標(biāo)題: Titlebook: Data Engineering and Intelligent Computing; Proceedings of ICICC Vikrant Bhateja,Suresh Chandra Satapathy,V. N. Man Conference proceedings [打印本頁(yè)] 作者: 婉言 時(shí)間: 2025-3-21 19:24
書(shū)目名稱(chēng)Data Engineering and Intelligent Computing影響因子(影響力)
書(shū)目名稱(chēng)Data Engineering and Intelligent Computing影響因子(影響力)學(xué)科排名
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書(shū)目名稱(chēng)Data Engineering and Intelligent Computing網(wǎng)絡(luò)公開(kāi)度學(xué)科排名
書(shū)目名稱(chēng)Data Engineering and Intelligent Computing被引頻次
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書(shū)目名稱(chēng)Data Engineering and Intelligent Computing讀者反饋
書(shū)目名稱(chēng)Data Engineering and Intelligent Computing讀者反饋學(xué)科排名
作者: 熱心助人 時(shí)間: 2025-3-21 21:40 作者: 心胸狹窄 時(shí)間: 2025-3-22 03:55 作者: Suggestions 時(shí)間: 2025-3-22 04:36 作者: 瘋狂 時(shí)間: 2025-3-22 09:43 作者: palliate 時(shí)間: 2025-3-22 13:59
Conference proceedings 2021mmunication (ICICC 2020) organized by?the?Department of Computer Science and Engineering and?the?Department of Computer Science and Technology, Dayananda Sagar University, Bengaluru, India, on 18–20 September 2020. The book is organized in two volumes and discusses advanced and multi-disciplinary re作者: palliate 時(shí)間: 2025-3-22 20:04 作者: 表臉 時(shí)間: 2025-3-22 23:47 作者: 樸素 時(shí)間: 2025-3-23 02:12
https://doi.org/10.1007/978-3-031-12063-3hm was tested on 266 MLO views from miniMIAS and 74CC views from local hospital. The pectoral muscle was detected with accuracy of 97%, and detected nipple position was acceptable in 93.67% of mammograms with average error of 5.755?mm with location annotated by a radiologist.作者: elastic 時(shí)間: 2025-3-23 09:18
https://doi.org/10.1007/978-94-009-4285-1is fighting. The experiments are conducted by using 500 crime scene videos collected from Internet. The experimental results shows that proposed architecture yields 90% of accuracy. Further, the results are compared with existing architectures.作者: Torrid 時(shí)間: 2025-3-23 11:45 作者: perpetual 時(shí)間: 2025-3-23 17:01
2.2?Evidence-Based Patient Carer a fixed time duration. In this paper, the ANN tool is used to find out the prediction accuracy level of the accessibility of the wireless cellular network. For this purpose, key performance indicators (KPIs) data are acquired from the real field measurement of approximately 50,000 BTS locations by the Nokia Network Pvt. Ltd., India.作者: 小卷發(fā) 時(shí)間: 2025-3-23 20:44
4.2?Effective Interdisciplinary Teamsd efficiently. This approach is tested on colorectal cancer histology image dataset which contains 5000 labeled images belonging to eight different classes. In our result, fine-tuning with early stopping performed better than other methods with accuracy of 91.2%.作者: bypass 時(shí)間: 2025-3-23 23:57
Clinical Informatics Study Guiderithm with negative sampling is used to apply the machine learning concept in a better way. Through simulation results, it is cleared that number of accidents will reduce after applying the proposed concept.作者: micturition 時(shí)間: 2025-3-24 04:26 作者: 革新 時(shí)間: 2025-3-24 10:20
Heuristic Approach to Detect Pectoral Muscle and Nipple in Mammogram for Computer-Aided Diagnosis,hm was tested on 266 MLO views from miniMIAS and 74CC views from local hospital. The pectoral muscle was detected with accuracy of 97%, and detected nipple position was acceptable in 93.67% of mammograms with average error of 5.755?mm with location annotated by a radiologist.作者: adroit 時(shí)間: 2025-3-24 11:03 作者: Cholesterol 時(shí)間: 2025-3-24 18:39 作者: extract 時(shí)間: 2025-3-24 21:44
Predicting the Accuracy of Accessibility of LTE Network Using ANN,r a fixed time duration. In this paper, the ANN tool is used to find out the prediction accuracy level of the accessibility of the wireless cellular network. For this purpose, key performance indicators (KPIs) data are acquired from the real field measurement of approximately 50,000 BTS locations by the Nokia Network Pvt. Ltd., India.作者: beta-cells 時(shí)間: 2025-3-25 00:21 作者: Morose 時(shí)間: 2025-3-25 07:16 作者: 大笑 時(shí)間: 2025-3-25 07:34
Identifying Handwriting Difficulties in Children in Devanagari Script Using Machine Learning, identify children with dysgraphia and without dysgraphia in Devanagari script based on their performance characteristics as per the BHK algorithm. 52 students handwriting samples were collected, and feature analysis is done based on BHK and machine learning model using the KNN algorithm for the predictions.作者: 聯(lián)邦 時(shí)間: 2025-3-25 12:29
https://doi.org/10.1007/978-3-031-45249-9ining purposes, deep learning classifier bidirectional long short-term memory (BiLSTM) network is used. Results established that despite using few channels, recognition accuracy does not vary to a large extent. We achieved almost the same accuracy level by selecting less number of optimal frontal channels.作者: PET-scan 時(shí)間: 2025-3-25 18:49
2194-5357 he environment and industry. Further, the book also addresses the deployment of emerging computational and knowledge transfer approaches, optimizing solutions in various disciplines of science, technology and?health care.978-981-16-0170-5978-981-16-0171-2Series ISSN 2194-5357 Series E-ISSN 2194-5365 作者: macabre 時(shí)間: 2025-3-25 20:16 作者: 尖 時(shí)間: 2025-3-26 01:12
Lecture Notes in Computer Scienceinput. The convolutional neural networks-based classification model proves accuracy of 93% in discriminate from malware and benign files. The convolutional neural network-based malware detection model has higher performance when compared with deep neural network classification model trained with GIS作者: 在駕駛 時(shí)間: 2025-3-26 05:40
Lecture Notes in Computer Scienceie reviews. Sentiment analysis is a natural language processing approach to identify the emotional tone behind the opinion text from negative to a positive level. This technique uses fine-grained sentiment analysis that provides a more precise level of polarity by breaking it from very negative to v作者: 擁護(hù)者 時(shí)間: 2025-3-26 10:48 作者: Ptsd429 時(shí)間: 2025-3-26 15:01 作者: 虛情假意 時(shí)間: 2025-3-26 18:54
Clinical In Vitro Fertilizationoal is to leverage deep learning visualization techniques for better interpretation of our results. Overall, our proposed model achieved a competitive MAE of 7.61?months on the test set provided by Radiological Society of North America (RSNA).作者: 分離 時(shí)間: 2025-3-27 00:04 作者: 歸功于 時(shí)間: 2025-3-27 04:17 作者: 洞穴 時(shí)間: 2025-3-27 08:19
4.2?Effective Interdisciplinary Teamserent settings has shown that only classes.dex files of apks are sufficient for Android malware detection. The proposed deep learning framework with convolutional neural networks could achieve 97.76% accuracy in detecting Android malware with minimal information requirement.作者: CHECK 時(shí)間: 2025-3-27 12:38
Malware Family Classification Model Using Convolutional Neural Network,s proposed. Malware family recognition is formulated as a multi-classification task, and an accurate solution is obtained by training convolutional neural network with images of malware executable files. Ten families of malware have been considered here for building the models. The image dataset wit作者: bypass 時(shí)間: 2025-3-27 15:02
Malware and Benign Detection Using Convolutional Neural Network,input. The convolutional neural networks-based classification model proves accuracy of 93% in discriminate from malware and benign files. The convolutional neural network-based malware detection model has higher performance when compared with deep neural network classification model trained with GIS作者: 不在灌木叢中 時(shí)間: 2025-3-27 19:13 作者: LATE 時(shí)間: 2025-3-28 00:13
Plant Health Report Through Advanced Convolution Neural Network Methodology,ble of identifying the disease with higher efficiency and is able to suggest the measures that farmers can take to avoid the pest infection and diseases that have been identified in their plants, to grow a healthy plant for high yield. The disease detection is done using the classifier present in th作者: vector 時(shí)間: 2025-3-28 05:53 作者: defeatist 時(shí)間: 2025-3-28 07:58
Pediatric Skeletal Age Assessment Using Deep Learning Proceedings,oal is to leverage deep learning visualization techniques for better interpretation of our results. Overall, our proposed model achieved a competitive MAE of 7.61?months on the test set provided by Radiological Society of North America (RSNA).作者: critic 時(shí)間: 2025-3-28 10:40
A Novel Model for Disease Identification in Mango Plant Leaves Using Multimodal Conventional and Te of the diseases using conventional methods is time consuming, and there can be over usage of chemicals to overcome the diseases. The technological methods along with conventional methods can be used to identify the diseases efficiently and treat the disease time and cost effectively. This paper giv作者: 現(xiàn)暈光 時(shí)間: 2025-3-28 15:34 作者: groggy 時(shí)間: 2025-3-28 18:56 作者: 愛(ài)了嗎 時(shí)間: 2025-3-29 00:24 作者: 間諜活動(dòng) 時(shí)間: 2025-3-29 03:44
,Design of LSTM–CNN with Feature Map Merge for Crime Scene Detection in CCTV Footage,ssness may prone to miss the important crimes that are been recorded. There are two existing architectures for detecting crimes and human activities such as 3D CNN and two-stream CNN. The drawbacks of the existing techniques are that it is unable to capture the complete local features and the accura作者: 領(lǐng)巾 時(shí)間: 2025-3-29 09:48 作者: uveitis 時(shí)間: 2025-3-29 14:26 作者: 猛然一拉 時(shí)間: 2025-3-29 17:24 作者: Ondines-curse 時(shí)間: 2025-3-29 23:04
Sentiment Analysis for Movie Ratings Using Deep Learning,oogle, Twitter, IMDB, shopping sites, and online review sites. This growing availability of opinion-rich resources leads to a new technology that is concerned with what other people think and their emotions. This textual data may have rich information with various labels such as sentiment, age, coun作者: endocardium 時(shí)間: 2025-3-30 01:23 作者: 實(shí)現(xiàn) 時(shí)間: 2025-3-30 06:32
,Performance Analysis of Dijkstra’s and the A-Star Algorithm on an Obstacle Map, majorly to be found in the presence of obstacles; these obstacles can be even a ball that is present in a play area or it can be houses that are present on a map which act like as a blockade through which the object cannot be passed and a deviation needs to be taken to get to the destination. The s作者: agitate 時(shí)間: 2025-3-30 08:48
Automated Microaneurysms Detection in Fundus Images for Early Diagnosis of Diabetic Retinopathy,sm is a common sign of diabetic retinopathy, which appears as a red lesion in the fundus image. This paper deals with the classification of microaneurysms and non-microaneurysms. The proposed work follows four steps, specifically pre-processing, candidate extraction, extraction of texture features f作者: FUSE 時(shí)間: 2025-3-30 14:26
Plant Health Report Through Advanced Convolution Neural Network Methodology,e detection in plants for effective development of the plant health monitoring system for farm fields. ?It is possible to obtain the pattern of a specific disease and the characteristics of a deficiency using the?Convolution Neural Network (CNN) algorithm, which employs approximately 128 filters; th作者: CRAB 時(shí)間: 2025-3-30 19:21 作者: 全面 時(shí)間: 2025-3-30 20:41
Pediatric Skeletal Age Assessment Using Deep Learning Proceedings, is normal or delayed compared to the patient’s chronological age (CA). A delayed or advanced bone age can indicate growth disorders. It is generally performed by using either the Greulich & Pyle (G&P) method or the Tanner–Whitehouse (TW) method. However, inter- and intra-observer differences occur 作者: 作嘔 時(shí)間: 2025-3-31 01:05 作者: STENT 時(shí)間: 2025-3-31 07:14 作者: 注視 時(shí)間: 2025-3-31 10:38 作者: tenosynovitis 時(shí)間: 2025-3-31 15:44 作者: debunk 時(shí)間: 2025-3-31 21:15
Histopathological Image Classification Using Deep Neural Networks with Fine-Tuning,issue subtypes, but it has many challenges like complexity of image, labeled data availability. Overcoming these challenges and accurately classifying the images require better approach than traditional one. In this work, we use fine-tuning-based deep neural network in classifying the histopathologi作者: alliance 時(shí)間: 2025-4-1 00:24 作者: 定點(diǎn) 時(shí)間: 2025-4-1 02:54
Identifying Handwriting Difficulties in Children in Devanagari Script Using Machine Learning, in holding a pencil, alignment, differentiating the strokes, curves, and sizing of the alphabets, etc. It is more challenging in scripts where there are more alphabets, curves, and strokes. In India, about 75% of school-going kids write in Devanagari script (includes Hindi, Marathi, Gujarati) as a 作者: Relinquish 時(shí)間: 2025-4-1 07:28
https://doi.org/10.1007/978-981-16-0171-2ICICC 2020; Intelligent Soft Computing; Data Engineering; Machine Learning; Data Science; Intelligent For
