Data Integration, Data Scarcity and Explainability

Deep Learning Techniques for Autonomous Driving: An Overview

Marktechpost

MAY 8, 2024

Conclusion: In the realm of autonomous driving, several open challenges persist, all of which can be addressed with the help of Deep Learning and AI: Perception: Deep learning enhances object detection and recognition accuracy, but future systems should aim for increased detail recognition and improved camera and LiDAR data integration.

Deep Learning

Deep Learning Neural Network Data Scarcity Natural Language Processing

Deep Learning for Medical Image Analysis: Current Trends and Future Directions

Heartbeat

NOVEMBER 27, 2023

Fine-tuning, a process where pre-trained models are further trained on task-specific data, allows the model to adapt and refine its representations to the specific medical imaging domain. Interpretability and Explainability One challenge with deep learning models in medical image analysis is their black-box nature.

Deep Learning

Deep Learning Convolutional Neural Networks Explainability Neural Network

Artificial Intelligence Zone

Deep Learning Techniques for Autonomous Driving: An Overview

Deep Learning for Medical Image Analysis: Current Trends and Future Directions

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