Even when we clean, because of laziness or lack of time, we often throw all waste into the same bin without separating ...

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

Accurate and efficient grain quality assessment is critical for making informed decisions throughout the grain value chain. Early detection of disease enables actions to mitigate spread and further ...

Detect vehicle license plates in videos and images using the tensorflow/object_detection API. Train object detection models for license plate detection using TFOD API, with either a single detection ...

The tuning of a pre-trained model is a crucial application for transfer learning in machine learning. It is a process of learning to re-adjust initially pre-trained models, with some big datasets, to ...

This research introduces an innovative approach to image classification, by making use of Vision Transformer (ViT) architecture. In fact, Vision Transformers (ViT) have emerged as a promising option ...

This contains examples, scripts and code related to image classification using TensorFlow models (from here) converted to TensorRT. Converting TensorFlow models to TensorRT offers significant ...

Purpose: We aim to present effective and computer aided diagnostics in the field of ophthalmology and improve eye health. This study aims to create an automated deep learning based system for ...

The constantly evolving human–machine interaction and advancement in sociotechnical systems have made it essential to analyze vital human factors such as mental workload, vigilance, fatigue, and ...

Pinpointing subcellular protein localizations from microscopy images is easy to the trained eye, but challenging to automate. Based on the Human Protein Atlas image collection, we held a competition ...