Member-only story
11 min readOct 24, 2025
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Convolutional Neural Networks (CNNs) are powerful deep learning models designed to process visual information by mimicking how the human brain processes images. They are primarily used for two critical tasks: object detection (locating and identifying multiple objects in an image) and object classification (categorizing what an object is).
In object detection, CNNs identify the location and boundaries of objects within an image, providing both classification labels and spatial coordinates. In object classification, CNNs simply determine what category an object belongs to — for example, distinguishing between a cat, dog, or car.
Practical Applications
CNNs are exceptionally effective for:
Object Classification: Determining w…
Member-only story
11 min readOct 24, 2025
–
Convolutional Neural Networks (CNNs) are powerful deep learning models designed to process visual information by mimicking how the human brain processes images. They are primarily used for two critical tasks: object detection (locating and identifying multiple objects in an image) and object classification (categorizing what an object is).
In object detection, CNNs identify the location and boundaries of objects within an image, providing both classification labels and spatial coordinates. In object classification, CNNs simply determine what category an object belongs to — for example, distinguishing between a cat, dog, or car.
Practical Applications
CNNs are exceptionally effective for:
Object Classification: Determining whether an image contains a dog, cat, bird, or other categories with high accuracy.
Object Detection: Not only identifying objects but also drawing bounding boxes around them and providing confidence scores — useful in autonomous vehicles, security systems, and medical imaging.
Medical Imaging: Detecting tumors, fractures, or abnormalities in X-rays and CT scans.
Autonomous Vehicles: Recognizing pedestrians, traffic signs, and other vehicles in real-time.
Facial Recognition: Identifying and verifying individuals in images and videos.