Results 11 to 20 of about 303 (142)

From Label‐Free Multiphoton Imaging to Pathological Reports: A Vision‐Language Breast Cancer Margin Pathological Diagnosis System

Advanced Science, EarlyView.
MarginPath is a novel vision‐language system that automates breast cancer margin assessment using a single label‐free multiphoton microscopy image. By integrating tumor‐associated collagen signatures with virtual H&E imaging, it generates accurate margin heatmaps and comprehensive diagnostic reports.
Shu Wang, Jingze Su, Xiahui Han, Deyong Kang, Xiao Zhang, Fei Xu, Changzu Liu, Junlin Pan, Xingfu Wang, Qiaohui Zhan, Aimin Wang, Feng Huang, Heping Cheng, Wenxi Liu, Ruolan Lin, Jianxin Chen   +15 more
wiley   +1 more source

SCP‐Pose: Leveraging Structural Consistency Prior Knowledge for Real‐Time Category‐Level 6D Pose Estimation

Advanced Intelligent Systems, EarlyView.
This paper presents a high‐speed object pose estimation method that deconstructs objects into geometric components. Inspired by human cognitive generalization, it detects these primitives and infers the 6D pose from their stable spatial configuration.
Xuyang Li, Mingxuan Yu, Xuemei Xie, Zhaozhuo An, Qiyue Li, Xiaodan Song, Guangming Shi   +6 more
wiley   +1 more source

Real‐Time Incremental Learning Artificial Neural Networks Maximum Power Point Tracking With Raspberry Pi‐Based Meteorological Data Acquisition

Energy Science &Engineering, EarlyView.
We present a smart solar tracking method using artificial intelligence to improve the efficiency of solar panels. Unlike traditional techniques, our system learns and adapts to changing sunlight conditions, ensuring faster and more reliable power generation for real‐world energy needs.
Rida Amine, Noureddine El Barbri, Mourad Yessef, Mohammed M. Alammar, Z.M.S. El‐Barbary, Hatim Ameziane   +5 more
wiley   +1 more source

Balancing Accuracy and Cost: Trade‐Offs in Large Language Model Quantization for the Systems Engineering Domain

Systems Engineering, EarlyView.
ABSTRACT As Large Language Models (LLMs) are increasingly deployed within the systems engineering domain, optimizing these models to balance performance accuracy and cost for given computational resources becomes essential. One process for finding the right balance is quantization, a process that involves converting model parameters from higher ...
Ryan Bell, Raymond Madachy, Ryan Longshore   +2 more
wiley   +1 more source

Extending lookahead for LR parsers

Journal of Computer and System Sciences, 1981
AbstractA practical method is presented for extending the lookahead of LR parsers, by the addition of “reduce-arcs.” Applied to an LR(0) parser, this gives a machine which is close in size to the corresponding LALR(1) machine, but is capable of making use of unbounded lookahead.
openaire   +1 more source

On the size of parsers and LR(k)-grammars

Theoretical Computer Science, 2000
AbstractIn this paper, we consider two tradeoff results regarding the economy of description in parsing. One result is on the tradeoff between the size of a parser and its ability to detect an error early. The other result is on the tradeoff between the size of an LR(k)-grammar and the length k of the lookahead.
Hing Leung, Detlef Wotschke
openaire   +1 more source

Baselining Large Language Model Performance in Systems Engineering Using SysEngBench

Systems Engineering, EarlyView.
ABSTRACT In the rapidly evolving field of artificial intelligence (AI), large language model s (LLMs) have demonstrated impressive capabilities in generating natural language. However, their proficiency in specialized domains, particularly in the field of systems engineering (SE), remains less explored and unquantified.
Ryan Bell, Ryan Longshore, Raymond Madachy, Ashlyn Hanrahan   +3 more
wiley   +1 more source

Enterprise Network Security Using Few‐Shot Meta‐Learning

Artificial Intelligence for Engineering, EarlyView.
This paper involves a few‐shot learning study that uses model‐agnostic meta‐learning. A meta‐dataset was curated by combining six benchmark network intrusion detection datasets by parsing network traffic data from PCAP files. An MAML model performs meta‐training, validation and meta‐testing before and after fine‐tuning.
Sushant Jain, Sumukh Gupta, Amit Pundir, Sanjeev Singh, Geetika Jain Saxena   +4 more
wiley   +1 more source

TriCrackNet: Trilateral Segmentation Network for Real‐Time Crack Segmentation

CAAI Transactions on Intelligence Technology, EarlyView.
ABSTRACT To achieve high‐precision real‐time crack segmentation, we propose TriCrackNet, an efficient network based on a tri‐branch collaborative architecture incorporating boundary constraints, semantic parsing, and spatial refinement. In the semantic branch, efficient atrous spatial pyramid pooling (EASPP) is integrated.
Haixin Jia, Han Wang, Xiaoqiang Shi, Guoying Zhang, Hanqi Jiang, Jianbo Peng   +5 more
wiley   +1 more source

Torpor‐assisted migration: Regular use of shallow torpor reduces rest‐phase energy expenditure for songbirds during migration

Journal of Animal Ecology, EarlyView.
Migrating songbirds regularly use shallow torpor (up to 98% of birds for some species) to save energy (up to 42%) during inactive periods. This Ruby‐crowned Kinglet Corthylio calendula that was captured after a spring snowstorm highlights the value of being able to save energy when encountering unfavourable conditions.
Ryan A. C. Leys, Lily Hou, Liam P. McGuire   +2 more
wiley   +1 more source