Even when we clean, because of laziness or lack of time, we often throw all waste into the same bin without separating ...
What does this project do? A USB camera connected to a Raspberry Pi continuously captures frames. OpenCV encodes each frame as a JPEG and sends it to the CircuitDigest Cloud Face Detection API via ...
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 ...
Microplastics have been found to be highly pervasive in the environment, driving concerns for health, environment, and ecology. Analytical methods that can accurately identify microplastics are ...
Diabetic retinopathy is a serious concern for people dealing with diabetes. Detecting diabetic retinopathy poses significant challenges, requiring skilled professionals, extensive manual image ...
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 ...
Deep learning-based classification of eye diseases using Convolutional Neural Network for OCT images
Deep learning shows promising results in extracting useful information from medical images. The proposed work applies a Convolutional Neural Network (CNN) on retinal images to extract features that ...
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 ...
Machine learning and deep learning have been widely embraced, and even more widely misunderstood. In this article, I’ll step back and explain both machine learning and deep learning in basic terms, ...
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