AI helps find trees in a forest: Researchers achieve 3D forest reconstruction from remote sensing data

Existing algorithms can partially reconstruct the shape of a single tree from a clean point-cloud dataset acquired by ...

New research decodes hidden bias in health care LLMs

Artificial intelligence is increasingly used as a tool in many health care settings, from writing physicians' notes to making ...
Frontiers

Advancing Deep Learning Frameworks for Enhanced Cervical Cancer Diagnosis, Staging and Treatment

Cervical cancer detection and diagnosis are undergoing a transformation with the integration of advanced deep learning (DL) technologies. Despite ...
IEEE

Sparse Autoencoder-Based Deep Learning Approach for Enhancing End-to-End Communication System Performance

Deep Learning (DL) has emerged as a transformative approach in artificial intelligence, demonstrating remarkable capabilities in solving complex problems once considered unattainable. Its ability to ...
IEEE

Depression Detection Through EEG Signal Analysis: A Convolutional Autoencoder Deep Learning Model

Abstract: Depression is a debilitating and enervating mental health disorder that requires attention for necessitating accurate and efficient diagnostic techniques ...
Scientific Research Publishing

Traffic Speed Prediction Based on Autoencoder and Deep Learning ()

Traffic prediction is the core of intelligent transportation system, and accurate traffic speed prediction is the key to optimize traffic management. Currently, the traffic speed prediction model ...
Live Science

Only 0.001% of deep ocean has ever been explored by humans — an area equal to the size of Rhode Island

Despite the deep ocean floor coating some 66% of our planet's surface, we haven't explored 99.999% of it, study finds. When you purchase through links on our site, we may earn an affiliate commission.
GitHub

Lesson No. 3: Variational autoencoder code for CelebA dataset takes too long to load

train_data = utils.image_dataset_from_directory( "celeba-dataset/img_align_celeba/img_align_celeba", labels = None, color_mode="rgb", image_size = (64, 64), batch ...