The YOLOv5 object detection models are well known for their excellent performance and optimized inference speed. Recently, the support for instance segmentation has also been added to the codebase. ...
DeepLabv3 & DeepLabv3+ The Ultimate PyTorch Guide
DeepLab models, first debuted in ICLR ‘14, are a series of deep learning architectures designed to tackle the problem of semantic segmentation. After making iterative refinements through the years, ...
Performance Comparison of YOLO Object Detection Models – An Intensive Study
If you are undertaking an object detection project, the probability is high that you would choose one of the many YOLO models. Going by the number of YOLO object detection models out there, it's a ...
YOLOv6 Custom Dataset Training – Underwater Trash Detection
The field of object detection is coming across a new YOLO model release every few months. Although reading the paper should be the first step towards exploring the model, we can evaluate the model ...
Document Segmentation Using Deep Learning in PyTorch
Document Scanning is a background segmentation problem that can be solved using various methods. It is one of the extensively used applications of computer vision. In this article, we are considering ...
Building Industrial embedded deep learning inference pipelines with TensorRT
You can scarcely find a good article on deploying computer vision systems in industrial scenarios. So, we decided to write a blog post series on the topic. The topics we will cover in this ...