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1. 发明申请

US20190050692A1 CONTEXT-BASED DIGITAL SIGNAL PROCESSING 审中-公开
公开(公告)号：US20190050692A1
公开(公告)日：2019-02-14
申请号：US15855763
申请日：2017-12-27
申请人： Vinod Sharma , Monica Martinez-Canales , Peggy Jo Irelan , Malini Krishnan Bhandaru , Rita Chattopadhyay , Soila Pertet Kavulya
发明人： Vinod Sharma , Monica Martinez-Canales , Peggy Jo Irelan , Malini Krishnan Bhandaru , Rita Chattopadhyay , Soila Pertet Kavulya
IPC分类号： G06K9/62 , G06K9/00 , G06K9/66 , G06K9/20
CPC分类号： G06K9/6292 , G06K9/00805 , G06K9/00825 , G06K9/00845 , G06K9/209 , G06K9/66
摘要： Various systems and methods for implementing context-based digital signal processing are described herein. An object detection system includes a processor to: access sensor data from a first sensor and a second sensor integrated in a vehicle; access an operating context of the vehicle; assign a first weight to a first object detection result from sensor data of the first sensor, the first weight adjusted based on the operating context; assign a second weight to a second object detection result from sensor data of the second sensor, the second weight adjusted based on the operating context; and perform a combined object detection technique by combining the first object detection result weighted by the first weight and the second object detection result weighted by the second weight.

2. 发明申请

US20190049560A1 LIDAR-BASED OBJECT DETECTION AND CLASSIFICATION 审中-公开
公开(公告)号：US20190049560A1
公开(公告)日：2019-02-14
申请号：US16103674
申请日：2018-08-14
申请人： Rita Chattopadhyay , Monica Lucia Martinez-Canales
发明人： Rita Chattopadhyay , Monica Lucia Martinez-Canales
IPC分类号： G01S7/48 , G06N99/00 , G01S17/42
摘要： Various systems and methods for implementing LiDAR-based object detection and classification are described herein. An object detection system includes a feature extraction and object identification (FEOI) circuit to: receive segmented data of an environment around the object detection system, the segmented data obtained using a light imaging detection and ranging (LiDAR) system, oriented with respect to a direction of travel; compute spatial and structural parameters of a segment of the segmented data; and use the spatial and structural parameters with a machine learning model to obtain a classification of the segment.

3. 发明申请

US20170178329A1 DETERMINING VALUES OF ANGULAR GAUGES 审中-公开
公开(公告)号：US20170178329A1
公开(公告)日：2017-06-22
申请号：US14979016
申请日：2015-12-22
申请人： Rita Chattopadhyay , Anne M. Russell , Nikhil Jog , David M. Bayba , Ravindra V. Narkhede
发明人： Rita Chattopadhyay , Anne M. Russell , Nikhil Jog , David M. Bayba , Ravindra V. Narkhede
IPC分类号： G06T7/00 , G01B11/26 , G01D13/22
CPC分类号： G01D13/22 , G01B11/26 , G06T7/00 , G06T7/70 , G06T2207/10016 , G06T2207/20036 , G06T2207/30108
摘要： In various embodiments, an angular gauge reporting system (“AGRS”) may determine one or more values from an image of an angular gauge. The AGRS may receive one or more images of the gauge and develop an angular map to determine values indicated by the gauge. The AGRS may identify numbers in the image to generate the angular map. The AGRS may determine a center for the angular gauge. The AGRS may determine numerical values by processing capture images of the angular gauge though angular or linear interpolation of values. By generating the angular map prior to later determination of values, the AGRS may provide for determination of numerical values without requiring repetition of actions which may be computationally complex or resource intensive. Other embodiments may be described and/or claimed.

4. 发明申请

US20220214170A1 SCENE INTELLIGENCE FOR COLLABORATIVE SEMANTIC MAPPING WITH MOBILE ROBOTS 有权
公开(公告)号：US20220214170A1
公开(公告)日：2022-07-07
申请号：US17704934
申请日：2022-03-25
申请人： Ruchika Singh , Mandar Chincholkar , Hassnaa Moustafa , Francesc Guim Bernat , Rita Chattopadhyay
发明人： Ruchika Singh , Mandar Chincholkar , Hassnaa Moustafa , Francesc Guim Bernat , Rita Chattopadhyay
IPC分类号： G01C21/16 , G01C21/00 , G06N20/20
摘要： Various aspects of techniques, systems, and use cases include provide instructions for operating an autonomous mobile robot (AMR). A technique may include capturing audio or video data using a sensor of the AMR, performing a classification of the audio or video data using a trained classifier, and identifying a coordinate of an environmental map corresponding to a location of the audio or video data. The technique may include updating the environmental map to include the classification as metadata corresponding to the coordinate. The technique may include communicating the updated environmental map to an edge device.

5. 发明申请

US20170089692A1 MONITORING OF GAUGES 审中-公开
公开(公告)号：US20170089692A1
公开(公告)日：2017-03-30
申请号：US14864635
申请日：2015-09-24
申请人： Rita Chattopadhyay , Anne M. Russell , David M. Bayba , Gary Godding
发明人： Rita Chattopadhyay , Anne M. Russell , David M. Bayba , Gary Godding
IPC分类号： G01B11/26 , G01D18/00 , G01D13/22 , G06K9/00 , G06K9/78
CPC分类号： G01B11/26 , G01D13/22 , G01D18/00 , G06F11/00 , G06K9/00771 , G06K9/78 , G06K2209/03 , H04W4/70
摘要： Methods, systems, and storage media for monitoring a gauge are disclosed herein. In an embodiment, an image processing module may receive a digital image of a gauge to identify an analog value indicator of the gauge and to form an indicator representation corresponding to the analog value indicator. A geometric analysis module may determine from the indicator representation a geometric characteristic corresponding to the analog value indicator and an indicated gauge value. Other embodiments may be disclosed and/or claimed.

6. 发明申请

US20080181457A1 Video based monitoring system and method 审中-公开
标题翻译：视频监控系统及方法
公开(公告)号：US20080181457A1
公开(公告)日：2008-07-31
申请号：US12009313
申请日：2008-01-17
申请人： Rita Chattopadhyay , Archana Kalyansundar
发明人： Rita Chattopadhyay , Archana Kalyansundar
IPC分类号： G06K9/00
CPC分类号： G06K9/38 , G06K9/00771
摘要： There is described a video based monitoring system and method. The system comprises an image acquisition module, a movement detection module, and a stationary object detection module. The movement detection module is adapted for detecting the presence of a moving object in a region of interest of said captured video image. The stationary object detection module is adapted for detecting the presence of a stationary object in said region of interest and operable when said movement detection module fails to detect a moving object in a region of interest of a current frame of the captured image. The stationary object detection module includes a pixel-by-pixel comparison module adapted to determine the number of pixels in the region of interest in the current frame whose pixel values match with that of corresponding pixels in an immediately preceding frame. The stationary object detection module further includes a background identification module adapted to identify those pixels in the region of interest in the current frame that form part of a background, based upon a comparison of their pixel values with a background pixel value. The system further includes means for generating a signal to indicate detection of a stationary object when the number of matches between the current frame and the immediately preceding frame exceeds a threshold value after discounting those pixels in the current frame that are identified to be part of the background.
摘要翻译：描述了基于视频的监控系统和方法。该系统包括图像采集模块，移动检测模块和静止物体检测模块。所述运动检测模块适于检测所述拍摄视频图像的感兴趣区域中的移动物体的存在。固定物体检测模块适于在所述感兴趣区域中检测静止物体的存在，并且当所述移动检测模块未能检测到所捕获图像的当前帧的感兴趣区域中的移动物体时可操作。固定物体检测模块包括逐像素比较模块，其适于确定当前帧中的像素值与紧邻的前一帧中的相应像素的像素值相匹配的感兴趣区域中的像素数。固定物体检测模块还包括背景识别模块，其适于基于其像素值与背景像素值的比较来识别形成背景的一部分的当前帧中的感兴趣区域中的那些像素。所述系统还包括用于当折扣当前帧中的当前帧和前一帧之间的匹配数目超过阈值时产生用于指示静止对象的检测的信号的装置，所述当前帧中的那些像素被识别为是背景。

7. 发明申请

US20220113698A1 AUTONOMOUS MOBILE ENTITY (AME) RISK MONITORING AND MANEUVERING SYSTEMS 有权
公开(公告)号：US20220113698A1
公开(公告)日：2022-04-14
申请号：US17556925
申请日：2021-12-20
申请人： Florian Mirus , Fabian Oboril , Frederik Pasch , Cornelius Buerkle , Kay-Ulrich Scholl , Ruchika Singh , Rita Chattopadhyay , Rony Ferzli , Thierry Beaumont
发明人： Florian Mirus , Fabian Oboril , Frederik Pasch , Cornelius Buerkle , Kay-Ulrich Scholl , Ruchika Singh , Rita Chattopadhyay , Rony Ferzli , Thierry Beaumont
IPC分类号： G05B19/4061 , G05B19/418
摘要： Various systems and methods for detecting risk conditions in a physical workspace. An apparatus can include an interface to receive smart sensor signals from at least one autonomous mobile entity (AME) in the physical workspace. The apparatus can also include processing circuitry coupled to the interface to detect a risk condition associated with the at least one AME, based on the smart sensor signals, relative to a user device associated with a human present in the physical workspace. The processing circuitry can also detect a direction of the risk condition relative to the user device and cause a notification to the first user device. The notification can indicate the direction of the risk condition relative to the user device. Other systems, methods and apparatuses are described.

8. 发明申请

US20200311559A1 OPTIMIZED DECISION TREE MACHINE LEARNING FOR RESOURCE-CONSTRAINED DEVICES 审中-公开
公开(公告)号：US20200311559A1
公开(公告)日：2020-10-01
申请号：US16902063
申请日：2020-06-15
申请人： Rita Chattopadhyay , Rajesh Bansal , Yuming Ma , Mrittika Ganguli
发明人： Rita Chattopadhyay , Rajesh Bansal , Yuming Ma , Mrittika Ganguli
IPC分类号： G06N5/00 , G06N5/04 , G06N20/00
摘要： In one embodiment, an edge computing device for performing decision tree training and inference includes interface circuitry and processing circuitry. The interface circuitry receives training data and inference data that is captured, at least partially, by sensor(s). The training data corresponds to a plurality of labeled instances of a feature set, and the inference data corresponds to an unlabeled instance of the feature set. The processing circuitry: computes a set of feature value checkpoints that indicate, for each feature of the feature set, a subset of potential feature values to be evaluated for splitting tree nodes of a decision tree model; trains the decision tree model based on the training data and the set of feature value checkpoints; and performs inference using the decision tree model to predict a target variable for the unlabeled instance of the feature set.

9. 发明申请

US20180189453A1 AUTOMATIC PREDICTION OF PATIENT LENGTH OF STAY AND DETECTION OF MEDICAL CENTER READMISSION DIAGNOSES 审中-公开
公开(公告)号：US20180189453A1
公开(公告)日：2018-07-05
申请号：US15396075
申请日：2016-12-30
申请人： Rita Chattopadhyay , Kalpana A. Algotar , Amith Harsha , Ravindra V. Narkhede
发明人： Rita Chattopadhyay , Kalpana A. Algotar , Amith Harsha , Ravindra V. Narkhede
IPC分类号： G06F19/00 , G06F17/30
CPC分类号： G16H50/20 , G16H10/60 , G16H40/20
摘要： Systems, apparatuses and methods may provide for technology that assigns confidence levels to data bins containing similarity data and length of stay data, wherein the similarity data and the length of stay data correspond to a plurality of previous admissions. Additionally, the confidence levels may be weighted based on a distribution metric that assigns higher weights to denser regions. A length of stay of a target admission may be predicted based on the weighted confidence levels.

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