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DevVibe is delighted to announce the signing of a Memorandum of Understanding (MoU) with the University of Management and Technology (UMT), establishing a strategic partnership focused on strengthening collaboration between academia and industry in the field of Artificial Intelligence.
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DevVibe partnered with Air University to develop a Digital Twin–based system for monitoring and predictive maintenance of radiological equipment, improving healthcare infrastructure and operational efficiency.
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DevVibe partnered with Air University to develop Gender-Neutral 8-Channel EMG Technology for Pelvic Floor Monitoring under NRPU funding.
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Conferences
In this paper, a computationally effective and explainable Vision Transformer (ViT)-based framework is also suggested that can be used to perform automated classification of ultrasound images of the breast into benign, malignant, and normal issues. The pipeline combines paired image-mask representation, class-weighted training
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In this paper, a computationally effective and explainable Vision Transformer (ViT)-based framework is also suggested that can be used to perform automated classification of ultrasound images of the breast into benign, malignant, and normal issues. The pipeline combines paired image-mask representation, class-weighted training In this paper, a computationally effective and explainable Vision Transformer (ViT)-based framework is also suggested that can be used to perform automated classification of ultrasound images of the breast into benign, malignant, and normal issues. The pipeline combines paired image-mask representation, class-weighted training In this paper, a computationally effective and explainable Vision Transformer (ViT)-based framework is also suggested that can be used to perform automated classification of ultrasound images of the breast into benign, malignant, and normal issues. The pipeline combines paired image-mask representation, class-weighted training
