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Kedar Babu Madineni

from Santa Barbara, CA
Age ~56
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Also known as:
Kedar B Madineni, Kedar Babu I, Kedar I
Phone and address:
350 Magna Vista St, Santa Barbara, CA 93110
Related to:
Swapna Madineni, 51Sasank Madineni, 27
Connected to:
Cynthia K Mading, 57Trenton Mading, 39Sasanka Madiraju, 44Manini Madireddy, 40Neena Madireddy, 71Rajesh Madireddy, 42Sateesh Madireddy, 38Shyam Madireddy, 45Jane E Madis, 78Sidney Madise, 34

Kedar Madineni Phones & Addresses

  • 350 Magna Vista St, Santa Barbara, CA 93110
  • 4028 Invierno Dr, Santa Barbara, CA 93110
  • 7380 Elmhurst Pl, Goleta, CA 93117 (805) 968-7805
  • 7380 Elmhurst Pl #A, Goleta, CA 93117 (805) 968-7805
  • Baton Rouge, LA
  • 7380 Elmhurst Pl #A, Goleta, CA 93117 (916) 912-8838

Work

Position: Sales Occupations

Education

Degree: High school graduate or higher

Industries

Telecommunications

Resumes

Resumes

Kedar Madineni Photo 1

Kedar Madineni

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Location:
Santa Barbara, California Area
Industry:
Telecommunications

Publications

Us Patents

System And Method For Distributed Device Control

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US Patent:
20030037171, Feb 20, 2003
Filed:
Aug 16, 2001
Appl. No.:
09/931790
Inventors:
Kedar Madineni - Goleta CA, US
Koral Ilgun - Santa Barbara CA, US
International Classification:
G06F009/00
US Classification:
709/310000
Abstract:
System and method for distributed device control. The method may be implemented in the kernel of an operating system and may include receiving at least one request regarding at least one designated device of a plurality of devices from at least one application program. The request is then communicated to the designated device(s) via a well-known communication protocol. Information is then received from the designated device and forwarded to the application program that sent the request. The system may include a processor and a memory coupled to a bus, at least one application program, and a communications server integrated with an operating system. The communication server passes information between the application program and devices using a communication protocol. The communication protocol in the method and system may be the User Datagram Protocol/Internet Protocol (UDP/IP).

System And Method To Uniformly Access Devices

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US Patent:
20030037180, Feb 20, 2003
Filed:
Aug 16, 2001
Appl. No.:
09/931792
Inventors:
Kedar Madineni - Goleta CA, US
Koral Ilgun - Santa Barbara CA, US
International Classification:
G06F009/00
G06F009/46
US Classification:
709/321000
Abstract:
System and method to uniformly access devices. The method may include receiving at least one high-level request regarding at least one designated device of a plurality of devices from an application program, translating the high-level request to one or more low-level requests, and communicating the low-level request(s) to a device driver associated with one or more devices. The method may further include receiving a low-level message from a device, translating the low-level message to a high-level message, and forwarding the high-level message to the application program that sent the high-level request. The system may include a processor and a memory coupled to a bus, an application program, and a multiplexor to forward requests from the application program to a plurality of device drivers for corresponding devices, and to forward information received from the device drivers regarding the devices to the application program.

Neural Network And Classifier Selection Systems And Methods

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US Patent:
20220301274, Sep 22, 2022
Filed:
May 18, 2020
Appl. No.:
17/612557
Inventors:
- Goleta CA, US
Pierre M. Boulanger - Goleta CA, US
Justin Muncaster - Goleta CA, US
James Klingshirn - Goleta CA, US
Kedar Babu Madineni - Goleta CA, US
Louis Tremblay - Goleta CA, US
International Classification:
G06V 10/22
G06V 20/40
G06N 3/04
Abstract:
High resolution image target classification systems and methods include a proposal component configured to receive a first set data associated with a scene, the first set of data including at least one image of the scene, a multistage neural network comprising a plurality of neural networks, each neural network trained to receive a region of interest and output an object classification in accordance with an associated resource allocation, and an attention coordinator configured to determine regions of interest in the image and allocate each determined region to one of the plurality of neural networks from the multi-scale neural network, in accordance with available system resources. The system may be configured to optimize a probability of detecting objects in the image, while minimizing a number of pixels processed through the multi-scale neural network.
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Kedar Babu Madineni from Santa Barbara, CA, age ~56 Get Report