Feature Pyramid Networks (FPN) Explained
Learn how Feature Pyramid Networks build multi-scale feature representations through top-down pathways and lateral connections for robust object detection.
10 min readConcept
Tagged with
Computer Vision
Explore machine learning concepts related to Computer Vision. Clear explanations and practical insights.
10
Concepts Found
Concepts Related to Computer Vision
RoI Pooling, RoI Align & Deformable RoI Pooling
Understanding region-based feature extraction for object detection, from quantized pooling to sub-pixel alignment and adaptive sampling
12 min readConcept
Anchor-Based vs Anchor-Free Object Detection
Compare anchor-based vs anchor-free object detection: Faster R-CNN and RetinaNet anchors vs FCOS and CenterNet point-based methods.
12 min readConcept
NAS-FPN: Learning to Design Feature Pyramid Networks
Understanding how neural architecture search discovers optimal feature pyramid architectures that outperform hand-designed alternatives
15 min readConcept
DETR Explained: Object Detection with Transformers
Understanding end-to-end object detection with transformers, from DETR's object queries to bipartite matching and attention-based localization
15 min readConcept
Convolution Operation: The Foundation of CNNs
Interactive guide to convolution in CNNs: visualize sliding windows, kernels, stride, padding, and feature detection with step-by-step demos.
10 min readConcept
NMS & Soft-NMS: Removing Duplicate Detections
Understanding Non-Maximum Suppression algorithms for object detection post-processing, from greedy NMS to soft variants
12 min readConcept
Visual Complexity Analysis for Token Allocation
Learn how visual complexity analysis optimizes vision transformer token allocation using edge detection, FFT, and entropy metrics.
15 min readConcept
Receptive Field in CNNs
Understand receptive fields in CNNs: how convolutional layers expand their field of view and the gap between theoretical and effective receptive fields.
7 min readConcept
Visual Complexity Analysis: Smart Image Processing
Learn visual complexity analysis in deep learning - how neural networks measure entropy, edges, and saliency for adaptive image processing.
8 min readConcept