Husnain Javid B. Profile

EXPLORAR

0,0

(0 comentarios)

Ahora estás siguiendo a

Error al seguir a usuario.

Este usuario no permite que los usuarios lo sigan.

Ya estás siguiendo a este usuario.

Tu plan de membresía solo permite 0 seguimientos. Mejora tu membresía aquí.

Dejaste de seguir correctamente a

Error al dejar de seguir al usuario.

Has recomendado exitosamente a

Error al recomendar al usuario.

Algo salió mal. Por favor, actualiza la página e intenta de nuevo.

Email verificado correctamente.

$20 USD / hora

islamabad,

pakistan

$20 USD / hora

Aquí son las 11:05 a. m.

Se unió el septiembre 28, 2015

0 Recomendaciones

Husnain Javid B.

@hussnainbhatti

0,0

(0 comentarios)

0,0

$20 USD / hora

islamabad,

pakistan

$20 USD / hora

N/A

Trabajos finalizados

N/A

Dentro del presupuesto

N/A

A tiempo

N/A

Tasa de recontratación

AI & Machine Learning | NLP | Computer Vision

An electrical engineer and a machine learning expert with over 4 years of experience in cutting-edge ML research with a focus on Neural Networks, Computer Vision, 3D vision, Point Cloud / 3D Mesh, embedded ML systems, and Medical Imaging. I am dedicated to delivering high-quality accurate and optimized work. Being able to work closely with clients to understand their needs and provide tailored solutions that meet their specific requirements, I have worked with several tech clients and developed complex and advanced projects. A lifelong learner regularly following the latest advancements in my field and incorporating upgrades for better solutions. Want my help? Contact me to stay ahead of the competition!

Ver todo Python Developers en Pakistan

Contacta Husnain Javid B. sobre tu trabajo

Inicia sesión para comentar cualquier detalle por chat.

Comentarios

Cambios guardados

¡No hay comentarios para ver aquí!

Experiencia

ALGORYC

feb 2023 - Presente

● Conduct experiments to test and validate computer vision models, and optimized their performance to achieve high accuracy and efficiency ● Maintained up-to-date knowledge of the latest computer vision techniques and tools, and evaluated their suitability for different use cases

RevolveAI

nov 2021 - feb 2023 (1 año, 3 meses)

● Developed cutting-edge computer vision solutions to address complex business challenges ● Design and implement computer vision models, and deploy them into production environments ● Used Python and C++ to develop and implement computer vision algorithms ● Deployed machine learning models on edge devices to enable real-time inference ● Contributed to research and development projects aimed at advancing state-of-the-art computer vision

MIPRG

mar 2018 - nov 2021 (3 años, 8 meses)

● Conducted cutting-edge research on Magnetic Resonance Imaging (MRI) image reconstruction from undersampled MRI data ● Worked closely with a team of researchers and professors to design experiments, analyze data, and publish research papers in top-tier conferences ● Developed software tools in programming languages such as Python and MATLAB to support the research efforts of the team

Educación

MS Electrical Engineering (Signal Processing)

National University of Science and Technology,

Pakistan

2019 - 2023

(4 años)

BS Electrical (Telecommunication) Engineer

COMSATS Institute of Information Technology,

Pakistan

2015 - 2019

(4 años)

Publicaciones

Calibration-less pMRI for the Reconstruction of Radially Encoded data using GROG based CS

ISMRM 28th Annual Meeting & Exhibition

To reduce MRI scan time, under-sampled non-Cartesian trajectories are used which lead to artifacts. This work proposes a new method ‘GROG with calibration-less pMRI for CS based p-thresholding’ to reconstruct MR images from the under-sampled radial k-space data.

CS based p-thresholding with pMRI for the reconstruction of radial data

37th ESMRMB Annual Scientific Meeting, Australia

Accelerated non-Cartesian trajectories are used to speed up MRI scan time, but it results in artifacts. In this paper, Compressed Sensing with parallel MRI (CS-pMRI) based p-thresholding with GRAPPA operator gridding (GROG) is proposed to recover the un-aliased MR images from the under-sampled radial k-space data. The proposed method is compared with CS-pMRI based soft and hard thresholding techniques. radial data.

Reconstruction of under-sampled Radial MRI using SC-GROG followed by SVT based CS

36th ESMRMB Annual Scientific Meeting, Netherlands

In pMRI, undersampled non-Cartesian trajectories are used to speed up the MR scan time but lead to artifacts in the final images. This paper proposes Singular Value Threshold (SVT) along with self-calibrated GROG (SC-GROG) for CS based reconstruction to get the unaliased MR images from the undersampled radial k-space data.