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Artificial intelligence detection software aims to determine whether some content (text, image, video or audio) was generated using artificial intelligence (AI). However, the reliability of such software is a topic of debate, [ 1 ] and there are concerns about the potential misapplication of AI detection software by educators.
PhotoDNA is a proprietary image ... Microsoft made PhotoDNA available to qualified organizations in a software as a service model for free ... with Google's AI-based ...
General scheme of content-based image retrieval. Content-based image retrieval, also known as query by image content and content-based visual information retrieval (CBVIR), is the application of computer vision techniques to the image retrieval problem, that is, the problem of searching for digital images in large databases (see this survey [1] for a scientific overview of the CBIR field).
Objects detected with OpenCV's Deep Neural Network module (dnn) by using a YOLOv3 model trained on COCO dataset capable to detect objects of 80 common classes. Object detection is a computer technology related to computer vision and image processing that deals with detecting instances of semantic objects of a certain class (such as humans, buildings, or cars) in digital images and videos. [1]
Undetectable AI (or Undetectable.ai) is an artificial intelligence content detection and modification software designed to identify and alter artificially generated text, such as that produced by large language models. [1] [2] [3]
Caffe supports many different types of deep learning architectures geared towards image classification and image segmentation. It supports CNN, RCNN, LSTM and fully-connected neural network designs. [8] Caffe supports GPU- and CPU-based acceleration computational kernel libraries such as Nvidia cuDNN and Intel MKL. [9] [10]