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...
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...
Learn about the Histogram Sliding technique, its applications, and how it can optimize image processing. Discover step-by-step implementation details.
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...
Nevertheless, the sliding window technique strongly increases the computational effort as the classifier has to verify a large number of object candidates. This paper proposes a sliding window approach which also uses depth information from a stereo camera. This leads to a greatly decreased number of...
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 ...
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...
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. ...
We proposed a combination of MAD and the sliding window technique to capture irregular data behaviors in a specific time frame. Hence, anomaly points were detected locally over a specified window using the prediction interval. With a statistical characteristic of MAD, a superior performance was ...
We proposed a combination of MAD and the sliding window technique to capture irregular data behaviors in a specific time frame. Hence, anomaly points were detected locally over a specified window using the prediction interval. With a statistical characteristic of MAD, a superior performance was ...