Realization of OpenCL based CNN Implementation on FPGA using SDAccel Platform

Chaurasiya, Abhishek; Shekhawat, Abhay Pratap Singh; Chaurasiya, Pawan; Patel, Preet; Pal, Prashant; Singh, Shashank; Bansod, Saurabh

doi:10.1109/incoft55651.2022.10094321

2022 International Conference on Futuristic Technologies (INCOFT) 2022

DOI: 10.1109/incoft55651.2022.10094321

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Realization of OpenCL based CNN Implementation on FPGA using SDAccel Platform

Abhishek Chaurasiya¹,

Abhay Pratap Singh Shekhawat²,

Pawan Chaurasiya³

et al.

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2023

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Cited by 2 publications

References 8 publications

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Advancing Prosthetic Arm Technology with Enhanced Aesthetics Integrating EMG Based Signals, 3D Printing and Tactile Sensors

Palthi,

Arug,

Gugulothu

et al. 2023

Preprint

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Enhancing prosthetic arm technology by integrating electromyography (EMG) signals, 3D printing, and tactile sensors to improve aesthetics, accuracy, and latency. The combination of these technologies has the potential to revolutionize prosthetic arm functionality by providing a more intuitive and responsive experience for users. The EMG-based signals enable high accuracy control over the prosthetic arm, allowing complex movements such as grasping and releasing objects. 3D printing technology allows for customized prosthetic arms that fit the user's unique physical characteristics with low latency, providing better comfort and functionality while allowing for aesthetically pleasing designs. Tactile sensors provide valuable feedback to the user with low latency, improving control and interaction with the surrounding environment. Our research shows that this system is effective in improving prosthetic arm functionality and appearance with high accuracy and low latency. The potential for further development and integration of these technologies to create more aesthetically pleasing prosthetic devices with improved accuracy and low latency is discussed. Integrating EMG-based signals, 3D printing, and tactile sensors with a focus on aesthetics, high accuracy, and low latency holds significant promise for advancing prosthetic arm technology. Future research should focus on enhancing these technologies for real-world applications.

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Advancing Prosthetic Arm Technology with Enhanced Aesthetics Integrating EMG Based Signals, 3D Printing and Tactile Sensors

Palthi,

Arug,

Gugulothu

et al. 2023

Preprint

View full text Add to dashboard Cite

show abstract

Virtual Assistant and Navigation for Visually Impaired using Deep Neural Network and Image Processing

Bhukhya¹,

Bhumireddy²,

Palakonalu³

et al. 2023

Preprint

Self Cite

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The quick development of technology promotes the use of the resources that are at hand to make simpler daily tasks and improve the standard and quality of life for those who are blind. This module suggests creating a system of virtual assistant glasses to help the visually impaired navigate around them. An obstacle detection module built into the device uses computer vision to find obstacles and inform the user through haptic feedback. The system also has a text recognition module that can turn any text it identifies into speech that the user can hear using built-in speakers in the user's glasses. Users are now able to access to printed materials like menus and signs in a way that was not previously feasible. A sign board recognition module, which converts text on signs into speech, is also part of the system. The proposed approach has the potential to enhance the liberty and standard of existence of blind individuals through integrating these attributes in a wearable device.

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Realization of OpenCL based CNN Implementation on FPGA using SDAccel Platform

Cited by 2 publications

References 8 publications

Advancing Prosthetic Arm Technology with Enhanced Aesthetics Integrating EMG Based Signals, 3D Printing and Tactile Sensors

Advancing Prosthetic Arm Technology with Enhanced Aesthetics Integrating EMG Based Signals, 3D Printing and Tactile Sensors

Virtual Assistant and Navigation for Visually Impaired using Deep Neural Network and Image Processing

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