AI image generation—which relies on neural networks to create new images from a variety of inputs, including text prompts—is ...

💡 Introduction IMAGHarmony tackles the challenge of controllable image editing in multi-object scenes, where existing models struggle with aligning object quantity and spatial layout.

This work designs and implements a custom hardware accelerator for single object classification from drone imagery, for surveillance applications. A lightweight attention-based convolutional neural ...

Image classification is one of AI's most common tasks, where a system is required to recognize an object from a given image. Yet real life requires us to recognize not a single standalone object but ...

Time-of-Flight (ToF) sensors are generally used in combination with red–blue–green sensors in image processing for adding the 3-D to 2-D scenes. Because of their low lateral resolution and contrast, ...

Abstract 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 ...

A computer vision team at the Georgia Institute of Technology has developed a new approach for computers to train themselves on image object recognition. The work modernizes how machine learning ...

Traditional image processing methods have been difficult to cope with the increasingly complex image backgrounds. To solve this problem, an EMRes-50 classification algorithm is proposed to solve the ...