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関連する概念動画

Structural Steel Products01:24

Structural Steel Products

707
Structural steel products are created within a structural mill. The process begins with a beam blank that is reheated and then fed through a series of rollers. These rollers progressively shape the metal into its final form. Adjusting the spacings between the rollers allows for the production of different sections with the same nominal dimensions.
Once shaped, the steel's final form emerges as a continuous length, which is then segmented by a hot saw into manageable pieces. These segments...
707
Protein Networks02:26

Protein Networks

4.6K
An organism can have thousands of different proteins, and these proteins must cooperate to ensure the health of an organism. Proteins bind to other proteins and form complexes to carry out their functions. Many proteins interact with multiple other proteins creating a complex network of protein interactions.
These interactions can be represented through maps depicting protein-protein interaction networks, represented as nodes and edges. Nodes are circles that are representative of a protein,...
4.6K
Steel Fastening Techniques01:17

Steel Fastening Techniques

1.3K
Steel sections can be joined together through various fastening techniques including riveting, bolting, and welding, each suitable for different structural requirements and conditions.
Rivets are cylindrical steel fasteners with a specially designed head. During application, rivets are heated until white-hot and then inserted through pre-drilled holes in the steel sections. A pneumatic hammer is used to shape the exposed end into a second head, securing the sections together.
Bolting is another...
1.3K
Steel Manufacturing01:26

Steel Manufacturing

1.5K
Steel manufacturing is a multi-stage process that begins by smelting iron ore into cast iron in a blast furnace. This initial stage involves layering iron ore with coke, a type of fuel, and crushed limestone within the furnace. The coke is ignited with a high volume of air, leading to the creation of carbon monoxide, which acts to reduce the iron ore to pure iron.
During this smelting process, limestone plays a crucial role by forming slag. Slag captures impurities within the molten iron, such...
1.5K
Network Covalent Solids02:18

Network Covalent Solids

16.2K
Network covalent solids contain a three-dimensional network of covalently bonded atoms as found in the crystal structures of nonmetals like diamond, graphite, silicon, and some covalent compounds, such as silicon dioxide (sand) and silicon carbide (carborundum, the abrasive on sandpaper). Many minerals have networks of covalent bonds.
To break or to melt a covalent network solid, covalent bonds must be broken. Because covalent bonds are relatively strong, covalent network solids are typically...
16.2K
Structures of Solids02:22

Structures of Solids

18.6K
Solids in which the atoms, ions, or molecules are arranged in a definite repeating pattern are known as crystalline solids. Metals and ionic compounds typically form ordered, crystalline solids. A crystalline solid has a precise melting temperature because each atom or molecule of the same type is held in place with the same forces or energy. Amorphous solids or non-crystalline solids (or, sometimes, glasses) which lack an ordered internal structure and are randomly arranged. Substances that...
18.6K

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関連する実験動画

Updated: Feb 14, 2026

Design, Surface Treatment, Cellular Plating, and Culturing of Modular Neuronal Networks Composed of Functionally Inter-connected Circuits
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LESSDD-Net:特徴セグメンテーションと部分的に接続された構造に基づいた軽量で効率的な鋼の表面欠陥検出ネットワーク.

Jiayu Wu1, Longxin Zhang1, Xinyi Pu1

  • 1School of Computer Science and Artificial Intelligence, Hunan University of Technology, Zhuzhou 412007, China.

Sensors (Basel, Switzerland)
|February 13, 2026
PubMed
まとめ

私たちは,スチール表面の欠陥検出のための軽量ネットワークである LESSDD-Net を開発しました. 計算コストとモデルのサイズを大幅に削減し,正確性を向上させ,モバイルデバイスに適しています.

キーワード:
注意力メカニズム 注意力メカニズムダウンサンプリング軽量で軽い軽量です.表面欠陥検出 表面欠陥検出

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Developing Neuroimaging Phenotypes of the Default Mode Network in PTSD: Integrating the Resting State, Working Memory, and Structural Connectivity
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関連する実験動画

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Design, Surface Treatment, Cellular Plating, and Culturing of Modular Neuronal Networks Composed of Functionally Inter-connected Circuits
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Developing Neuroimaging Phenotypes of the Default Mode Network in PTSD: Integrating the Resting State, Working Memory, and Structural Connectivity
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科学分野:

  • マテリアルサイエンス 材料科学
  • コンピュータビジョン コンピュータビジョン
  • 人工知能 (AI) とは,人工知能 (AI) のことです.

背景:

  • 鋼の表面の欠陥検出は,産業の品質と安全性にとって極めて重要です.
  • 現在のディープラーニングの方法は計算的に高価で,モバイル展開を制限しています.
  • 効率的で正確な欠陥検出モデルが必要である.

研究 の 目的:

  • 軽量で効率的な鋼材表面欠陥検出ネットワーク (LESSDD-Net) を提案する.
  • モバイルアプリケーションのコンピューティングコストとモデルサイズを削減します.
  • 既存のモデルと比較して検出精度を高めるため.

主な方法:

  • 軽量ダウンサンプリングモジュール (CSPDDM) を導入しました.
  • 軽量な注意力メカニズム (CCAttention) を開発した.
  • 軽量なC2fモジュール (LP-C2f) を設計し,検出を向上させ,サイズを縮小しました.

主要な成果:

  • LESSDD-Netは,YOLO11n.と比較して平均精度 (mAP) を3.19%改善しました.
  • YOLO11n.と比較して,モデルのパラメータを39.92%削減し,計算コストを20.63%削減しました.
  • 主流のオブジェクト検出モデルの中で最も低いモデルの複雑さで最高の検出精度を達成しました.

結論:

  • LESSDD-Netは,鋼の表面の欠陥検出に高度に正確で計算効率の高いソリューションを提供します.
  • 提案されたネットワークは,携帯電話などのリソースが限られたデバイスに展開するのに適しています.
  • 新しいモジュール (CSPDDM,CCAttention,LP-C2f) は,ネットワークの優れた性能と効率に貢献しています.