Python 代码实现 class Solution: def maxSlidingWindow(self, nums: List[int], k: int) -> List[int]: # 如果数组为空或 k = 0,直接返回空 if not nums or not k: return [] # 如果数组只有1个元素,直接返回该元素 if len(nums) == 1: return [nums[0]] # 初始化队列和结果,队...
We call this technique the Power Window (PW) method. Parameters and functions The carrier count used to define windows can be adjusted to fit different scenarios. There is a balance to strike, rooted in the currently available cohort sample size, between being able to home in on a specific ...
This paper presents a method for automatically detecting and analyzing offsets in GNSS (Global Navigation Satellite System) position time series using the RMS (Root Mean Square) sliding-window approach. This technique identifies anomalies that indicate offsets within the time series. ...
Implement a sliding-window technique and use trained classifier to search for vehicles in images Run the above steps on a video stream and create a heat map of recurring detections frame by frame to reject outliers and follow detected vehicles. Estimate a bounding box for vehicles detected. Pipel...
Histogram Sliding Technique - Learn about the Histogram Sliding technique, its applications, and how it can optimize image processing. Discover step-by-step implementation details.
The adaptive meshing technique in ABAQUS combines the features of pure Lagrangian analysis and pure Eulerian analysis. During the Lagrangian phase, the material moves with the mesh, and during the Eulerian phase, the mesh nodes are fixed in space, and the material flows through the mesh elements...
In the sliding window technique, we maintain a window that satisfies the problem constraints. The window is unstable if it violates the problem constraints, and it tries to stabilize by increasing or decreasing its size. Following are some of the commonly asked interview questions that use the sl...
These frames are convolved individually, stacked in chronological order, and then input into the BiGRU module for time-series modeling. The sliding window technique effectively addresses the sparsity issue of radar point cloud by expanding the original data along the time axis. By combining the ...
These frames are convolved individually, stacked in chronological order, and then input into the BiGRU module for time-series modeling. The sliding window technique effectively addresses the sparsity issue of radar point cloud by expanding the original data along the time axis. By combining the ...
Anomaly detection and a data imputation are necessary steps in a data monitoring system. Anomaly data can be detected if its values lie outside of a normal pattern distribution. We developed a median-based statistical outlier detection approach using a sliding window technique. In order to fill ...