Results 31 to 40 of about 19,170,582 (248)

Iterative source and channel decoding relying on correlation modelling for wireless video transmission [PDF]

, 2013
Since joint source-channel decoding (JSCD) is capable of exploiting the residual redundancy in the source signals for improving the attainable error resilience, it has attracted substantial attention.
Wang, Tao, Hanzo, Lajos, Huo, Yongkai, Maunder, Robert G.   +3 more
core   +1 more source

Artificial Intelligence–Based Online Symptom Assessment Tools for Systemic Lupus Erythematosus Diagnosis: Patient Perspectives

Arthritis Care &Research, EarlyView.
Objective The objective of this article is to identify perceptions of patients with systemic lupus erythematosus (SLE) regarding artificial intelligence (AI)–based online symptom assessment tools, and the potential of these tools to address diagnostic barriers.
Olivia A. Stein, Jennifer L. F. Lee, Evelyne Vinet, Arielle Mendel, Christian A. Pineau, Fares Kalache, Louis‐Pierre Grenier, Sasha Bernatsky   +7 more
wiley   +1 more source

Cognitive computing method based on decoding psychological emotional states

International Journal of Cognitive Computing in Engineering
The current artificial intelligence is constrained to passively executing human command control. It cannot perceive, learn, and guide itself. Furthermore, the majority of these systems are unable to comprehend the human psychological cognitive state or ...
Baihui Huangfu, Wenjuan Cheng
doaj   +1 more source

What Do Large Language Models Know About Materials?

Advanced Engineering Materials, EarlyView.
If large language models (LLMs) are to be used inside the material discovery and engineering process, they must be benchmarked for the accurateness of intrinsic material knowledge. The current work introduces 1) a reasoning process through the processing–structure–property–performance chain and 2) a tool for benchmarking knowledge of LLMs concerning ...
Adrian Ehrenhofer, Thomas Wallmersperger, Gianaurelio Cuniberti   +2 more
wiley   +1 more source

Contrastive representation learning with transformers for robust auditory EEG decoding

Scientific Reports
Decoding of continuous speech from electroencephalography (EEG) presents a promising avenue for understanding neural mechanisms of auditory processing and developing applications in hearing diagnostics.
Lies Bollens, Bernd Accou, Hugo Van hamme, Tom Francart   +3 more
doaj   +1 more source

HSST-EEG: A Hybrid State-Space and Transformer Architecture for EEG Decoding

IEEE Access
Accurate interpretation of electroencephalography (EEG) signals requires effective modeling of high-dimensional, non-stationary, and long-range spatio-temporal dynamics, which remains a central challenge in both clinical and BCI-oriented decoding tasks ...
Emil Kim, Jin Kyu Gahm
doaj   +1 more source

Frequency set selection for multi-frequency steady-state visual evoked potential-based brain-computer interfaces

Frontiers in Neuroscience, 2022
ObjectiveMulti-frequency steady-state visual evoked potential (SSVEP) stimulation and decoding methods enable the representation of a large number of visual targets in brain-computer interfaces (BCIs).
Jing Mu, David B. Grayden, David B. Grayden, Ying Tan, Ying Tan, Denny Oetomo, Denny Oetomo   +6 more
doaj   +1 more source

Erasure codes with a banded structure for hybrid iterative-ML decoding [PDF]

, 2009
This paper presents new FEC codes for the erasure channel, LDPC-Band, that have been designed so as to optimize a hybrid iterative-Maximum Likelihood (ML) decoding.
Soro, Alexandre, Alexandre Soro, Lacan, Jérôme, Cunche, Mathieu, Mathieu Cunche, Vincent Roca, Roca, Vincent, Jerome Lacan   +7 more
core   +1 more source

Is an Apple an Orange? A Large Language Model Benchmark for Candidate Term Extraction and Subclass Decisions Against Upper Ontologies in Engineering and Materials Science

Advanced Engineering Materials, EarlyView.
Building machine‐readable vocabularies for materials science is slow, expert‐driven work. This study benchmarks 13 large language models on two of its first steps: finding candidate terms in engineering articles and deciding where they belong in a class hierarchy.
Thomas Bjarsch, Maximilian Holland, Klaus Drechsler, Johannes Schilp   +3 more
wiley   +1 more source

Multi-Domain Collaborative Decoding of SSVEP with Adaptive Visual Distraction Compensation [PDF]

Jisuanji gongcheng
Brain-Computer Interface (BCI) systems based on Steady-State Visual Evoked Potential (SSVEP) show classification performance limitations due to individual differences and interference from non-target stimuli.
JIA Shuting, WEN Xin, HAO Yanrong, CAO Rui
doaj   +1 more source