লক্ষ্য করুন: এই এন্ট্রির অনুবাদ বর্তমানে মান পর্যালোচনার অধীনে রয়েছে, তাই কিছু বিষয়বস্তু সাময়িকভাবে শুধুমাত্র ইংরেজিতে প্রদর্শিত হচ্ছে।
এই এন্ট্রিটি এখনও আপনার ভাষায় অনুবাদ করা হয়নি, তাই নিচে মূল লেখাটি দেখানো হচ্ছে।
convolutional
This term is used almost exclusively in technical, mathematical, and computational contexts. In everyday conversation, it is rarely encountered unless the topic is signal processing or artificial intelligence. It describes a specific process of combining two sets of information to produce a third, often used to extract patterns or features from data.
In the context of machine learning, it is most commonly associated with Convolutional Neural Networks (CNNs). Here, it refers to the way a filter or kernel slides across an image to identify edges, textures, or complex shapes. It is a specialized adjective and is not used to describe things that are simply "complex" or "twisted" in a general sense; for those meanings, words like "convoluted" are used instead.
Avoid confusing "convolutional" with "convoluted." While they share a root, "convolutional" is a precise technical term for a mathematical operation, whereas "convoluted" describes something unnecessarily complex or difficult to follow.
Meanings
Examples
The team decided to implement a convolutional neural network for image recognition.
I need to study the convolutional layers of this model to understand how it extracts features.
Is a convolutional approach better than a standard dense network for this dataset?
The paper describes a new convolutional filter that improves edge detection.
We are using a convolutional architecture to process the satellite imagery.
The mathematical properties of the convolutional operator are essential for signal processing.
The mathematical properties of the convolutional operator are essential for signal processing.
I wonder if adding more convolutional layers will increase the accuracy of the classifier.
The system utilizes a convolutional kernel to slide across the input matrix.