Method Detects(方法检测)研究综述
Method Detects 方法检测 - We show that the existing portfolio optimization methods with high order moments can misclassify inefficient portfolios as efficient, while our method detects the actual efficient set. [1] Applied to a market for school milk, our method detects a known cartel and calculates that it has high cohesion and exclusivity. [2] This method detects the concentration of methanol using spectroscopy. [3] Different from the existing results, this method detects the replay attack without sacrificing any system performances in normal systems. [4] The method detects and measures the length and angularity of any straight edge of over the image. [5] This method detects the features regions that describe the geometry of the surface. [6] This method detects the binarized side image of the paper at the suspected position by using a rectangular template to eliminate the false detection position and recover the missed detection position. [7]我们表明，现有的具有高阶矩的投资组合优化方法可以将低效的投资组合误分类为有效的，而我们的方法检测的是实际的有效集。 [1] 应用于学校牛奶市场，我们的方法检测到已知的卡特尔并计算出它具有高凝聚力和排他性。 [2] 该方法使用光谱法检测甲醇的浓度。 [3] 与现有结果不同的是，该方法在不牺牲正常系统中的任何系统性能的情况下检测重放攻击。 [4] 该方法检测和测量图像上任何直边的长度和角度。 [5] 此方法检测描述表面几何形状的特征区域。 [6] 该方法利用矩形模板对可疑位置的纸张二值化侧图像进行检测，消除误检位置，恢复漏检位置。 [7]
Proposed Method Detects 建议的方法检测
In addition, the proposed method detects even when two faults occur at the same time. [1] In the second stage, the proposed method detects candidate’s pixels that are in the range of skin color. [2] The proposed method detects HIF depending on the amount of even harmonics present in the voltage waveforms measured by SMs. [3] The proposed method detects symmetries through simple inversion, concatenation and reflection operations on the chains, thus allowing the classification of symmetrical and asymmetrical contours. [4] From the experimental results, the proposed method detects falling status with 96. [5] The simulation results show that the proposed method detects the attacks more accurately when compared to the existing methods. [6] Specifically, the proposed method detects the abnormal agitation power and the abnormal substrate supply at 47 h and 86 h, respectively. [7] The proposed method detects overloaded IoT signals via convex optimization approach named sum of complex sparse regularizers (SCSR) taking advantage of both the discreteness and the sparsity of the SC-CP IoT signal. [8] We have experimented with the proposed method on two datasets, and confirmed that the proposed method detects moving objects with higher accuracy than other methods. [9] The proposed method detects locally damaged members of the entire structure by comparing the stress variations before and after damage. [10] In the course of broad experimentation we demonstrate that the proposed method detects the Wormhole attacks and reduces the overhead required if the network size increases. [11] Results demonstrated that the proposed method detects edges more efficiently and accurately in comparison to state of the art edge detection algorithms. [12] The proposed method detects and classify possible faulty IC conditions with improved accuracy and can also help in early prevention remotely before complete circuit failure. [13] As the proposed method detects fault by utilising local voltages and currents, its reliability is better than the previous algorithms. [14] The proposed method detects wheel slip phenomenon by wheel slip velocity and wheel acceleration. [15] Furthermore, the proposed method detects and prices the electricity theft which is occurred between electric poles. [16] Finally, the experiment results show that the proposed method detects the moving object from the high-speed video sequence images precisely and effectively. [17] The proposed method detects straight and curved sections that are estimated to be lanes using the Hough transform. [18] The proposed method detects tomato peduncles based on a point cloud taken by an RGBD camera. [19] Firstly, the proposed method detects the relationship between three-phase winding inductances by injecting the high-frequency detection signal into motor windings in a coupling way, and the initial rotor position is determined into two sectors with 180 degrees electric angle difference. [20] Results show that the proposed method detects outliers over streaming data with higher accuracy than SOD_GPU algorithm proposed in 7516110, even when concept drifts occur. [21] The proposed method detects falls of elderly people automatically using the result of action recognition. [22] The proposed method detects infectious diseases in a given individual with maximum accuracy, speed and is highly reliable and robust in disease detection. [23] Experimental results demonstrate that the proposed method detects and estimates leaks early and accurately. [24] The results show that the proposed method detects more outbreaks than benchmark methods suggested recently and is robust against badly chosen parameters. [25] A case study in ultraprecision machining indicates that this proposed method detects the formation and sweeping away of built-up edge phenomenon with minimal time delay. [26] The results demonstrate that the proposed method detects different types of statistical biases in two different algorithms without prior knowledge of these biases. [27] The proposed method detects the R point and QRS interval in units of a sliding window for real-time processing and combines the detected R points in each sliding window. [28] The proposed method detects STCOPs against the null hypothesis that the spatiotemporal distributions of different features are independent of each other. [29] The proposed method detects shot boundaries by employing combo feature set (PCC and CM). [30] The experimental results show that our proposed method detects the lane on the road surface accurately in several brightness conditions. [31] Using this feature, the proposed method detects individual vehicles and calculates the vehicle speed. [32] The proposed method detects a pictogram accurately by using a deep-learning based object detection algorithm and the results of detection are matched the table of pictogram interpretation in Korean. [33] Compared with traditional computer vision techniques that are based on edge features for crack detection, the proposed method detects the breathing behavior of fatigue cracks; therefore, it is able to distinguish true cracks from crack-like features and structural boundaries. [34] The proposed method detects six types of sidewalk: asphalt, gravel, lawn, grass, sand, and mat, imitating snowy sidewalk. [35] Comparing with root-mean-square (RMS) calculation-based methods, the proposed method detects the fault at least twice faster, with minimal system resources. [36] A structural analysis on various supercritical fluids shows that the proposed method detects the influence of the attractive interaction on the structural transition of supercritical fluids. [37] Experimental results show that the proposed method detects insecure debug port, timing channel and hardware Trojans that cause violation of important security properties such as confidentiality, integrity and isolation and also derives the trigger condition of hardware Trojans. [38] The analysis of obtained simulation results with the proposed TSPM establishes that the proposed method detects and isolates the attackers efficiently. [39] Experimental results show that our proposed method detects periodontal infection with 94. [40] Proposed method detects checkerboard corner candidates by utilizing 1-dimensional gaussian filters with succeeding corner refinement process to remove outliers from corner candidates and accurately detect checkerboard corners in sub-pixel unit. [41] The proposed method detects straight lines that are estimated to be lanes using the Hough transform. [42] Additionally, the proposed method detects the malicious data in the IoT network and estimates the location in case of sensor faults. [43] According to experiments with the real fabric images and defects types that have not been learned, the proposed method detects fabric defects with 96. [44] The results demonstrate that the proposed method detects nuclei and leukocytes with Dice score of 0. [45] The simulation results show that the proposed method detects the attacks more accurately when compared to the existing methods. [46] Experimental results show that the proposed method detects with high accuracy than most of vehicle tail light detection algorithms that using a single classifier. [47] The proposed method detects the failure of the master controller and try to migrate its connected switches to slave controllers. [48] Based on this idea, the proposed method detects anomalies by directly isolating anomaly pixels from background. [49] Our proposed method detects and analyzes different parts of human sperms. [50]此外，即使两个故障同时发生，所提出的方法也能检测到。 [1] 在第二阶段，所提出的方法检测候选者在肤色范围内的像素。 [2] 所提出的方法根据 SM 测量的电压波形中存在的偶次谐波量来检测 HIF。 [3] 所提出的方法通过对链的简单反转、连接和反射操作来检测对称性，从而允许对对称和非对称轮廓进行分类。 [4] 从实验结果来看，所提出的方法以 96 检测跌倒状态。 [5] 仿真结果表明，与现有方法相比，该方法更准确地检测到攻击。 [6] 具体来说，所提出的方法分别在 47 小时和 86 小时检测到异常的搅拌功率和异常的基板供应。 [7] 所提出的方法利用 SC-CP 物联网信号的离散性和稀疏性，通过称为复稀疏正则化器 (SCSR) 和的凸优化方法检测过载的物联网信号。 [8] 我们在两个数据集上对所提出的方法进行了实验，并证实所提出的方法比其他方法更准确地检测运动物体。 [9] 所提出的方法通过比较损伤前后的应力变化来检测整个结构的局部损伤构件。 [10] 在广泛的实验过程中，我们证明了所提出的方法可以检测到虫洞攻击，并在网络规模增加时减少所需的开销。 [11] 结果表明，与最先进的边缘检测算法相比，所提出的方法更有效、更准确地检测边缘。 [12] 所提出的方法以更高的准确性检测和分类可能的故障 IC 条件，并且还可以帮助在电路完全故障之前进行远程早期预防。 [13] 由于所提出的方法利用本地电压和电流检测故障，其可靠性优于以前的算法。 [14] 该方法通过车轮打滑速度和车轮加速度检测车轮打滑现象。 [15] 此外，所提出的方法检测并定价发生在电线杆之间的电力盗窃。 [16] 最后，实验结果表明，该方法能够准确有效地从高速视频序列图像中检测出运动目标。 [17] 所提出的方法使用霍夫变换检测估计为车道的直线和弯曲部分。 [18] 所提出的方法基于 RGBD 相机拍摄的点云检测番茄花序梗。 [19] 首先，该方法通过将高频检测信号以耦合方式注入电机绕组中，检测三相绕组电感之间的关系，将转子初始位置确定为两个具有180度电角差的扇区。 [20] 结果表明，即使发生概念漂移，所提出的方法也能比 7516110 中提出的 SOD_GPU 算法更准确地检测流数据中的异常值。 [21] nan [22] nan [23] nan [24] nan [25] nan [26] nan [27] nan [28] nan [29] nan [30] nan [31] nan [32] nan [33] nan [34] nan [35] nan [36] nan [37] nan [38] nan [39] nan [40] nan [41] 所提出的方法使用霍夫变换检测估计为车道的直线。 [42] nan [43] nan [44] nan [45] nan [46] nan [47] nan [48] 基于这个想法，所提出的方法通过直接从背景中分离异常像素来检测异常。 [49] nan [50]
My Method Detects 我的方法检测
Our method detects abrupt shifts regardless of their origin (which it cannot deduce). [1] Our method detects a higher number of basal icequakes, has a lower rate of incorrectly identifying crevassing as basal icequakes and detects an additional, spatially independent basal icequake cluster. [2] Our method detects the center of gravity of a marked spherical instrument tip in the stereoscopic image pair of a digital surgical microscope and triangulates points in 3D space of the calibrated stereo system. [3] Our method detects the MFF-based attacks by measuring the consistency between the LBP histogram and the real facial texture feature. [4] Our method detects human poses in the camera images and then models walking persons as vertical sticks. [5] Our method detects changes in transcript dynamics and in overall gene abundance in large numbers of cells to determine differential expression. [6] Our method detects the user's stroked finger through machine learning that uses the measured EMG. [7] Our method detects such codewords with an arbitrary number of spikes, does so from small data sets, and accounts for dependencies in occurrences of codewords. [8] Our method detects remarkable points in time series based on patterns. [9]我们的方法检测突然变化，而不管它们的起源（它无法推断）。 [1] 我们的方法检测到更多的基础冰震，错误地将裂缝识别为基础冰震的比率较低，并检测到一个额外的、空间独立的基础冰震群。 [2] 我们的方法在数字手术显微镜的立体图像对中检测标记的球形仪器尖端的重心，并对校准立体系统的 3D 空间中的点进行三角测量。 [3] 我们的方法通过测量 LBP 直方图和真实面部纹理特征之间的一致性来检测基于 MFF 的攻击。 [4] nan [5] 我们的方法检测大量细胞中转录动力学和整体基因丰度的变化，以确定差异表达。 [6] nan [7] nan [8] nan [9]
Detection Method Detects 检测方法检测
Acoustic detection method detects the hidden as well as moving insects by amplifying and filtering their motility and feeding sounds. [1] Experimental results show that our proposed detection method detects strep throats with 93. [2] The distance-based outlier detection method detects the implied outliers by calculating the distance of the points in the dataset, but the computational complexity is particularly high when processing multidimensional datasets. [3] The one-stage object detection method detects and recognizes the objects in the scenes. [4]声学检测方法通过放大和过滤昆虫的运动和进食声音来检测隐藏和移动的昆虫。 [1] 实验结果表明，我们提出的检测方法用 93 检测到链球菌性喉炎。 [2] nan [3] nan [4]
Novel Method Detects 新方法检测
The novel method detects higher harmonics of the motor input current and adjusts the excitation frequency pulling the motor away from the nonlinear behaviors and stabilizing the vibration amplitudes. [1] Thus, we need to understand why this novel method detects such high levels. [2] The standard venous pressure alarm used in clinical routine only detects 50% of the VNDs, whereas the novel method detects all VNDs and has a false alarm rate of 0. [3]新方法检测电机输入电流的高次谐波并调整励磁频率，使电机远离非线性行为并稳定振动幅度。 [1] 因此，我们需要了解为什么这种新方法可以检测到如此高的水平。 [2] nan [3]
Screening Method Detects 筛查方法检测
The screening method detects changes in the fluorescence of reduced nicotinamide adenine dinucleotide (NADH) at 340 nm using a microplate reader when 2-KLG is degraded by 2-KLG reductase. [1] RESULTS This screening method detects numerous strains of bacteria with collagenolytic properties, including the collagenolytic species that have been implicated previously in anastomotic leak. [2]当 2-KLG 被 2-KLG 还原酶降解时，该筛选方法使用酶标仪检测还原型烟酰胺腺嘌呤二核苷酸 (NADH) 在 340 nm 处的荧光变化。 [1] 结果 这种筛选方法可检测多种具有胶原分解特性的细菌菌株，包括先前与吻合口漏有关的胶原分解物种。 [2]
method detects change 方法检测变化
The screening method detects changes in the fluorescence of reduced nicotinamide adenine dinucleotide (NADH) at 340 nm using a microplate reader when 2-KLG is degraded by 2-KLG reductase. [1] Our method detects changes in transcript dynamics and in overall gene abundance in large numbers of cells to determine differential expression. [2]当 2-KLG 被 2-KLG 还原酶降解时，该筛选方法使用酶标仪检测还原型烟酰胺腺嘌呤二核苷酸 (NADH) 在 340 nm 处的荧光变化。 [1] 我们的方法检测大量细胞中转录动力学和整体基因丰度的变化，以确定差异表达。 [2]
method detects anomaly 方法检测异常
This method detects anomaly areas to analyze temporal and spatial changes of an area where a personal movement during a flooding event differs from that during regular times from personal location data. [1] Based on this idea, the proposed method detects anomalies by directly isolating anomaly pixels from background. [2]该方法检测异常区域，从个人位置数据分析洪水事件期间人员移动与常规时间不同区域的时空变化。 [1] 基于这个想法，所提出的方法通过直接从背景中分离异常像素来检测异常。 [2]
method detects straight 方法检测直
The proposed method detects straight and curved sections that are estimated to be lanes using the Hough transform. [1] The proposed method detects straight lines that are estimated to be lanes using the Hough transform. [2]所提出的方法使用霍夫变换检测估计为车道的直线和弯曲部分。 [1] 所提出的方法使用霍夫变换检测估计为车道的直线。 [2]