This is a compelling opportunity to join a market leader where you will work at the intersection of data, machine learning, and business impact, using advanced analytics to drive strategic ...

Camouflaged object segmentation (COS) is a challenging task in computer vision where the objective is to recognize and precisely separate objects that blend in with their environment. Traditional ...

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 ...

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

I tested video playback performance on YouTube using the web browsers included with the BeagleY-AI operating system image, which are Firefox ESR 111.15.0 (64-bit ...

Axelera M.2 AI accelerator module is said to deliver up to 214 TOPS of AI inference and up to 3200 FPS with ResNet -50 in a compact M.2 2280 form factor. Few details are available at this time, but ...

Flank wear is the most common wear that happens in the end milling process. However, the process of detecting the flank wear is cumbersome. To achieve comprehensively automatic detecting the flank ...

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 ...

Nuclei segmentation is a fundamental but challenging task in histopathological image analysis. One of the main problems is the existence of overlapping regions which increases the difficulty of ...

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 ...