How to answer this Question in Interview?
Interview Question: What is the difference between traditional computer vision techniques and deep learning-based approaches?
Answer: “Traditional computer vision techniques and deep learning-based approaches differ fundamentally in their methodologies and the way they handle visual data. Traditional computer vision relies heavily on manual feature extraction and domain-specific knowledge. Techniques such as edge detection, texture analysis, and HOG (Histogram of Oriented Gradients) descriptors are examples where predefined algorithms are used to identify patterns and features in images. These methods require significant human intervention to design and fine-tune features that are relevant to the task at hand.
On the other hand, deep learning-based approaches, particularly those utilizing convolutional neural networks (CNNs), automate feature extraction. In deep learning, the model learns to identify features directly from the data through multiple layers of processing. Each layer extracts increasingly complex features from the raw pixel data, allowing the model to learn hierarchical representations of the input images. This process reduces the need for manual feature engineering and enables the model to adapt to a wide range of visual tasks with minimal human intervention.
Another key difference lies in their performance and scalability. Traditional methods often struggle with large datasets and complex tasks because they rely on handcrafted features that may not generalize well across different scenarios. In contrast, deep learning models excel in handling large volumes of data and can achieve superior performance on tasks such as image classification, object detection, and segmentation, given sufficient data and computational resources. The ability to leverage vast amounts of labeled data for training allows deep learning models to improve accuracy and robustness significantly.”
Difference between Traditional Computer Vision Techniques and Deep Learning-based Approaches
Computer vision enables machines to interpret and understand the visual world. Over the years, two main approaches have dominated the field: traditional computer vision techniques and deep learning-based approaches.
This article delves into the fundamental differences between these two methodologies and how can be answered in the interview.
Contact Us