In fact, most object detection networks use an image classification CNN and repurpose it for object detection. Object detection is a supervised machine learning problem, which means you must train ...

In this post, I will briefly review the deep learning architectures that help computers detect objects. Convolutional neural networks. One of the key components of most deep learning–based ...

Thanks to deep learning, the tricky business of making brain atlases just got a lot easier. Brain maps are all the rage these days. From rainbow-colored dots that highlight neurons or gene expression ...

New adversarial techniques developed by engineers can make objects 'invisible' to image detection systems that use deep-learning algorithms. These techniques can also trick systems into thinking ...

More information: Bo-Han Wei et al, Annotation-free deep learning for predicting gene mutations from whole slide images of acute myeloid leukemia, npj Precision Oncology (2025). DOI: 10.1038 ...

FOMO is a deep learning object detection model that weighs less than 200 kilobytes. ... FOMO can be applied to MobileNetV2, a popular deep learning model for image classification on edge devices.

Researchers develop novel deep learning-based detection system for autonomous vehicles The new system, aided by the Internet of things, improves the detection capabilities of autonomous vehicles ...

Clinical Photographic Images: Deep learning algorithms such as DenseNet-169, ResNet-101, and EfficientNet-b4 have been employed to analyze clinical photographs of oral lesions.