Results 1 to 10 of about 1,795,661 (198)
K-Means Cloning: Adaptive Spherical K-Means Clustering [PDF]
Algorithms, 2018 We propose a novel method for adaptive K-means clustering. The proposed method overcomes the problems of the traditional K-means algorithm. Specifically, the proposed method does not require prior knowledge of the number of clusters.
Abdel-Rahman Hedar +3 more
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Exact Acceleration of K-Means++ and K-Means|| [PDF]
Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, 2021 K-Means++ and its distributed variant K-Means|| have become de facto tools for selecting the initial seeds of K-means. While alternatives have been developed, the effectiveness, ease of implementation,and theoretical grounding of the K-means++ and || methods have made them difficult to "best" from a holistic perspective.
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Barekeng, 2021 Mengembangkan wilayah untuk mengurangi kesenjangan dan menjamin pemerataan merupakan salah satu dari tujuh agenda Pembangunana RPJMN IV Tahun 2020-2024. Setiap wilayah tentunya memiliki potensi yang berbeda, baik potensi fisik maupun non-fisik. Perbedaan
Muhamad Budiman Johra
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t-k-means: A ROBUST AND STABLE k-means VARIANT [PDF]
ICASSP 2021 - 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2021 $k$-means algorithm is one of the most classical clustering methods, which has been widely and successfully used in signal processing. However, due to the thin-tailed property of the Gaussian distribution, $k$-means algorithm suffers from relatively poor performance on the dataset containing heavy-tailed data or outliers.
Li, Yiming +5 more
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Genetic K-means algorithm [PDF]
IEEE Transactions on Systems, Man and Cybernetics, Part B (Cybernetics), 1999 In this paper, we propose a novel hybrid genetic algorithm (GA) that finds a globally optimal partition of a given data into a specified number of clusters. GA's used earlier in clustering employ either an expensive crossover operator to generate valid child chromosomes from parent chromosomes or a costly fitness function or both.
Krishna, K, Murty, Narasimha M
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A Lightweight Crop Pest Detection Method Based on Convolutional Neural Networks
Applied Sciences, 2022 Existing object detection methods with many parameters and computations are not suitable for deployment on devices with poor performance in agricultural environments.
Zekai Cheng +5 more
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TSR-YOLO: A Chinese Traffic Sign Recognition Algorithm for Intelligent Vehicles in Complex Scenes
Sensors, 2023 Recognizing traffic signs is an essential component of intelligent driving systems’ environment perception technology. In real-world applications, traffic sign recognition is easily influenced by variables such as light intensity, extreme weather, and ...
Weizhen Song, Shahrel Azmin Suandi
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High-Performance Lightweight Fall Detection with an Improved YOLOv5s Algorithm
Machines, 2023 The aging population has drastically increased in the past two decades, stimulating the development of devices for healthcare and medical purposes. As one of the leading potential risks, the injuries caused by accidental falls at home are hazardous to ...
Yuanpeng Wang +4 more
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Optimized Cartesian K-Means [PDF]
IEEE Transactions on Knowledge and Data Engineering, 2015 Product quantization-based approaches are effective to encode high-dimensional data points for approximate nearest neighbor search. The space is decomposed into a Cartesian product of low-dimensional subspaces, each of which generates a sub codebook. Data points are encoded as compact binary codes using these sub codebooks, and the distance between two
Wang, Jianfeng +5 more
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The development of a GIS for New Deal Archaeology
Bulletin of the History of Archaeology, 2011 I have recently launched an effort to create a GIS of all New Deal-funded archaeological investigations conducted in the 48 states that comprised the USA during the Great Depression (Means 2011).
Bernard K. Means
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