Deep Dive into Implementation: Bounding Boxes, Heatmaps & Class Activation Maps in CNNs! (Part 14.2) скачать в хорошем качестве

Deep Dive into Implementation: Bounding Boxes, Heatmaps & Class Activation Maps in CNNs! (Part 14.2)

Video Description: 🔍 Going Beyond the Basics – Fine-Tuning the CNN for Medical Imaging! 🔍 In this video, we explore the crucial implementation details of our CNN-based Thorax Disease Classification & Detection System using the Chest X-ray 8 Dataset. 💡 Key Topics Covered: ✅ Recalculating Bounding Box Coordinates: Ensuring accurate localization of detected abnormalities. ✅ Understanding CNN Heatmaps: How convolutional layers output heatmaps that provide spatial feature relevance. ✅ Class Activation Maps (CAMs): The relationship between CNN heatmaps and explainability in AI models. ✅ Connecting It All: How these components integrate into the final detection system for medical imaging. 🚀 Why Watch This Video? Fine-tuning the details of Bounding Boxes, Heatmaps, and CAMs is crucial for building high-performance AI models in healthcare. Master these techniques and take your computer vision skills to the next level! 🔥 Don’t forget to LIKE, COMMENT, and SUBSCRIBE for more cutting-edge AI tutorials! #DeepLearning #CNNModel #ClassActivationMaps #BoundingBoxes #Heatmaps #AIProjects #MedicalAI #MachineLearning #ChestXrayDataset #SupervisedLearning #DataScience #AIInHealthcare #MedicalImaging #HealthcareInnovation #ThoraxDiseaseDetection #ExplainableAI #PythonProgramming #AIForGood #TrainingDeepLearningModels #TensorFlow #Keras #NeuralNetworks