標題: Titlebook: Data Management, Analytics and Innovation; Proceedings of ICDMA Neha Sharma,Amol C. Goje,Alfred M. Bruckstein Conference proceedings 2024 T [打印本頁] 作者: 面臨 時間: 2025-3-21 19:39
書目名稱Data Management, Analytics and Innovation影響因子(影響力)
書目名稱Data Management, Analytics and Innovation影響因子(影響力)學(xué)科排名
書目名稱Data Management, Analytics and Innovation網(wǎng)絡(luò)公開度
書目名稱Data Management, Analytics and Innovation網(wǎng)絡(luò)公開度學(xué)科排名
書目名稱Data Management, Analytics and Innovation被引頻次
書目名稱Data Management, Analytics and Innovation被引頻次學(xué)科排名
書目名稱Data Management, Analytics and Innovation年度引用
書目名稱Data Management, Analytics and Innovation年度引用學(xué)科排名
書目名稱Data Management, Analytics and Innovation讀者反饋
書目名稱Data Management, Analytics and Innovation讀者反饋學(xué)科排名
作者: 寵愛 時間: 2025-3-21 20:30
esearchers because of poor visual clarity. Further, in densely populated areas, the low contrast of the built-up areas causes huge difficulty in the detection of roof-tops individually. In view of such challenges, we develop a Mask-RCNN model for segmentation of probable built-up areas in low-resolu作者: 完全 時間: 2025-3-22 02:33
o test the performance of our proposed system, we used several machine learning algorithms like Support Vector Machines (SVMs) and Random Forest (RF) algorithms. Here, these algorithms are mainly used for diagnosing mental health disorders on the basis of given input (i.e. verified dataset of sympto作者: 老巫婆 時間: 2025-3-22 06:15
two main stages: feature extraction and speech recognition. The feature extraction stage involves the use of the VGGish model to process the raw audio signals and create a feature representation that is both concise and comprehensive. The resulting feature vectors capture various acoustic attribute作者: 隱藏 時間: 2025-3-22 10:45 作者: 陳舊 時間: 2025-3-22 12:59
g pothole detection model, built upon YOLO V8, has been proposed. Additionally, road quality and PHR mapping via sensory data (accelerometer and gyrometer), which undergoes post-processing to provide quality observations for various vehicles and classify them, has been introduced. Leveraging this da作者: 陳舊 時間: 2025-3-22 20:49
learning-based 3D facial reconstruction algorithm with motion capture data to produce high-quality facial animation. We evaluate our method by comparing it to traditional animation methods and show that our approach produces more realistic and natural facial expressions. Our results demonstrate the 作者: ANA 時間: 2025-3-22 23:08
,An revolution?re Traditionen anknüpfen,inopathy (NPDR), or proliferative diabetic retinopathy (PDR), from a healthy eyeball to a proliferative diabetic retinopathy presence. Remarkably, our approach attains an impressive 93.5% accuracy, bolstering the model‘s reliability in diabetic retinopathy diagnosis from fundus images. With potentia作者: Extemporize 時間: 2025-3-23 01:36 作者: Devastate 時間: 2025-3-23 08:32 作者: 小歌劇 時間: 2025-3-23 12:19
Denial, Projection, and the Empathic Wall Starting from understanding human psychology, decoding different human emotions based, and providing proper affective response, HCI plays a very crucial role. The paper investigates various types of human emotions, the sources to identify it and various HCI traditional to modern techniques which pr作者: Clinch 時間: 2025-3-23 16:36 作者: 健壯 時間: 2025-3-23 19:57 作者: Astigmatism 時間: 2025-3-24 00:36
A Two-Stage CNN Based Satellite Image Analysis Framework for Estimating Building-Count in Residentiesearchers because of poor visual clarity. Further, in densely populated areas, the low contrast of the built-up areas causes huge difficulty in the detection of roof-tops individually. In view of such challenges, we develop a Mask-RCNN model for segmentation of probable built-up areas in low-resolu作者: Charlatan 時間: 2025-3-24 03:52
Mental Health Prediction Using Artificial Intelligence,o test the performance of our proposed system, we used several machine learning algorithms like Support Vector Machines (SVMs) and Random Forest (RF) algorithms. Here, these algorithms are mainly used for diagnosing mental health disorders on the basis of given input (i.e. verified dataset of sympto作者: 針葉類的樹 時間: 2025-3-24 08:35
VGGish Deep Learning Model: Audio Feature Extraction and Analysis, two main stages: feature extraction and speech recognition. The feature extraction stage involves the use of the VGGish model to process the raw audio signals and create a feature representation that is both concise and comprehensive. The resulting feature vectors capture various acoustic attribute作者: 破裂 時間: 2025-3-24 14:30 作者: 幼稚 時間: 2025-3-24 17:59
,Trigger-Based Pothole Detection, and?Warning System with?RQ and?PHR Mapping,g pothole detection model, built upon YOLO V8, has been proposed. Additionally, road quality and PHR mapping via sensory data (accelerometer and gyrometer), which undergoes post-processing to provide quality observations for various vehicles and classify them, has been introduced. Leveraging this da作者: Stress 時間: 2025-3-24 21:36 作者: Intrepid 時間: 2025-3-25 02:29 作者: 老巫婆 時間: 2025-3-25 04:17 作者: 得罪人 時間: 2025-3-25 10:12 作者: 窩轉(zhuǎn)脊椎動物 時間: 2025-3-25 12:23 作者: 大喘氣 時間: 2025-3-25 15:48 作者: ABASH 時間: 2025-3-25 20:18
Boosting Tiny Object Detection in Complex Backgrounds Through Deep Multi-Instance Learning,y objects. Moreover, our work represents the first empirical study on detecting small objects from complex backgrounds using (multi-instance learning) MIL. Additionally, our solution improves the accuracy and speed of multi-stage methods by incorporating multiple architectural enhancements.作者: 不近人情 時間: 2025-3-26 02:17
2367-3370 and solutions for future development.Serves as a reference .This book presents the latest findings in the areas of data management and smart computing, big data management, artificial intelligence, and data analytics, along with advances in network technologies. The book is a collection of peer-rev作者: 我沒有命令 時間: 2025-3-26 06:55
Improving Sentiment Analysis by Handling Negation on Twitter Data Using Deep Learning Approaches,omparing CNN‘s performance in managing negation words, the paper assesses its effectiveness on tweet data. This strategy achieves superior accuracy over traditional machine learning methods and therefore mitigates misclassification in tweets.作者: Glucocorticoids 時間: 2025-3-26 10:59 作者: 機構(gòu) 時間: 2025-3-26 16:03 作者: Medicare 時間: 2025-3-26 17:27 作者: 效果 時間: 2025-3-26 23:50 作者: 領(lǐng)先 時間: 2025-3-27 04:34 作者: Exaggerate 時間: 2025-3-27 05:50 作者: 鬼魂 時間: 2025-3-27 10:08
https://doi.org/10.1007/978-1-4939-0348-1ther a client will subscribe to term insurance, drawing insights from a multitude of contributing factors. The primary emphasis of this research lies in highlighting the efficacy and elegance of ensemble learning algorithms in addressing predictive tasks.作者: Duodenitis 時間: 2025-3-27 15:44
Einführung in die Probleml?sunguishing steps. (1) Take an image from an OCR-based source dataset and extract features to create a new image with no text in it. (2) Use this newly formed collection of synthetic images which is very similar to the original images for fine-tuning.作者: 宣稱 時間: 2025-3-27 20:48
Comprehensive Survey of Nonverbal Emotion Recognition Techniques,res, and body posture-based emotion. This paper systematically analyzes various ways of nonverbal communication, emotions expressed through it, its autorecognition, available techniques, its performance and provides a methodical survey of the existing literature based on various aspects.作者: HUSH 時間: 2025-3-27 23:35
Forecast of Energy Demand Using Temporal Fusion Transformer,r (RMSE) in predicting future energy consumption. The paper indicates that the TFT model can be an effective tool for accurate and reliable time series forecasting in various industries, including energy and finance.作者: 手勢 時間: 2025-3-28 03:45 作者: 最小 時間: 2025-3-28 06:23
Analysis of Regular Machine Learning and Ensemble Learning Approaches for Term Insurance Predictionther a client will subscribe to term insurance, drawing insights from a multitude of contributing factors. The primary emphasis of this research lies in highlighting the efficacy and elegance of ensemble learning algorithms in addressing predictive tasks.作者: Grievance 時間: 2025-3-28 10:31 作者: 品嘗你的人 時間: 2025-3-28 17:32
efficient while giving scientists, planners, and decision-makers access to a variety of valuable data for effective policy and decision-making. Change detection in satellite images is a key application area of the proposed system.作者: BOOR 時間: 2025-3-28 22:39 作者: 耐寒 時間: 2025-3-29 02:49 作者: 疲憊的老馬 時間: 2025-3-29 07:03 作者: UNT 時間: 2025-3-29 10:38
Forecast of Energy Demand Using Temporal Fusion Transformer, novelty of TFT model lies in combining the strengths of recurrent and convolutional neural networks, ultimately resulting in improved accuracy in forecasting. The dataset used in this study consists of data on power consumption per quarter hour of 370 consumers, over a four-year period. The results作者: 愛管閑事 時間: 2025-3-29 14:04
Mental Health Prediction Using Artificial Intelligence,ms to predict the type of Mental Disorder using Artificial Intelligence, specifically the Random Forest Algorithm which is known for its effectiveness in classification tasks. The motivation for this study is the lack of a model which can accurately predict the type of mental health disorder of any 作者: tariff 時間: 2025-3-29 19:00
VGGish Deep Learning Model: Audio Feature Extraction and Analysis, One of the key challenges in speech recognition systems is the efficient extraction of discriminative features from raw audio signals which directly impacts their performance. This study recommends a distinct method to enhance the precision and resilience of speech recognition systems in which audi作者: spinal-stenosis 時間: 2025-3-29 20:11
Stacking Ensemble-Based Approach for Sarcasm Identification with Multiple Contextual Word Embeddingwever, relying exclusively on a singular word embedding approach can hinder our capacity to capture the intricate interconnections between words within texts. To address this issue, this paper introduces a stacking ensemble model for sarcasm detection that harnesses the strengths of multiple context作者: GEM 時間: 2025-3-30 03:50 作者: 放逐某人 時間: 2025-3-30 04:22 作者: paltry 時間: 2025-3-30 12:13 作者: Bravado 時間: 2025-3-30 15:00 作者: 慢慢沖刷 時間: 2025-3-30 16:38
Deep Learning for MRI-Based Brain Tumour Identification and Classification,cal image processing software helps find brain tumours in MRI data. This study segmented and detected brain tumours using MRI sequence images. This process is complicated by the similarity of normal tissues and the wide range of tumour tissues in different patients. Brain tumour detection is the mai作者: 旁觀者 時間: 2025-3-30 20:49 作者: Altitude 時間: 2025-3-31 03:10
Analysis of Regular Machine Learning and Ensemble Learning Approaches for Term Insurance Prediction spans various domains, including business models, scientific research, banking, medical applications, and industrial applications. To address these multifaceted challenges, a plethora of predictive mechanisms have been developed and explored. This paper undertakes a comprehensive comparison and ana作者: GLUE 時間: 2025-3-31 05:34
Platform Independent Satellite Image Processing Using GPGPU,pret and use information efficiently. Traditional methods for processing such data need a lot of time and resources. The proposed system seeks to identify significant changes in environmental parameters using various image processing techniques while allowing hardware and operating system independen作者: Contracture 時間: 2025-3-31 10:21 作者: 微枝末節(jié) 時間: 2025-3-31 13:59
An Enhanced Deep Learning Method to Generate Synthetic Images with Features That are Comparable to rial perspective, using these pre-trained models to attain such results mostly falls short. The main reasons are the data-hungry architecture and the limited amount of available data that is used for retraining these models. In this study, we discuss a deep learning method that generates synthetic d作者: oracle 時間: 2025-3-31 20:30 作者: crutch 時間: 2025-3-31 21:56
Comparative Analysis of Deep Learning Models for Car Part Image Segmentation,diagnostics and maintenance to insurance claim assessments. In this study, we present a quantitative approach to car part segmentation, by evaluating and comparing the power of YOLOv8, the Detectron2 Mask R-CNN with Resnet 101 and Mask R-CNN with ResNeXt 101 32×8d configuration+FPN Backbone architec作者: reperfusion 時間: 2025-4-1 04:27
Boosting Tiny Object Detection in Complex Backgrounds Through Deep Multi-Instance Learning,on and multi-instance learning (MIL). Conventional MIL models often underperform when the assumption of negative bags containing solely negative instances and positive bags containing at least one positive instance is violated, which commonly occurs during MIL for object detection. Additionally, det作者: institute 時間: 2025-4-1 06:52 作者: NIB 時間: 2025-4-1 10:55 作者: 禮節(jié) 時間: 2025-4-1 16:37
s one of that. Humans are able to express emotions through verbal and nonverbal ways. Emotions communicated through nonverbal ways have gained much more popularity in recent times due to recent technological developments. Such type of communication mainly includes facial expressions, hand gestures, 作者: 離開就切除 時間: 2025-4-1 19:08 作者: 不怕任性 時間: 2025-4-1 23:14
