標(biāo)題: Titlebook: Classification Applications with Deep Learning and Machine Learning Technologies; Laith Abualigah Book 2023 The Editor(s) (if applicable) [打印本頁] 作者: Consonant 時(shí)間: 2025-3-21 19:23
書目名稱Classification Applications with Deep Learning and Machine Learning Technologies影響因子(影響力)
書目名稱Classification Applications with Deep Learning and Machine Learning Technologies影響因子(影響力)學(xué)科排名
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書目名稱Classification Applications with Deep Learning and Machine Learning Technologies網(wǎng)絡(luò)公開度學(xué)科排名
書目名稱Classification Applications with Deep Learning and Machine Learning Technologies被引頻次
書目名稱Classification Applications with Deep Learning and Machine Learning Technologies被引頻次學(xué)科排名
書目名稱Classification Applications with Deep Learning and Machine Learning Technologies年度引用
書目名稱Classification Applications with Deep Learning and Machine Learning Technologies年度引用學(xué)科排名
書目名稱Classification Applications with Deep Learning and Machine Learning Technologies讀者反饋
書目名稱Classification Applications with Deep Learning and Machine Learning Technologies讀者反饋學(xué)科排名
作者: 拋棄的貨物 時(shí)間: 2025-3-21 21:42 作者: GILD 時(shí)間: 2025-3-22 02:03 作者: Jacket 時(shí)間: 2025-3-22 05:48
Jerzy Korczak,Aleksander Fafu?a We also compared the performance of optimizers and three levels of epoch on the performance of the model. In general, transfer learning with a pre-trained VGG16 neural network provides higher performance for the dataset; the dataset performed better with an optimizer of SGD, compared with ADAM.作者: Inflamed 時(shí)間: 2025-3-22 11:09 作者: 品嘗你的人 時(shí)間: 2025-3-22 13:35 作者: 品嘗你的人 時(shí)間: 2025-3-22 19:00
Research in Security Sector Reform Policyption. Effects of variables, i.e., hidden layers, perceptrons, filter number, optimizers, and learning rate, on the proposed model are also investigated in this study. The best performing model in this study is the new proposed model with 2 CNN layers (12, 96 filters) and 6 dense layers with 147 perceptrons, achieving an accuracy of 87%.作者: affect 時(shí)間: 2025-3-22 22:11 作者: Conserve 時(shí)間: 2025-3-23 02:48
Book 2023elps them study, formulate, and design their research goal by aligning the latest technologies studies’ image and data classifications. The early start-up can use it to work with product or prototype design requirement analysis and its design and development..作者: 無法治愈 時(shí)間: 2025-3-23 07:17
https://doi.org/10.1007/978-3-319-16348-2ollected and obtain a deep learning model which is able to classify four types of mango (Alampur Baneshan, Alphonso, Harum Manis and Keitt) automatically. In summary, the objective in this paper is to develop a deep learning algorithm to automatically classify four types of mango cultivar.作者: 該得 時(shí)間: 2025-3-23 12:06
Jerzy Korczak,Aleksander Fafu?attack possibility) dataset, freely available on kagle. The data was divided into three categories consisting of (303, 909, 1808) instances which were analyzed on the WEKA platform. The results showed that the RFC was the best performer.作者: Anthrp 時(shí)間: 2025-3-23 15:34
Mango Varieties Classification-Based Optimization with Transfer Learning and Deep Learning Approachollected and obtain a deep learning model which is able to classify four types of mango (Alampur Baneshan, Alphonso, Harum Manis and Keitt) automatically. In summary, the objective in this paper is to develop a deep learning algorithm to automatically classify four types of mango cultivar.作者: Incompetent 時(shí)間: 2025-3-23 20:12
A Novel Big Data Classification Technique for Healthcare Application Using Support Vector Machine, ttack possibility) dataset, freely available on kagle. The data was divided into three categories consisting of (303, 909, 1808) instances which were analyzed on the WEKA platform. The results showed that the RFC was the best performer.作者: 圓錐 時(shí)間: 2025-3-24 00:23 作者: 難聽的聲音 時(shí)間: 2025-3-24 02:42
Research in Soviet Social Psychologyvert into jpg format and augmentation. Based on the accuracy result from the model, the best model for the salak classification is ResNet50 which gave an accuracy of 84% followed by VGG16 that gave an accuracy of 77% and CNN which gave 31%.作者: 有罪 時(shí)間: 2025-3-24 10:07 作者: 音樂戲劇 時(shí)間: 2025-3-24 13:54
Iryna Zolotaryova,Anna Khodyrevskawith a higher accuracy. In the proposed work, we also inspected two transfer learning methods in the classification of markisa which are VGG-16 and InceptionV3. The results showed that the performance of the first proposed CNN model outperforms VGG-16 (95% accuracy) and InceptionV3 (65% accuracy).作者: Arteriography 時(shí)間: 2025-3-24 17:34 作者: PRO 時(shí)間: 2025-3-24 21:56 作者: 幾何學(xué)家 時(shí)間: 2025-3-25 01:02 作者: DIS 時(shí)間: 2025-3-25 07:07 作者: indecipherable 時(shí)間: 2025-3-25 09:27
Salak Image Classification Method Based Deep Learning Technique Using Two Transfer Learning Models,vert into jpg format and augmentation. Based on the accuracy result from the model, the best model for the salak classification is ResNet50 which gave an accuracy of 84% followed by VGG16 that gave an accuracy of 77% and CNN which gave 31%.作者: champaign 時(shí)間: 2025-3-25 15:02
Image Processing Identification for Sapodilla Using Convolution Neural Network (CNN) and Transfer Lnguish Sapodilla from various?images. Furthermore, we utilized different versions of hidden layer and epochs for various outcomes to improve predictive performance. We investigated transfer learning approaches in the classification of Sapodilla?in the suggested study. The suggested CNN model improve作者: APO 時(shí)間: 2025-3-25 18:48 作者: 騙子 時(shí)間: 2025-3-25 19:58 作者: Champion 時(shí)間: 2025-3-26 04:07
Comparative Study on Arabic Text Classification: Challenges and Opportunities, researches, SVM and Naive Bayes were the most widely used classifiers for Arabic text classification, while more effort is needed to develop and to implement flexible Arabic text classification methods and classifiers.作者: leniency 時(shí)間: 2025-3-26 04:40
Pedestrian Speed Prediction Using Feed Forward Neural Network,rian speed with a value of 67.72?m/min and 52.19?m/min. The speed distribution also indicate male pedestrian wearing English/short African clothes and cover shoe to have a higher mean speed of 84.21?m/min and 60.10?m/min in ascending descending direction The artificial neural network was satisfactor作者: SAGE 時(shí)間: 2025-3-26 11:53 作者: CAMP 時(shí)間: 2025-3-26 13:54 作者: 沖擊力 時(shí)間: 2025-3-26 20:28 作者: 獨(dú)行者 時(shí)間: 2025-3-26 22:31
Studies in Computational Intelligencehttp://image.papertrans.cn/c/image/227186.jpg作者: Toxoid-Vaccines 時(shí)間: 2025-3-27 02:28 作者: 發(fā)炎 時(shí)間: 2025-3-27 09:16
978-3-031-17578-7The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl作者: ellagic-acid 時(shí)間: 2025-3-27 12:47 作者: 輕快來事 時(shí)間: 2025-3-27 17:25 作者: 使成核 時(shí)間: 2025-3-27 19:16 作者: 彎彎曲曲 時(shí)間: 2025-3-27 23:22
Research in Soviet Social Psychologylor will be different depending on the cultivar. Thus, classification of salak based on their cultivar become a daily job for the fruit farmers. There are many techniques that can be used for fruit classification using computer vision technology. Deep learning is the most promising algorithm compare作者: mitral-valve 時(shí)間: 2025-3-28 02:59 作者: 無脊椎 時(shí)間: 2025-3-28 07:36 作者: flourish 時(shí)間: 2025-3-28 10:34
Iryna Zolotaryova,Anna Khodyrevskan the production line, which is labor intensive, error-prone, and ineffective. Therefore, a lot of fruit recognition systems are created to automate the process, but fruit recognition system for Malaysia local fruit is limited. Thus, this project will focus on classifying one of the Malaysia local f作者: 帶子 時(shí)間: 2025-3-28 14:51 作者: neolith 時(shí)間: 2025-3-28 19:55 作者: Ligament 時(shí)間: 2025-3-28 23:29
Research in Terrestrial Impact Structuresfields. This made finding certain text classification algorithms that fit a specific language or a set of languages a difficult task for researchers. Text Classification or categorization is the practice of allocating a given text document to one or more predefined labels or categories, it aims to o作者: Fierce 時(shí)間: 2025-3-29 06:28 作者: BILE 時(shí)間: 2025-3-29 09:29
A. V. Bridgwater,J. M. Double,S. A. Bridge both Arabic, and its dialects. This text describes the user’s condition or needs for satisfaction or dissatisfaction, and this evaluation is either negative or positive polarity. Based on the need to work on Arabic text sentiment analysis problem, the case of the Jordanian dialect.?The main purpose作者: 大雨 時(shí)間: 2025-3-29 13:10 作者: orthopedist 時(shí)間: 2025-3-29 16:03 作者: 懶惰民族 時(shí)間: 2025-3-29 23:40
Rambutan Image Classification Using Various Deep Learning Approaches,assified into tens of different cultivars based on fruit, flesh, and tree features. In this project, five different rambutan cultivars classification models using deep learning techniques were developed based on a 1000 rambutan images dataset. Common deep learning methods for the image classificatio作者: 紅腫 時(shí)間: 2025-3-30 01:35 作者: Habituate 時(shí)間: 2025-3-30 05:47
