標(biāo)題: Titlebook: Recent Trends in Artificial Intelligence and IoT; First International Rajesh Kumar Tiwari,G. Sahoo Conference proceedings 2023 The Editor( [打印本頁(yè)] 作者: mobility 時(shí)間: 2025-3-21 16:16
書(shū)目名稱(chēng)Recent Trends in Artificial Intelligence and IoT影響因子(影響力)
書(shū)目名稱(chēng)Recent Trends in Artificial Intelligence and IoT影響因子(影響力)學(xué)科排名
書(shū)目名稱(chēng)Recent Trends in Artificial Intelligence and IoT網(wǎng)絡(luò)公開(kāi)度
書(shū)目名稱(chēng)Recent Trends in Artificial Intelligence and IoT網(wǎng)絡(luò)公開(kāi)度學(xué)科排名
書(shū)目名稱(chēng)Recent Trends in Artificial Intelligence and IoT被引頻次
書(shū)目名稱(chēng)Recent Trends in Artificial Intelligence and IoT被引頻次學(xué)科排名
書(shū)目名稱(chēng)Recent Trends in Artificial Intelligence and IoT年度引用
書(shū)目名稱(chēng)Recent Trends in Artificial Intelligence and IoT年度引用學(xué)科排名
書(shū)目名稱(chēng)Recent Trends in Artificial Intelligence and IoT讀者反饋
書(shū)目名稱(chēng)Recent Trends in Artificial Intelligence and IoT讀者反饋學(xué)科排名
作者: 窩轉(zhuǎn)脊椎動(dòng)物 時(shí)間: 2025-3-21 21:01 作者: 可耕種 時(shí)間: 2025-3-22 00:26
ral and problem oriented way. Recently so called metric or real-time temporal logics have been proposed for the specification of real-time systems, for which not only qualitative but also quantitative temporal properties are very important. In this work we investigate a subset of metric temporal Hor作者: Indent 時(shí)間: 2025-3-22 06:19 作者: fertilizer 時(shí)間: 2025-3-22 10:33 作者: 持久 時(shí)間: 2025-3-22 15:11 作者: ASSET 時(shí)間: 2025-3-22 18:57
Lung Disease Classification Using CNN-Based Trained Models from CXR Imageccuracy to that of three popular pre-trained models, including ResNet-50, Vgg-16, and Vgg-19. The VGG-16, VGG-19 and ResNet-50 CNN-based pre-trained models also achieved an accuracy of 95.76%, 92.84%, and 96.27%, respectively in classification. The results demonstrated that the cascaded feature gene作者: 諄諄教誨 時(shí)間: 2025-3-22 21:45 作者: CHIP 時(shí)間: 2025-3-23 02:12
Meta-transfer Learning for Contextual Emotion Detection in Face Affirmationbile Net-V2 model with the transfer learning strategy to speed up the generation time and improve the accuracy of emotion detection. In order to improve upon the current method, we have compiled a large CIFE data collection from the relevant literature. One of the best outcomes for emotion detection作者: Apraxia 時(shí)間: 2025-3-23 08:16 作者: CLAMP 時(shí)間: 2025-3-23 13:03 作者: 實(shí)施生效 時(shí)間: 2025-3-23 14:02 作者: atopic-rhinitis 時(shí)間: 2025-3-23 20:32
Advanced MRI Segmentation Algorithm for the Detection of Brain Tumor Using U-Net Architecture with Tal networks (CNNs) and U-Nets with different transfer learning models as backbones, including ResNet50, Vgg16, InceptionV4, DenseNet169, and EfficientNet-B7. Making use of the BraTS 2020 dataset, brain lesion segmentation is carried out. The tumor segmentation method is evaluated using the F1-Score,作者: LIEN 時(shí)間: 2025-3-24 00:38
Audio Analysis for Early Diagnosis of Alzheimer’s Disease: A Study on Fisher’s Linear Discriminant ay system..With a focus on the use of audio analysis in diagnosis, we first give a general overview of AD and its diagnosis. The use of MFCCs and FLD for categorizing Alzheimer‘s patients based on audio data is then discussed..Overall, the findings of earlier research indicate that FLD and MFCCs can 作者: abreast 時(shí)間: 2025-3-24 05:50
Automation in?Agriculture Using Deep Machine Learning: A Surveyr the farming sector. Deep Learning (DL), including the algorithms of Convolutional Neural Networks (CNN), Recurrent Neural Networks (RNN), and Generative Adversarial Networks (GAN), has been extensively studied and implemented in a variety of disciplines, including agriculture, in recent years. Thi作者: GRATE 時(shí)間: 2025-3-24 06:44
Amod Kumar Sahwal,Manjeet Singh,Namrata Kumari,Krishna Murari,Shashi Prabhaoteric things like David Williams‘ path decomposition, it provides a method for constructing processes whose description in terms of an in- finitesimal generato978-1-4684-9414-3978-1-4684-9412-9Series ISSN 2297-0371 Series E-ISSN 2297-0398 作者: Commemorate 時(shí)間: 2025-3-24 11:39
Sanjay Kumar Mahto,Yogendra Kumar,Manjeet Singh,Ruchi Kumari,Kishore Kumar Rayuse to advantage general probabilistic potential theory to make quite specific calculations, it provides a natural setting for apply- ing esoteric things like David Williams‘ path decomposition, it provides a method for constructing processes whose description in terms of an in- finitesimal generato作者: Type-1-Diabetes 時(shí)間: 2025-3-24 17:48
r .′ which is NP-complete. Moreover, we show that an extension of the metric temporal logic considered by the inclusion of variables within the temporal operators leads already to a temporal Horn logic which is expressively equivalent to constraint logic programs over .′.作者: 銀版照相 時(shí)間: 2025-3-24 19:38 作者: 衰弱的心 時(shí)間: 2025-3-25 01:53
Md Shoaib Alam,Pankaj Rai,Rajesh Kumar Tiwari,Vijay Pandey,Sharafat Hussain作者: Host142 時(shí)間: 2025-3-25 03:32 作者: 財(cái)主 時(shí)間: 2025-3-25 09:30 作者: Gobble 時(shí)間: 2025-3-25 13:50
Simranjit Singh,Monika Gosain,Rubaljeet Kaur,Sukhpreet Kaur,Triloki Nath作者: hematuria 時(shí)間: 2025-3-25 17:21 作者: DEMN 時(shí)間: 2025-3-25 22:53
Prakash Anand,Piyush Ranjan,Priyanka Srivastava,Deepak Kumar作者: 牲畜欄 時(shí)間: 2025-3-26 03:07
P. Kirubanantham,G. Arun Prasath,A. Saranya,G. M. Karthik作者: 兇猛 時(shí)間: 2025-3-26 04:38
Litan Kumar Das,Kumar Sankar Ray,Prakash Chandra Mali作者: 開(kāi)玩笑 時(shí)間: 2025-3-26 10:09 作者: 灰姑娘 時(shí)間: 2025-3-26 14:31
Vikash Kumar Dubey,Krishna Murari,Triloki Nath,Kriti Poddar作者: ELATE 時(shí)間: 2025-3-26 17:36 作者: 為寵愛(ài) 時(shí)間: 2025-3-26 22:04
On Assaying the T-score Value for the Detection and Classification of Osteoporosis Using AI Learningsteoporosis has become a worldwide health issue. However, early detection is difficult due to the absence of visible symptoms. Therefore, to screen osteoporosis using AI techniques via dental based panoramic radiographs would be cost-effective as well as beneficial. This study investigates the contr作者: 贊美者 時(shí)間: 2025-3-27 02:24
Evaluation of Healthcare Data in Machine Learning Model Used in Fraud Detectiong a machine learning model, get evaluation from different kind of techniques, make enhancement and progress until we accomplish a expected efficiency. Feedback metrics describe the work of a machine learning model. Critical form of feedback metrics is their potential to segregate among machine learn作者: 異端邪說(shuō)下 時(shí)間: 2025-3-27 06:18
A New Approach to Heart Disease Prediction Using Clustering and Classification Algorithmsy are found on the understanding and knowledge of medical professionals instead of knowledge of a mass of data invisible in a record. Medical professionals must undergo continuous training to make sound clinical decisions. They use basic knowledge, current research and work experience. These exercis作者: Foregery 時(shí)間: 2025-3-27 13:07 作者: CON 時(shí)間: 2025-3-27 17:39 作者: 流逝 時(shí)間: 2025-3-27 21:49
A Novel Framework for?Satellite Image Denoising and?Super Resolution Using CNN-GANapplications of Deep Learning and other methodologies have made significant achievements in this field. Generative Adversarial Network advancement takes researcher attention towards this area due to results obtained by GAN. In this paper, We focused on the speckle noise denoising and super-resolutio作者: placebo 時(shí)間: 2025-3-27 23:51
Deep Learning Based Enhanced Text Recognition System of recognizing objects, photos, messages, observations, and other structures. The underwhelming performance of the current scene recognition algorithms has motivated many researchers in the computer vision field in recent years, yet scene text recognition still need improvement. This study offered 作者: 搖曳 時(shí)間: 2025-3-28 02:39
Meta-transfer Learning for Contextual Emotion Detection in Face Affirmationy, people will show seven distinct feelings (happy, angry, surprised, sad, disgusted, fearful, and neutral). Humans communicate their feelings via words, body language, and facial expressions. Humans’ ability to reveal inner thought processes via facial expressions is crucial to studying human behav作者: 發(fā)微光 時(shí)間: 2025-3-28 06:44
Hand-Written Devanagri Character Recognition Using Convolutional Neural Network in Python with Tensoies. One of the main goals of AI is to enable machines to see, understand, and read text. Although much effort has been done in this area, the intricacy of the problem has not yet been fully resolved. A good text recognizer can be used for a wide range of practical and commercial purposes, such as a作者: 模仿 時(shí)間: 2025-3-28 12:25 作者: gait-cycle 時(shí)間: 2025-3-28 16:56
Bisimulations for?Fuzzy Geometric Modelsal operators are introduced in the fuzzy geometric logic language using coalgebraic techniques. We introduce the idea of fuzzy-open predicate lifting in order to define the modal operators. Based on coalgebras for an endofunctor . on the category . of fuzzy topological spaces, we build models for th作者: 擁護(hù) 時(shí)間: 2025-3-28 19:05 作者: Camouflage 時(shí)間: 2025-3-29 00:22 作者: 不可思議 時(shí)間: 2025-3-29 07:04 作者: ALTER 時(shí)間: 2025-3-29 09:33 作者: 網(wǎng)絡(luò)添麻煩 時(shí)間: 2025-3-29 11:58
A Survey on Security Threats in VANET and Its Solutionshoc networks (ITS). “Virtual Ad Hoc Networks” (VANETs) are the most popular, productive, and quickly growing subset of “mobile ad hoc networks” (MANETs). The wireless network called VANET is hard to predict because it is made up of both roadside units (RSUs) and on-board units (OBUs) as well as cars作者: 才能 時(shí)間: 2025-3-29 18:39
Conference proceedings 2023eld in Jamshedpur, India. ICAII 2022 has been postponed to April 2023.?.The 23 papers were thoroughly reviewed and selected from the 86 submissions. They are arranged in topical sections on?.?.artificial Intelligence, and Internet of Things..作者: 眨眼 時(shí)間: 2025-3-29 23:22 作者: inhibit 時(shí)間: 2025-3-30 01:56 作者: 服從 時(shí)間: 2025-3-30 05:47 作者: 心痛 時(shí)間: 2025-3-30 08:55
Bisimulations for?Fuzzy Geometric Modelse coalgebraic fuzzy geometric logic. We study the relationship between the concepts of behavioural equivalence and modal equivalence on the class of fuzzy geometric models. Furthermore, the paper studies bisimulation for fuzzy geometric models.作者: Trochlea 時(shí)間: 2025-3-30 15:29 作者: Etymology 時(shí)間: 2025-3-30 20:07 作者: 我邪惡 時(shí)間: 2025-3-31 00:02 作者: 可觸知 時(shí)間: 2025-3-31 02:58 作者: Corporeal 時(shí)間: 2025-3-31 08:18
Recent Trends in Artificial Intelligence and IoT978-3-031-37303-9Series ISSN 1865-0929 Series E-ISSN 1865-0937 作者: 道學(xué)氣 時(shí)間: 2025-3-31 12:00 作者: 喊叫 時(shí)間: 2025-3-31 13:46
1865-0929 II 2022, held in Jamshedpur, India. ICAII 2022 has been postponed to April 2023.?.The 23 papers were thoroughly reviewed and selected from the 86 submissions. They are arranged in topical sections on?.?.artificial Intelligence, and Internet of Things..978-3-031-37302-2978-3-031-37303-9Series ISSN 1865-0929 Series E-ISSN 1865-0937 作者: 口味 時(shí)間: 2025-3-31 18:55 作者: 著名 時(shí)間: 2025-3-31 22:03
