標(biāo)題: Titlebook: Deep Learning Theory and Applications; 4th International Co Donatello Conte,Ana Fred,Carlo Sansone Conference proceedings 2023 The Editor(s [打印本頁] 作者: 口語 時(shí)間: 2025-3-21 19:27
書目名稱Deep Learning Theory and Applications影響因子(影響力)
書目名稱Deep Learning Theory and Applications影響因子(影響力)學(xué)科排名
書目名稱Deep Learning Theory and Applications網(wǎng)絡(luò)公開度
書目名稱Deep Learning Theory and Applications網(wǎng)絡(luò)公開度學(xué)科排名
書目名稱Deep Learning Theory and Applications被引頻次
書目名稱Deep Learning Theory and Applications被引頻次學(xué)科排名
書目名稱Deep Learning Theory and Applications年度引用
書目名稱Deep Learning Theory and Applications年度引用學(xué)科排名
書目名稱Deep Learning Theory and Applications讀者反饋
書目名稱Deep Learning Theory and Applications讀者反饋學(xué)科排名
作者: GIST 時(shí)間: 2025-3-21 20:18
,A Study of?Neural Collapse for?Text Classification,this additional cluster represents an additional topic within the dataset, challenging the initial assumption of four distinct classes in AG News. This significant discovery suggests a promising research direction, where NC can serve as a tool for cluster discovery in semi-supervised learning scenarios.作者: 留戀 時(shí)間: 2025-3-22 03:23 作者: 準(zhǔn)則 時(shí)間: 2025-3-22 08:15
Zhongwei Gu,Youxiang Cui,Haibo Tang,Xiao Liue make use of convolutional neural networks (CNN) and various data-augmentation techniques. We showcase the results of this approach on the challenging . dataset, with the task of classifying between different primate species sounds, and report significantly higher Accuracy and UAR scores in contrast to comparatively equipped model baselines.作者: 宇宙你 時(shí)間: 2025-3-22 11:26 作者: intangibility 時(shí)間: 2025-3-22 12:59
Yun Liang,Junyi Mo,Yi Lu,Xing Yuan. Finally, we present an ablation study to validate our approach. We discovered that data2vec appears to be the best option if time and lightweightness are critical factors. On the other hand, wav2vec2phoneme is the most appropriate choice if overall performance is the primary criterion.作者: intangibility 時(shí)間: 2025-3-22 20:27
Improving Primate Sounds Classification Using Binary Presorting for Deep Learning,e make use of convolutional neural networks (CNN) and various data-augmentation techniques. We showcase the results of this approach on the challenging . dataset, with the task of classifying between different primate species sounds, and report significantly higher Accuracy and UAR scores in contrast to comparatively equipped model baselines.作者: thalamus 時(shí)間: 2025-3-23 00:59
An Automated Dual-Module Pipeline for Stock Prediction: Integrating N-Perception Period Power Stratlenges, we propose an automated pipeline consisting of two modules: an N-Perception period power strategy for identifying potential stocks and a sentiment analysis module using NLP techniques to capture market sentiment. By incorporating these methodologies, we aim to enhance stock prediction accuracy and provide valuable insights for investors.作者: Gesture 時(shí)間: 2025-3-23 02:40
,Phoneme-Based Multi-task Assessment of?Affective Vocal Bursts,. Finally, we present an ablation study to validate our approach. We discovered that data2vec appears to be the best option if time and lightweightness are critical factors. On the other hand, wav2vec2phoneme is the most appropriate choice if overall performance is the primary criterion.作者: 貞潔 時(shí)間: 2025-3-23 06:23
1865-0929 submissions. The scope of the conference includes such topics as models and algorithms; machine learning; big data analytics; computer vision applications; and natural language understanding..978-3-031-39058-6978-3-031-39059-3Series ISSN 1865-0929 Series E-ISSN 1865-0937 作者: 蠟燭 時(shí)間: 2025-3-23 10:09 作者: LATE 時(shí)間: 2025-3-23 16:22
Fátima Cruzalegui,Rony Cueva,Freddy Pazlyze what level of accuracy can be achieved, how much training data is required and how long the training process takes, when the neural network-based model is trained without symbolic knowledge vs. when different architectures of embedding symbolic knowledge into neural networks are used.作者: –吃 時(shí)間: 2025-3-23 21:55 作者: Brocas-Area 時(shí)間: 2025-3-23 23:34
Moralphilosophie im Kommunikationsdesignfeatures The experiments were conducted on a data set available on the UCI repository, which collects 756 different recordings. The results obtained are very encouraging, reaching an F-score of 95%, which demonstrates the effectiveness of the proposed approach.作者: 致詞 時(shí)間: 2025-3-24 04:59
Eric Koehler,Ara Jeknavorian,Stephen Klausxy10 dataset show that by using the pre-trained ViT model, we can get better accuracy compared to the ViT model built from scratch and do so with a faster training time. Experimental data further shows that the fine-tuned ViT model can achieve similar accuracy to the model built from scratch while using less training data.作者: 溫和女孩 時(shí)間: 2025-3-24 09:28
Calculation of Eddy Current Lossesrecision, and mean lag time while improving the performance of the base classifier. The SPNCD* algorithm provides a reliable solution for detecting concept drift in real-time streaming data, enabling practitioners to maintain their machine learning models’ performance in dynamic environments.作者: adj憂郁的 時(shí)間: 2025-3-24 13:41
,Towards Exploring Adversarial Learning for?Anomaly Detection in?Complex Driving Scenes,ages and videos with impressive results on simple data sets. Therefore, in this work, we investigate and provide insight into the performance of such techniques on a highly complex driving scenes dataset called Berkeley DeepDrive.作者: 沉積物 時(shí)間: 2025-3-24 15:50 作者: CAND 時(shí)間: 2025-3-24 20:28 作者: antenna 時(shí)間: 2025-3-25 01:40 作者: hangdog 時(shí)間: 2025-3-25 04:12
Conference proceedings 2023 Italy from 13 to 14 July 2023..The 9 full papers and 22 short papers presented were thoroughly reviewed and selected from the 42 qualified submissions. The scope of the conference includes such topics as models and algorithms; machine learning; big data analytics; computer vision applications; and 作者: bisphosphonate 時(shí)間: 2025-3-25 10:47 作者: 啟發(fā) 時(shí)間: 2025-3-25 13:02 作者: Gesture 時(shí)間: 2025-3-25 18:02 作者: 針葉類的樹 時(shí)間: 2025-3-25 20:47 作者: 簡潔 時(shí)間: 2025-3-26 00:36
Eric Koehler,Ara Jeknavorian,Stephen Klaustion module (WS-TAM). The features extracted from the individual streams are fed to train the modified MIL classifier by employing a novel temporal loss function. Finally, a fuzzy fusion method is used to aggregate the anomaly detection scores. To validate the performance of the proposed method, com作者: critique 時(shí)間: 2025-3-26 08:11
Design, User Experience, and Usabilityng both reveals that models tend to learn shortcut patterns from data. These patterns are hard to detect with current interpretability methods, such as input reductions. Our approach can help detect and eliminate spurious decision patterns during model development. Semantic extents can increase the 作者: Immobilize 時(shí)間: 2025-3-26 08:39 作者: 聯(lián)想記憶 時(shí)間: 2025-3-26 13:03
Yuanning Han,Yijing Zhang,Marcelo M. Soares the implementation of AL strategies with low effort and a fair data-driven comparison through defining and tracking experiment parameters (e.g., initial dataset size, number of data points per query step, and the budget). ALE helps practitioners to make more informed decisions, and researchers can 作者: invert 時(shí)間: 2025-3-26 20:31 作者: 符合你規(guī)定 時(shí)間: 2025-3-26 21:54 作者: 責(zé)任 時(shí)間: 2025-3-27 03:23
,Synthetic Network Traffic Data Generation and?Classification of?Advanced Persistent Threat Samples:metrics indicate successful generation and detection with an accuracy of 99.97% a recall rate of 99.94%, and 100% precision. Further results show a 99.97% . score for detecting APT samples in the synthetic data, and a Receiver Operator Characteristic Area Under the Curve (ROC_AUC) value of 1.0, indi作者: alabaster 時(shí)間: 2025-3-27 07:39 作者: DUCE 時(shí)間: 2025-3-27 12:59 作者: impaction 時(shí)間: 2025-3-27 15:35
,Research Data Reusability with?Content-Based Recommender System,te that the developed prototype content-based recommender system effectively provides relevant recommendations for research data repositories. The evaluation of the system using standard evaluation metrics shows that the system achieves an accuracy of 79% in recommending relevant items. Additionally作者: Paradox 時(shí)間: 2025-3-27 20:54
,MSDeepNet: A Novel Multi-stream Deep Neural Network for?Real-World Anomaly Detection in?Surveillanction module (WS-TAM). The features extracted from the individual streams are fed to train the modified MIL classifier by employing a novel temporal loss function. Finally, a fuzzy fusion method is used to aggregate the anomaly detection scores. To validate the performance of the proposed method, com作者: ODIUM 時(shí)間: 2025-3-28 00:31
,Explaining Relation Classification Models with?Semantic Extents,ng both reveals that models tend to learn shortcut patterns from data. These patterns are hard to detect with current interpretability methods, such as input reductions. Our approach can help detect and eliminate spurious decision patterns during model development. Semantic extents can increase the 作者: 長處 時(shí)間: 2025-3-28 05:16 作者: Insul島 時(shí)間: 2025-3-28 08:31
ALE: A Simulation-Based Active Learning Evaluation Framework for the Parameter-Driven Comparison of the implementation of AL strategies with low effort and a fair data-driven comparison through defining and tracking experiment parameters (e.g., initial dataset size, number of data points per query step, and the budget). ALE helps practitioners to make more informed decisions, and researchers can 作者: Innovative 時(shí)間: 2025-3-28 12:48 作者: Debrief 時(shí)間: 2025-3-28 18:00
Explainable Abnormal Time Series Subsequence Detection Using Random Convolutional Kernels, of randomly generated convolutional kernels and the use of the One-Class SVM algorithm. We tested our approach on voltage signals acquired during circular welding processes in hot water tank manufacturing, the results indicate that the approach achieves higher accuracy in detecting welding defects 作者: Horizon 時(shí)間: 2025-3-28 21:59
Lecture Notes in Computer Scienceal element in secured monitoring systems for networks and cybersecurity. This study investigates selected Generative Adversarial Network (GAN) architectures to generate realistic network traffic samples. It incorporates Extreme Gradient Boosting (XGBoost), an Ensemble Machine Learning algorithm effe作者: Analogy 時(shí)間: 2025-3-29 01:46 作者: dainty 時(shí)間: 2025-3-29 07:03
https://doi.org/10.1007/978-3-030-77025-9s take advantage of Artificial Intelligence (AI) techniques to perceive their environment. But these perceiving components could not be formally verified, since, the accuracy of such AI-based components has a high dependency on the quality of training data. So Machine learning (ML) based anomaly det作者: 陰謀 時(shí)間: 2025-3-29 11:07 作者: homeostasis 時(shí)間: 2025-3-29 14:57 作者: 濃縮 時(shí)間: 2025-3-29 18:14
Erschlie?ung und Virtualisierung der Weltinistic algorithms and AI models have been extensively explored, leveraging large historical datasets. Volatility and market sentiment play crucial roles in the development of accurate stock prediction models. We hypothesize that traditional approaches, such as n-moving averages, may not capture the作者: 使虛弱 時(shí)間: 2025-3-29 21:26 作者: 按時(shí)間順序 時(shí)間: 2025-3-30 02:43
Eric Koehler,Ara Jeknavorian,Stephen Klausmputer Vision. However, transformer models are very data-hungry, making them challenging to adopt in many applications where data is scarce. Using transfer learning techniques, we explore the classic Vision Transformer (ViT) and its ability to transfer features from the natural image domain to class作者: 四海為家的人 時(shí)間: 2025-3-30 04:21
Eric Koehler,Ara Jeknavorian,Stephen Klausews dataset?[.]. Initially, our findings indicate the occurrence of NC, which initially underperforms compared to a non-collapsed CNN. However, upon closer examination, we uncover an intriguing insight: certain data points converge towards an unknown cluster during NC. Further analysis reveals that 作者: concentrate 時(shí)間: 2025-3-30 10:58 作者: 制定 時(shí)間: 2025-3-30 14:48 作者: Infuriate 時(shí)間: 2025-3-30 19:56
Calculation of Eddy Current Lossesft detection methods often struggle with the trade-off between fast detection and low false alarm rates. This paper presents a novel concept drift detection algorithm, called SPNCD*, based on probabilistic methods, particularly Sum-Product Networks, that addresses this challenge by offering high det作者: 磨坊 時(shí)間: 2025-3-31 00:23 作者: 狗舍 時(shí)間: 2025-3-31 02:37 作者: 殺子女者 時(shí)間: 2025-3-31 07:29
Yuanning Han,Yijing Zhang,Marcelo M. Soaressignificance of red blood cell antibodies in transfusion candidates with intent to determine whether the patient needs to receive the expensive, rare, antigen-negative blood to avoid an acute hemolytic transfusion reaction that could lead to death. The assay requires a highly trained technician to s作者: 燈絲 時(shí)間: 2025-3-31 11:16 作者: dainty 時(shí)間: 2025-3-31 14:47
Guy-Serge Emmanuel,Francesca Politotion (ASR) models for low-resource languages. The study aims to evaluate the performance of recent state-of-the-art models for speech recognition in low-resource languages, such as Macedonian, where there are limited resources available for training or fine-tuning. The paper presents a methodology u作者: optic-nerve 時(shí)間: 2025-3-31 20:43 作者: adjacent 時(shí)間: 2025-4-1 00:54
Adriano Bernardo Renzi,Luiz Agnertor. Feature extraction can be accomplished by manually designing the features or by automatically learning them using a neural network. However, for the former, significant domain expertise is required to design features that are effective in accurately detecting anomalies, while in the latter, it 作者: 彩色 時(shí)間: 2025-4-1 01:55 作者: 消瘦 時(shí)間: 2025-4-1 06:43
