標題: Titlebook: Artificial Intelligence and Soft Computing; 20th International C Leszek Rutkowski,Rafa? Scherer,Jacek M. Zurada Conference proceedings 2021 [打印本頁] 作者: INFER 時間: 2025-3-21 18:23
書目名稱Artificial Intelligence and Soft Computing影響因子(影響力)
書目名稱Artificial Intelligence and Soft Computing影響因子(影響力)學科排名
書目名稱Artificial Intelligence and Soft Computing網(wǎng)絡公開度
書目名稱Artificial Intelligence and Soft Computing網(wǎng)絡公開度學科排名
書目名稱Artificial Intelligence and Soft Computing被引頻次
書目名稱Artificial Intelligence and Soft Computing被引頻次學科排名
書目名稱Artificial Intelligence and Soft Computing年度引用
書目名稱Artificial Intelligence and Soft Computing年度引用學科排名
書目名稱Artificial Intelligence and Soft Computing讀者反饋
書目名稱Artificial Intelligence and Soft Computing讀者反饋學科排名
作者: mitten 時間: 2025-3-21 21:34
https://doi.org/10.1007/978-3-030-87897-9artificial intelligence; computer hardware; computer networks; computer science; computer systems; comput作者: 連鎖 時間: 2025-3-22 02:08 作者: CYN 時間: 2025-3-22 06:10 作者: NICE 時間: 2025-3-22 08:51 作者: 水土 時間: 2025-3-22 15:52 作者: Trypsin 時間: 2025-3-22 20:47
Karlheinz Lohs,Peter Elstner,Ursula Stephansification society’s standards which contain both non-destructive tests and visual surveys, to search structural damage, reliability, cracks, thickness measurement, and Water dripping generally documented by manually or with measurements tape. But, it is very hard to search cracks by visually monito作者: ear-canal 時間: 2025-3-22 23:28
https://doi.org/10.1007/b138937bject recognition. In this paper, we propose to present a technique for automatic filtering of cluttered surfaces. First, the technique clusters a point cloud and then based on three features that are size, distance and spatial information, cluttered surfaces are separated. To the best of our knowle作者: 使尷尬 時間: 2025-3-23 03:10 作者: 刪除 時間: 2025-3-23 09:36 作者: 薄膜 時間: 2025-3-23 13:31
https://doi.org/10.1007/b138937tremely high accuracy levels in many fields. However, they still encounter many challenges. In particular, the models are not explainable or easy to trust, especially in life and death scenarios. They may reach correct predictions through inappropriate reasoning and have biases or other limitations.作者: prodrome 時間: 2025-3-23 16:14 作者: Cosmopolitan 時間: 2025-3-23 21:36 作者: epicondylitis 時間: 2025-3-23 22:46
https://doi.org/10.1007/b138937 of an image using classical information requires a huge amount of computational resources. Hence, exploring techniques for representing images in a different information paradigm is important. This paper describes the variety of options for representing images in quantum information. Image processi作者: LAIR 時間: 2025-3-24 05:26 作者: Asperity 時間: 2025-3-24 06:34 作者: altruism 時間: 2025-3-24 11:54
https://doi.org/10.1007/b138937ected only during normal behaviors. We also consider the problem of detecting which group of sensors is most affected by the anomalous situation solving an open-set classification task. The proposed methods are domain independent and are based on a temporal analysis of data collected by the system. 作者: cogent 時間: 2025-3-24 15:02 作者: BLINK 時間: 2025-3-24 21:04
Karlheinz Lohs,Peter Elstner,Ursula Stephanction, classification, systems’ misbehaviour, etc. In this paper, we focus on generalizing the K-Means clustering approach when involving linear constraints on the clusters’ size. Indeed, to avoid local optimum clustering solutions which consists in empty clusters or clusters with few points, we pro作者: slipped-disk 時間: 2025-3-25 00:57
Teubner Reihe WirtschaftsinformatikThe method is especially useful for localizing objects in images. Here, we extend the method to the task of joint localization of several objects in a?2D-image by means of combining several centroids. The novel approach, i.e. joint optimization of several centroids and a?subsequent optimization of t作者: corpus-callosum 時間: 2025-3-25 04:15
Teubner Reihe Wirtschaftsinformatikfrom different groups are as dissimilar to each other as possible. The literature presents vast diversity on data clustering approaches, including systems that model the behavior of social individuals from different species. This work proposes a clustering algorithm that is reasoned upon the social 作者: 彩色 時間: 2025-3-25 10:31 作者: Melatonin 時間: 2025-3-25 12:35
Contextual Image Classification Through Fine-Tuned Graph Neural Networks from the advances in computational resources and the large volume of complex data (i.e., images). These factors led to an increase in the use of convolutional neural networks. However, such deep learning architectures do not appropriately explore the relationships between the data (e.g., images) an作者: 諷刺滑稽戲劇 時間: 2025-3-25 17:25
Architecture Monitoring and Reliability Estimation Based on DIP Technologysification society’s standards which contain both non-destructive tests and visual surveys, to search structural damage, reliability, cracks, thickness measurement, and Water dripping generally documented by manually or with measurements tape. But, it is very hard to search cracks by visually monito作者: 整潔漂亮 時間: 2025-3-25 21:38
An Efficient Technique for Filtering of 3D Cluttered Surfacesbject recognition. In this paper, we propose to present a technique for automatic filtering of cluttered surfaces. First, the technique clusters a point cloud and then based on three features that are size, distance and spatial information, cluttered surfaces are separated. To the best of our knowle作者: Debate 時間: 2025-3-26 01:56 作者: remission 時間: 2025-3-26 06:54
Multimodal Image Fusion Method Based on Multiscale Image Mattingource images. This paper proposes a multimodal image fusion method situated on image enhancement, edge detection, multiscale sliding window, and image matting to obtain the detailed region information of the input images. In the proposed system, firstly the multimodality input images are rectified v作者: Melodrama 時間: 2025-3-26 11:52 作者: depreciate 時間: 2025-3-26 15:45
RGB-D Odometry for Autonomous Lawn Mowingerating in various lawns placed in parks, airports, home gardens and many more. To ensure all navigation algorithms’ requirements are met, first accurate estimation of current position and orientation needs to be found. Scientists proposed many approaches using encoders, RADARs, LIDARs or vision/dep作者: 裂隙 時間: 2025-3-26 17:39
Using PMI to Rank and Filter Edges in Graphs of Wordsation, which must provide relevant information to the classifier. One of the most effective representation models uses graphs to represent documents. This paper presents an approach that uses this representation model but with weighted graphs. We propose to use a popular word association measure, th作者: Blood-Vessels 時間: 2025-3-26 21:34 作者: Parley 時間: 2025-3-27 02:31
Selecting the Optimal Configuration ofSwarm Algorithms for an NLP Task the optimal values for a set of parameters, based on a limited amount of training data. The starting point is a detailed analysis of generated solutions, which leads to a reformulation of the phrasing task. Based on this reformulation, the optimal swarm configuration is investigated, including the 作者: incite 時間: 2025-3-27 07:11
Active Learning Strategies and Convolutional Neural Networks forMammogram Classificationome domains present a shortage of both samples and labels, for instance, the medical area. In this work, we propose machine learning approaches that include traditional supervised classifiers and active learning methods for the breast lesion domain, in order to aid breast cancer diagnosis. We propos作者: ingrate 時間: 2025-3-27 12:11 作者: Archipelago 時間: 2025-3-27 17:30 作者: 爭論 時間: 2025-3-27 19:07
Constrained Clustering Problems: NewOptimization Algorithmsction, classification, systems’ misbehaviour, etc. In this paper, we focus on generalizing the K-Means clustering approach when involving linear constraints on the clusters’ size. Indeed, to avoid local optimum clustering solutions which consists in empty clusters or clusters with few points, we pro作者: jocular 時間: 2025-3-28 00:46
Robustness of Supervised Learning Based on Combined CentroidsThe method is especially useful for localizing objects in images. Here, we extend the method to the task of joint localization of several objects in a?2D-image by means of combining several centroids. The novel approach, i.e. joint optimization of several centroids and a?subsequent optimization of t作者: 瘙癢 時間: 2025-3-28 04:55 作者: 都相信我的話 時間: 2025-3-28 08:55 作者: JEER 時間: 2025-3-28 12:16
Architecture Monitoring and Reliability Estimation Based on DIP Technologyication system more portable and integrated, estimates the crack more precisely and reduction in expenditure as well. The proposed algorithm accuracy is 93.8% as compared to the traditional and recent work.作者: Arrhythmia 時間: 2025-3-28 16:12 作者: Pudendal-Nerve 時間: 2025-3-28 21:54 作者: FLACK 時間: 2025-3-29 01:24
Robustness of Supervised Learning Based on Combined Centroidsmization turns out to ensure robustness with respect to the presence of noise or occlusion in the images. Moreover, combining the optimized centroids yields more robust results than a method using simple centroids with a highly robust correlation coefficient (with a high breakdown point).作者: indecipherable 時間: 2025-3-29 03:17 作者: 某人 時間: 2025-3-29 10:25
Karlheinz Lohs,Peter Elstner,Ursula Stephannnections according to a given image context, which improves their efficiency and efficacy. We performed experiments considering different types of state-of-the-art deep features aggregated with the GNNs. The results demonstrate that our proposed method can achieve equal accuracy (statistically) to 作者: insincerity 時間: 2025-3-29 12:19
Karlheinz Lohs,Peter Elstner,Ursula Stephanication system more portable and integrated, estimates the crack more precisely and reduction in expenditure as well. The proposed algorithm accuracy is 93.8% as compared to the traditional and recent work.作者: Keratin 時間: 2025-3-29 19:34 作者: Abominate 時間: 2025-3-29 21:59 作者: 職業(yè)拳擊手 時間: 2025-3-30 03:43
Teubner Reihe Wirtschaftsinformatikmization turns out to ensure robustness with respect to the presence of noise or occlusion in the images. Moreover, combining the optimized centroids yields more robust results than a method using simple centroids with a highly robust correlation coefficient (with a high breakdown point).作者: indignant 時間: 2025-3-30 04:30
Conference proceedings 2021orithms and Their Applications..?.·??????? Artificial Intelligence in Modeling and Simulation..?.·??????? Computer Vision, Image and Speech Analysis..·??????? Data Mining..?..·??????? Various Problems of Artificial Intelligence..·??????? Bioinformatics, Biometrics and Medical Applications.作者: 艦旗 時間: 2025-3-30 12:06
Karlheinz Lohs,Peter Elstner,Ursula Stephanent of skin lesions asymmetry, along with various variations of the PH2 database. For the best CNN network, we achieved the following results: true positive rate for the asymmetry 92.31%, weighted accuracy 67.41%, F1 score 0.646 and Matthews correlation coefficient 0.533.作者: Condescending 時間: 2025-3-30 16:13 作者: 著名 時間: 2025-3-30 19:03
https://doi.org/10.1007/b138937 the corpus and attack the most important words in each sentence. The rating is global to the whole corpus and not to each specific data point. This method performs equal or better when compared to previous attack methods, and its running time is around 39 times faster than previous models.作者: 半身雕像 時間: 2025-3-30 21:00 作者: 時間等 時間: 2025-3-31 02:48
Karlheinz Lohs,Peter Elstner,Ursula Stephaneled training images, minimizing the specialist’s annotation effort. The validation of our proposed methodology is done on a public breast lesion-related dataset and our results show considerable accuracy gains over the traditional supervised learning approach and reductions of up?to . in the labeled training sets.作者: 有限 時間: 2025-3-31 05:15 作者: Graduated 時間: 2025-3-31 09:58 作者: fidelity 時間: 2025-3-31 14:48
A Computer Vision Based Approach forDriver Distraction Recognition Using Deep Learning and Genetic A technique achieves an accuracy of 96.37%, surpassing the previously obtained 95.98%, and on the State Farm Driver Distraction Dataset, on which we attain an accuracy of 99.75%. The 6-Model Ensemble gave an inference time of 0.024?s as measured on our machine with Ubuntu 20.04(64-bit) and GPU as GeForce GTX 1080.作者: lanugo 時間: 2025-3-31 21:03 作者: hermetic 時間: 2025-4-1 00:12 作者: 散步 時間: 2025-4-1 02:35
Active Learning Strategies and Convolutional Neural Networks forMammogram Classificationeled training images, minimizing the specialist’s annotation effort. The validation of our proposed methodology is done on a public breast lesion-related dataset and our results show considerable accuracy gains over the traditional supervised learning approach and reductions of up?to . in the labeled training sets.作者: Neuropeptides 時間: 2025-4-1 08:14
Exploiting Time Dynamics for One-Class and Open-Set Anomaly Detection boats and water treatment plants (SWaT dataset). Quantitative results on these datasets show that our approach achieves comparable results with respect to state of the art approaches and promising results for open-set classification.作者: cumber 時間: 2025-4-1 13:06 作者: 四溢 時間: 2025-4-1 14:57 作者: 鬼魂 時間: 2025-4-1 20:06
