IEEE

Transferring CNN With Adaptive Learning for Remote Sensing Scene Classification

Abstract: Accurate classification of remote sensing (RS) images is a perennial topic of interest in the RS community. Recently, transfer learning, especially for fine-tuning pretrained convolutional ...
Ars Technica

Why do LLMs make stuff up? New research peers under the hood.

One of the most frustrating things about using a large language model is dealing with its tendency to confabulate information, hallucinating answers that are not supported by its training data. From a ...
IEEE

Deep Learning Earth Observation Classification Using ImageNet Pretrained Networks

Abstract: Deep learning methods such as convolutional neural networks (CNNs) can deliver highly accurate classification results when provided with large enough data sets and respective labels. However ...
Futurism

Google’s Artificial Intelligence Built an AI That Outperforms Any Made by Humans

Add Futurism (opens in a new tab) More information Adding us as a Preferred Source in Google by using this link indicates that you would like to see more of our content in Google News results. In May ...
Scientific Research Publishing

Krizhevsky, A., Sutskever, I. and Hinton, G.E. (2012) Imagenet Classification with Deep Convolutional Neural Networks. Advances in Neural Information Processing Systems, 25 ...

ABSTRACT: The latest advances in Deep Learning based methods and computational capabilities provide new opportunities for vehicle tracking. In this study, YOLOv2 (You Only Look Once—version 2) is used ...
Frontiers

Deep Convolutional Neural Network-Based Epileptic Electroencephalogram (EEG) Signal Classification

Electroencephalogram (EEG) signals contain vital information on the electrical activities of the brain and are widely used to aid epilepsy analysis. A challenging element of epilepsy diagnosis, ...