semi-automatic selection

简明释义

半自动选择

英英释义

例句

1.The semi-automatic selection feature in this graphic design application simplifies the task of creating complex shapes.

这个图形设计应用中的半自动选择功能简化了创建复杂形状的任务。

2.The new video editing tool incorporates a semi-automatic selection method to enhance editing speed.

新的视频编辑工具采用了半自动选择方法，以提高编辑速度。

3.Using semi-automatic selection, the system can suggest relevant options based on user preferences.

使用半自动选择，系统可以根据用户偏好建议相关选项。

4.The photo editing software features a semi-automatic selection tool that allows users to quickly isolate subjects from the background.

这款照片编辑软件具有一个半自动选择工具，可以让用户快速从背景中分离出主体。

5.In our data analysis program, we implemented a semi-automatic selection process to help users filter large datasets more efficiently.

在我们的数据分析程序中，我们实施了一个半自动选择过程，以帮助用户更有效地过滤大型数据集。

作文

In the age of technology, we are constantly surrounded by tools and systems designed to simplify our lives. One such concept that has gained traction in various fields is semi-automatic selection. This term refers to a process where certain elements are chosen automatically based on predefined criteria, while still allowing for human intervention at critical points. The blend of automation and human oversight creates a balance that can enhance efficiency without sacrificing quality. For instance, in the realm of data analysis, semi-automatic selection can be utilized to sift through vast amounts of information. Automated algorithms can identify patterns and trends, flagging significant data points for review. However, it is essential for analysts to have the final say in which data is ultimately selected for deeper examination. This not only ensures that the most relevant information is prioritized but also allows for human intuition and expertise to play a role in the decision-making process.Moreover, in the field of manufacturing, semi-automatic selection can streamline production lines. Machines can be programmed to select components based on specific criteria, such as size or color. Yet, operators are still needed to oversee the process and make adjustments when necessary. This hybrid approach can lead to increased productivity, as machines handle repetitive tasks while humans focus on quality control and problem-solving.The benefits of semi-automatic selection extend beyond efficiency; they also encompass accuracy and precision. In medical diagnostics, for example, machine learning algorithms can assist doctors in identifying potential health issues based on patient data. While the algorithms can provide recommendations, it is the healthcare professionals who ultimately make the diagnosis, ensuring that the patient's unique context is considered.However, it is crucial to recognize the challenges that come with implementing semi-automatic selection. One of the primary concerns is the potential for over-reliance on automated systems. If humans become too dependent on technology, there is a risk of diminishing their analytical skills and critical thinking abilities. Therefore, training and education must accompany these systems to ensure that users remain engaged and capable of making informed decisions.Additionally, transparency in how semi-automatic selection processes work is vital. Users should understand the criteria and algorithms that dictate automated selections to trust the system fully. Without this transparency, skepticism may arise, leading to resistance against adopting such technologies.In conclusion, semi-automatic selection represents a significant advancement in how we approach decision-making across various sectors. By combining the strengths of automation with the irreplaceable value of human judgment, we can create systems that are not only efficient but also reliable. As we continue to embrace technological innovations, it is imperative to strike a balance that empowers individuals while leveraging the capabilities of machines. This approach will undoubtedly pave the way for more effective solutions in the future.

在技术时代，我们周围不断被旨在简化生活的工具和系统所包围。一个在各个领域获得关注的概念是半自动选择。这个术语指的是一种过程，其中某些元素根据预定义的标准被自动选择，同时仍然允许在关键时刻进行人工干预。自动化与人类监督的结合创造了一种平衡，可以在不牺牲质量的情况下提高效率。例如，在数据分析领域，半自动选择可以用于筛选大量信息。自动化算法可以识别模式和趋势，标记重要的数据点以供审查。然而，分析师必须对最终选择深入检查的数据有最终决定权。这不仅确保了最相关的信息被优先考虑，也允许人类的直觉和专业知识在决策过程中发挥作用。此外，在制造领域，半自动选择可以简化生产线。机器可以被编程根据特定标准选择组件，例如大小或颜色。然而，操作员仍然需要监督该过程并在必要时进行调整。这种混合方法可以提高生产力，因为机器处理重复性任务，而人类则专注于质量控制和问题解决。半自动选择的好处不仅限于效率；它们还包括准确性和精确性。例如，在医疗诊断中，机器学习算法可以帮助医生根据患者数据识别潜在的健康问题。虽然算法可以提供建议，但最终做出诊断的是医疗专业人员，确保患者的独特背景被考虑在内。然而，必须认识到实施半自动选择所带来的挑战。一个主要的担忧是对自动化系统的过度依赖。如果人类变得过于依赖技术，就有可能降低他们的分析能力和批判性思维能力。因此，必须伴随这些系统进行培训和教育，以确保用户保持参与并能够做出明智的决策。此外，半自动选择过程的透明度至关重要。用户应该了解决定自动选择的标准和算法，以完全信任该系统。如果没有这种透明度，可能会产生怀疑，从而导致对采用此类技术的抵制。总之，半自动选择代表了我们在各个行业如何处理决策的重要进步。通过将自动化的优势与人类判断的不可替代价值结合起来，我们可以创建不仅高效而且可靠的系统。随着我们继续接受技术创新，必须找到一种平衡，既能赋予个人权力，又能利用机器的能力。这种方法无疑将为未来更有效的解决方案铺平道路。