Radxa AICore DX-M1M is a compact, low-power M.2 edge AI acceleration module built around the DeepX DX-M1M neural processing unit (NPU) and delivers up to 25 TOPS (INT8) of AI performance while ...

Abstract: Advanced Driver-Assistance Systems (ADAS) are complex systems consisting of many computer vision tasks including image classification, object detection and semantic segmentation. FPGA is a ...

BONUS: Custom Object Counting Mode (TensorFlow implementation): You can train TensorFlow models with your own training data to built your own custom object counter system! If you want to learn how to ...

Abstract: The management of plastic waste in our ecosystem represents a significant environmental issue, necessitating effective sorting and categorization to facilitate efficient recycling practices.

In recent years, the exploitation of three-dimensional (3D) data in deep learning has gained momentum despite its inherent challenges. The necessity of 3D approaches arises from the limitations of two ...

This is an implementation of Mask R-CNN on Python 3, Keras, and TensorFlow. The model generates bounding boxes and segmentation masks for each instance of an object in the image. It's based on Feature ...

Coral Dev Board Micro is the latest iteration of Google’s Edge AI devkit with an NXP i.MX RT1176 Cortex-M7/M4 crossover processor/microcontroller coupled with the company’s 4 TOPS Edge TPU, a camera, ...

Image segmentation is crucial for various Computer Vision tasks, aiding in image classification and object detection. Segmentation techniques can be categorised into semantic, instance, and panoptic ...