Results 11 to 20 of about 14,277,947 (281)
Improved Guarantees for k-means++ and k-means++ Parallel
CoRR, 2020 In this paper, we study k-means++ and k-means++ parallel, the two most popular algorithms for the classic k-means clustering problem. We provide novel analyses and show improved approximation and bi-criteria approximation guarantees for k-means++ and k-means++ parallel.
Konstantin Makarychev +2 more
openaire +3 more sources
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
doaj +1 more source
, 2022 S k-means program was developed by a team led by Quang-Van DOAN at the Center for Computational Sciences (CCS), the University of Tsukuba. S k-means can be used by any person or entity for any purpose without any fee or charge.
Van Doan
core +1 more source
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
doaj +1 more source
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
doaj +1 more source
On $k$-means for segments and polylines
CoRR, 2023 18 pages, 3 ...
Cabello, S., Giannopoulos, P.
openaire +6 more sources
CoRR, 2020 This paper presents a novel accelerated exact k-means algorithm called the Ball k-means algorithm, which uses a ball to describe a cluster, focusing on reducing the point-centroid distance computation. The Ball k-means can accurately find the neighbor clusters for each cluster resulting distance computations only between a point and its neighbor ...
Shuyin Xia +6 more
openaire +2 more sources
, 2023 This paper presents two novel deterministic initialization procedures for k-means clustering based on a modified crowding distance. The procedures, named ck-means and fck-means, use more crowded points as initial centroids.
Abdesslem Layeb
core +1 more source
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
doaj +1 more source
Algorithms, 2020 Two new initialization methods for K-means clustering are proposed. Both proposals are based on applying a divide-and-conquer approach for the K-means‖ type of an initialization strategy. The second proposal also uses multiple lower-dimensional subspaces
Joonas Hämäläinen +2 more
doaj +1 more source