PyTorch

Object detection models are among the most resource-intensive in deep learning, often requiring substantial computational power and memory. This poses significant challenges when deploying these models on embedded systems, which are......

Introduction to CycleGANCycleGAN (Cycle-Consistent Generative Adversarial Networks) are an innovative approach to solving the problem of image-to-image translation, enabling you to convert images from one domain to another without......

Video object tracking and multi-object detection are essential components in a wide array of computer vision applications ranging from surveillance systems to robotics. PyTorch, with its dynamic computation graph and robust GPU......

Depth estimation is a crucial task in computer vision, enabling applications such as 3D reconstruction, robotics, and augmented reality. In this article, we'll explore how to train a depth estimation model using PyTorch by leveraging only......

In the realm of visual data analysis, leveraging powerful libraries like PyTorch and OpenCV can significantly enhance the capabilities of your project. These tools seamlessly complement each other: PyTorch for its deep learning framework......

Human pose estimation is a crucial task in computer vision, which involves identifying the precise positions of human joints or landmarks in an image or video. It has notable applications in various sectors such as healthcare, sports......

Style transfer is an exciting topic in the field of computer vision and deep learning. It involves applying the style of one image onto another, making the resulting image a blend of the content of one and the style of another. With......

In the realm of image processing and computer vision, super-resolution networks stand as pioneering models that enhance the resolution of images, rendering them with superior clarity and detail. PyTorch, a popular deep learning framework,......

Generative Adversarial Networks (GANs) have revolutionized the field of artificial intelligence, enabling the generation of highly realistic images that are nearly indistinguishable from real-world photographs. PyTorch, an increasingly......

In recent years, landmark detection has become a crucial task in computer vision, powering applications such as augmented reality, mobile apps, and more. Designing a landmark detection system that operates in real-time is challenging but......

Instance Segmentation, a fundamental task in computer vision, involves detecting and delineating each distinct object of interest in an image. PyTorch, a flexible and popular deep learning framework, offers the capability to implement and......

Semantic segmentation is a crucial area in computer vision, involving the process of classifying each pixel in an image into a class. In this article, we will walk through building a semantic segmentation model using PyTorch and the U-Net......