized in order to increase model accuracy. Over the span of six runs of varying parameters, a maximum accuracy of appr作者: Dorsal 時(shí)間: 2025-3-27 14:15
Emotion Recognition from Speech Signals Using Machine Learning and Deep Learning Techniques was noted. Six different models have been mentioned in this paper, and out of all the approaches performed, the multilayer perceptron neural network performed the best, having an average accuracy of 70.65% on three different input variations.作者: 抑制 時(shí)間: 2025-3-27 21:44 作者: Pde5-Inhibitors 時(shí)間: 2025-3-28 01:58 作者: hypertension 時(shí)間: 2025-3-28 05:01 作者: exceptional 時(shí)間: 2025-3-28 07:05 作者: 殺菌劑 時(shí)間: 2025-3-28 10:59
A Low-Cost IOT and Deep Learning Enabled Precision Agriculture Support System for Indian Diverse Envnetwork (NN)-based small squeeze-and-excitation (SE) block residual network module with 50 layers (SE-Resnet50). In experimentation, convolutional neural network (CNN), residual neural network-50 (ResNet50), and SE-Resnet50 model are trained with 24,360 images of tomato plant leaves and 17,134 image作者: AIL 時(shí)間: 2025-3-28 17:04
2522-8595 open issues, innovations and latest technologies;.Shows industrial deep learning in practice with examples/cases, efforts, challenges, and strategic approaches..978-3-030-76169-1978-3-030-76167-7Series ISSN 2522-8595 Series E-ISSN 2522-8609 作者: 干旱 時(shí)間: 2025-3-28 22:08
Concepts and Real-Time Applications of Deep Learning978-3-030-76167-7Series ISSN 2522-8595 Series E-ISSN 2522-8609 作者: 追蹤 時(shí)間: 2025-3-29 00:43 作者: 艱苦地移動(dòng) 時(shí)間: 2025-3-29 07:05 作者: 合同 時(shí)間: 2025-3-29 08:58
Gravitational Radiation Experiments,stance without their knowledge and cooperation is still however a problem for most of the biometrics mentioned above. Sometimes these techniques are necessary for security and surveillance purposes. They also might prove to be useful for orthopaedic problems. The existing models of gait recognition 作者: 一再遛 時(shí)間: 2025-3-29 14:28
Shock Waves in General Relativity,rithms, these can be applied to develop highly accurate speech emotion recognition systems (SER systems). Hence, this paper explores deep neural network (DNN) architectures and machine learning approaches to recognise emotions from speech signals. The project involves multiple steps, starting with t
