Results 121 to 130 of about 104,311 (276)
Attention-Guided Hierarchical Parsing for Fine-Grained Person-Centric Image Captioning
Although significant progress in the task of producing fine-grained captions for portrait images has been made by the current models for generating detailed descriptions in captions, they still face challenges in attention allocation and in capturing the
Zhengcheng Gu, Jing Jin
doaj +1 more source
Smart Exploration of Perovskite Photovoltaics: From AI Driven Discovery to Autonomous Laboratories
In this review, we summarize the fundamentals of AI in automated materials science, and review AI applications in perovskite solar cells. Then, we sum up recent progress in AI‐guided manufacturing optimization, and highlight AI‐driven high‐throughput and autonomous laboratories.
Wenning Chen +4 more
wiley +1 more source
An Overview of Image Caption Generation Methods. [PDF]
Wang H, Zhang Y, Yu X.
europepmc +1 more source
This study analyzed log data from the Japanese hinotori surgical robot to characterize manipulation performed by experienced surgeons in robotic surgery. Compared with less‐experienced surgeons, the experienced group demonstrated shorter task durations, reduced travel distances with the right instrument (Arm3), faster and more dynamically modulated ...
Masaki Saito +11 more
wiley +1 more source
Abstract Filamentous microorganisms exhibit complex morphologies that influence product formation and are affected by various bioprocess parameters. Consistent morphology is therefore essential for comparable results during scale‐up. This study investigates the scale‐up of Streptomyces species (Streptomyces spp.) cultivations from shake flasks to ...
Gesa Brauneck +12 more
wiley +1 more source
Image Caption Generator Using LSTM
Abstract: There have been groundbreaking applications that connect visual content understanding with verbal expression made possible by the rise of Deep Learning (DL) in Computer Vision (CV) and Natural Language Processing (NLP). Among these, the project on Image Caption Generator using Long Short-Term Memory (LSTM) networks stands out as a significant
Chalcheema Sasidhar +4 more
openaire +2 more sources
This study applies QSAR‐based new approach methodologies to 90 synthetic tattoo and permanent makeup pigments, revealing systemic links between their physicochemical properties and absorption, distribution, metabolism, and elimination profiles. The correlation‐driven analysis using SwissADME, ChemBCPP, and principal component analysis uncovers insights
Girija Bansod +10 more
wiley +1 more source
Large Language Model in Materials Science: Roles, Challenges, and Strategic Outlook
Large language models (LLMs) are reshaping materials science. Acting as Oracle, Surrogate, Quant, and Arbiter, they now extract knowledge, predict properties, gauge risk, and steer decisions within a traceable loop. Overcoming data heterogeneity, hallucinations, and poor interpretability demands domain‐adapted models, cross‐modal data standards, and ...
Jinglan Zhang +4 more
wiley +1 more source
Review Networks for Caption Generation
We propose a novel extension of the encoder-decoder framework, called a review network. The review network is generic and can enhance any existing encoder- decoder model: in this paper, we consider RNN decoders with both CNN and RNN encoders. The review network performs a number of review steps with attention mechanism on the encoder hidden states, and
Yang, Zhilin +4 more
openaire +2 more sources
Sequential multicolor fluorescence imaging in dynamic microsystems is constrained by acquisition speed and excitation dose. This study introduces a real‐time framework to reconstruct spectrally separated channels from reduced cross‐channel acquisitions (frames containing mixed spectral contributions).
Juan J. Huaroto +3 more
wiley +1 more source

