Results 121 to 130 of about 209,152 (323)
Overcoming the Nyquist Limit in Molecular Hyperspectral Imaging by Reinforcement Learning
Explorative spectral acquisition guide automatically selects informative spectral bands to optimize downstream tasks, outperforming full‐spectrum acquisition. The selected hyperspectral data are used for tasks such as unmixing and segmentation. BandOptiNet encodes selection states and outputs optimal bands to guide spectral acquisition. Recent advances
Xiaobin Tang +4 more
wiley +1 more source
BMPCQA: Bioinspired Metaverse Point Cloud Quality Assessment Based on Large Multimodal Models
This study presents a bioinspired metaverse point cloud quality assessment metric, which simulates the human visual evaluation process to perform the point cloud quality assessment task. It first extracts rendering projection video features, normal image features, and point cloud patch features, which are then fed into a large multimodal model to ...
Huiyu Duan +7 more
wiley +1 more source
Research on NVIDIA's Development Strategy
NVIDIA, as the world's leading supplier of graphics processing units (GPUs) and artificial intelligence (AI) computing hardware, has achieved rapid development and expansion in recent years. This paper studies the evolution of NVIDIA's development strategy and the factors for its success by analyzing NVIDIA's development history, industry environment ...
Rui Zhang, Lei Hu
openaire +1 more source
Automated Discovery of Multicellular Behavior for Optimized Plant Growth and Climate Resilience
An automated robotic system is described for rapid scientific experimentation with multicellular organisms. By enhancing a robotic liquid handler with a custom developed deep learning algorithm and camera module, samples and data are prepared with minimal human intervention.
Mark A. DeAngelis +2 more
wiley +1 more source
Advancing Parsimonious Deep Learning Weather Prediction Using the HEALPix Mesh
We present a parsimonious deep learning weather prediction model to forecast seven atmospheric variables with 3‐hr time resolution for up to 1‐year lead times on a 110‐km global mesh using the Hierarchical Equal Area isoLatitude Pixelization (HEALPix ...
Matthias Karlbauer +7 more
doaj +1 more source
Variational Autoencoder+Deep Deterministic Policy Gradient addresses low‐light failures of infrared depth sensing for indoor robot navigation. Stage 1 pretrains an attention‐enhanced Variational Autoencoder (Convolutional Block Attention Module+Feature Pyramid Network) to map dark depth frames to a well‐lit reconstruction, yielding a 128‐D latent code ...
Uiseok Lee +7 more
wiley +1 more source
This study presents a new sampling‐based model predictive control minimizing reverse Kullback‐Leibler divergence to quickly find a local optimum. In addition, a modified Nesterov's acceleration method is introduced for faster convergence. The method is effective for real‐time simulations and real‐world operability improvement on a force‐driven mobile ...
Taisuke Kobayashi, Kota Fukumoto
wiley +1 more source
FTGRN introduces an LLM‐enhanced framework for gene regulatory network inference through a two‐stage workflow. It combines a Transformer‐based model, pretrained on GPT‐4 derived gene embeddings and regulatory knowledge, with a fine‐tuning stage utilizing single‐cell RNA‐seq data.
Guangzheng Weng +7 more
wiley +1 more source
Accelerating virtual texturing using CUDA [PDF]
Mark Harris Shubhabrata Sengupta +6 more
core +1 more source
A novel autonomous robotic colonoscopy is introduced through supervised learning approaches. The proposed system consists of 3 degrees of freedom motorized colonoscope with an integrated navigation module that can infer a target steering point and collision probability.
Bohyun Hwang +3 more
wiley +1 more source

