Results 111 to 120 of about 2,709,471 (316)

Improving the Robustness of Visual Teach‐and‐Repeat Navigation Using Drift Error Correction and Event‐Based Vision for Low‐Light Environments

open access: yesAdvanced Robotics Research, EarlyView.
Visual teach‐and‐repeat (VTR) navigation allows robots to learn and follow routes without building a full metric map. We show that navigation accuracy for VTR can be improved by integrating a topological map with error‐drift correction based on stereo vision.
Fuhai Ling, Ze Huang, Tony J. Prescott
wiley   +1 more source

Taxonomic structure in a set of abstract concepts

open access: yesFrontiers in Psychology
A large portion of human knowledge comprises “abstract” concepts that lack readily perceivable properties (e.g., “love” and “justice”). Since abstract concepts lack such properties, they have historically been treated as an undifferentiated category of ...
Andrew S. Persichetti   +4 more
doaj   +1 more source

The relative contributions of visual and semantic information in the neural representation of object categories

open access: yesBrain and Behavior, 2019
Introduction How do multiple sources of information interact to form mental representations of object categories? It is commonly held that object categories reflect the integration of perceptual features and semantic/knowledge‐based features.
Lindsay W. Victoria   +2 more
doaj   +1 more source

Structural Stability of Lexical Semantic Spaces: Nouns in Chinese and French

open access: yes, 2017
Many studies in the neurosciences have dealt with the semantic processing of words or categories, but few have looked into the semantic organization of the lexicon thought as a system.
Lu, Bao-Liang   +5 more
core  

Continual Learning for Multimodal Data Fusion of a Soft Gripper

open access: yesAdvanced Robotics Research, EarlyView.
Models trained on a single data modality often struggle to generalize when exposed to a different modality. This work introduces a continual learning algorithm capable of incrementally learning different data modalities by leveraging both class‐incremental and domain‐incremental learning scenarios in an artificial environment where labeled data is ...
Nilay Kushawaha, Egidio Falotico
wiley   +1 more source

Challenges and Future Directions in Assessing the Quality and Completeness of Advanced Materials Safety Data for Re‐Usability: A Position Paper From the Nanosafety Community

open access: yesAdvanced Sustainable Systems, EarlyView.
Nanosafety data provide a guiding example for establishing best practices in data management, aligning with FAIR principles and quality criteria. This review explores existing quality assessment approaches for reliability, relevance, and completeness, emphasizing the need for harmonization and adaptation to nanomaterials and advanced materials. The aim
Verónica I. Dumit   +43 more
wiley   +1 more source

Semantic, Aspectual Category and Evidential Category of-guo

open access: yesEnglish Language Teaching and Linguistics Studies, 2020
 The semantics of -guo indicates a non-empty set of a type of eventuality in a certain time frame, while the properties of term inability, discontinuity and repeatability are only pragmatic implicatures. From the viewpoint of event structure, -guo is better considered as an imperfective marker than an experiential marker which asserting the activity ...
openaire   +2 more sources

Single‐Nucleus Multi‐Omics Reveals Hypoxia‐Driven Angiogenic Programs and Their Epigenetic Control in Sinonasal Squamous Cell Carcinoma

open access: yesAdvanced Science, EarlyView.
Single‐nucleus multi‐omics profiling of sinonasal squamous cell carcinoma unveils a hypoxia‐driven angiogenic axis. A specific hypoxic tumor subpopulation orchestrates endothelial tip cell differentiation via epigenetically regulated ADM and VEGFA secretion.
Chaelin You   +12 more
wiley   +1 more source

Foundation Model‐Enabled Multimodal Deep Learning for Prognostic Prediction in Colorectal Cancer with Incomplete Modalities: A Multi‐Institutional Retrospective Study

open access: yesAdvanced Science, EarlyView.
FLARE, a multimodal AI framework, combines pathology slides, radiology scans, and clinical reports to predict colorectal cancer outcomes, even when some tests are missing. Evaluated retrospectively in 1679 patients from four medical centers, it consistently achieved the best prognostic accuracy and clearly separated high‐ and low‐risk groups.
Linhao Qu   +6 more
wiley   +1 more source

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