That is exactly what this Raspberry Pi object detection project demonstrates. You can build a fully working object detection ...

AI thrives on data but feeding it the right data is harder than it seems. As enterprises scale their AI initiatives, they face the challenge of managing diverse data pipelines, ensuring proximity to ...

Abstract: Deep neural networks (DNNs) are widely used for image recognition, speech recognition, pattern analysis, and intrusion detection. Recently, the adversarial example attack, in which the input ...

Back in November last year, we covered the launch of the NuMicro M55M1 MCU from Nuvoton, which combines an Arm Cortex-M55 core with an Ethos-U55 microNPU for on-device AI and gesture control. Now, ...

Until now, our neural networks have treated every input feature independently. That works for tabular data, but images are different. A 224×224 image contains over 50,000 pixels, and nearby pixels are ...

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Delivered pre-trained and fine-tuned neural network models using TensorFlow for internal projects, including object detection and automated chatbots using NLP. Collaborated with cross-functional teams ...

The experiments using existing benchmark datasets validate the performance, achieving 98.9% accuracy in weapon detection and 97.34% accuracy in face recognition and outperforming the existing ...