Using Mobilenets for Robust GoPiGo Detection
Toxic Language Detection using Robust Filters
... the detection of toxic ...a robust text classification to detect hate speech ...secondly, using the method of the ...toxic detection, the utmost importance is equally essential is model ...
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Robust circle detection using Harmony Search
... quantised into accumulator cells that are as small as possible or when the space needs to be enlarged to beyond the size of the image to allow for partial circle detection that may have centres that fall outside ...
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Robust Abandoned Object Detection Using Dual Foregrounds
... accurate detection of moving objects, which often fail for crowded scenarios, we present a pixelwise method that employs dual foregrounds to extract temporally static image ...online using a Bayesian update ...
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Robust VPE Detection using Automatically Parsed Text
... (NN balance) (NN sheet) )) Figure 1: Fragment of sentence from Treebank as possible candidates and then eliminates them using local syntactic information in a very simple way. It searches forwards within a short ...
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A Robust Approach for Detection of Brain Anomalies using MRI
... Abstract— Our brain is our body’s control center. It’s part of the nervous system, which also includes the spinal cord and a large network of nerves and neurons. The nervous system including brain controls everything ...
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Anomaly Detection Using Robust Principal Component Analysis
... Our manager also bears the responsibility of running mathematical analysis. It assists with easy experimentation of our algorithm, as explained in chapter 4. It is to be noted that feature generation occurs with Python ...
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Robust Adaptive Detection of Buried Pipes using GPR
... pipes using a Ground Penetrating Radar (GPR) is intricate for three main ...a detection method: (1) enhancing the signal of interest while reducing the noise and layer contributions, and (2) giving a local ...
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Anomaly Detection Using Robust Principal Component Analysis
... This matrix is then inserted into a mySQL table for easy manipulation of data. For example, join in each IP address to a vulnerability scan is one example that can be used in feature generation that would require that ...
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Robust Anomaly Detection in Videos Using Multilevel Representations
... To further understand the trained DAEs, we have a look at their filters and activations (Fig. 2). The filters at the low layer (the top row) usually describe colors and edges, for ex- ample, the filter in Fig. 2a ...
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Robust Tracking-by-Detection using a Detector Confidence Particle Filter
... Abstract We propose a novel approach for multi-person tracking- by-detection in a particle filtering framework. In addition to final high-confidence detections, our algorithm uses the continuous confidence of ...
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Robust Component-based Face Detection Using Color Feature
... VIII. CONCLUSION In this paper, a robust component face detection algorithm based on color features was presented. Proposed algorithm has a big benefit due to its computationally reduction. By applying ...
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Fast and Robust Hand Tracking Using Detection-Guided Optimization
... hand using a sin- gle depth camera. Our algorithm uses a novel detection- guided optimization strategy that increases the robustness and speed of pose ...the detection step, a ran- domized decision ...
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Robust Cross Lingual Hypernymy Detection Using Dependency Context
... of robust, unsuper- vised approaches for identifying cross-lingual hy- ...exhibits robust behavior along multiple ...embeddings using a parser trained on related lan- ...
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ROBUST FACE DETECTION USING COLOR SEGMENTATION AND ENERGY THRESHOLDING
... We propose to develop a model for face detection based on color segmentation. The color segmentation process will be followed by energy thresholding. The model tries to take advantage of face color correlation. ...
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Robust detection of ionospheric scintillations using MF DFA technique
... generated using the CEEMD technique for C/N 0 values of PRN 15 on 29 June 2013 sampled at 1 Hz ...ated using CEEMD matched with the inherent charac- teristics of the ...
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Detection of Outliers in Growth Curve Models: Using Robust Estimators
... both using for comparison of groups and making short term predictions could be badly affected by outliers in ...on robust test statistics, it is well-known that the obtained results could reflect the ...
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Robust Malware Detection for Internet of Things Using Deep Learning
... classify Robust Internet into several categories such as entertainment, society, tools, and productivity, multimedia and video, communication, puzzle and brain ...in Robust application by extracting four ...
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Robust Railway Track Crack Detection using MEMS Technology
... crack detection using MEMS accelerometer. The proposed detection system is a cost effective yet robust solution to the problem of railway crack detection utilizing a method that is ...
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Robust structural damage detection by using statistical hybrid algorithms
... Nevertheless, robust structural damage localization and identification can be achieved by integrating individual techniques through an ensemble architecture in order to increase the performance of the whole expert ...
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Heart rate variability analysis using robust period detection
... Metrics for assessing HRV are generally based on either time-domain (time series) or frequency-domain analysis. Several advanced filtering techniques (linear and non- linear) have been described in the literature, but ...
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