point clouddeep learningcompressionscene understandingsemantic segmentationcompletionRecent advancements in self-driving cars, robotics, and remote sensing have widened the range of applications for 3D Point Cloud (PC) data. This data format poses several new issues concerning noise levels, sparsit...
Deep Learning Breakthroughs in deep learning algorithms, enabling AI to learn from complex data, and make decisions with human-like accuracy. Applications in computer vision, NLP, and more. Edge AI and Systems Edge AI enables real-time processing, reducing latency, and increasing efficiency. Autonom...
Advances in deep learning architectures Hybrid neural network models Neural networks in computer vision, NLP, and other specialized domains Techniques for improving efficiency, scalability, and interpretability Ethical considerations and emerging challenges in neural network applications Target Audience: This boo...
One are a where AI is making a profound impact is the medical field, particularly in the domain of diagnostics.AI-powered diagnostic systems leverage deep learning algorithms to analyze medical images, such as X-rays,MRIs, and CT scans. These algorithms can detect subtle patterns and anomalies ...
systems, are adapted to ensure the integrity and confidentiality of imaging data transmission, mitigating the risks of cyberattacks. On the other hand, AI plays a crucial role in CYSTDA by providing advanced threat detection techniques using deep learning models such as neural networks, enabling ...
2.2. Deep Learning Deep learning is a significant branch of machine learning and is currently one of the most widely applied technologies in artificial intelligence. Its core idea is to establish deep neural network models and utilize backpropagation algorithms to fit data models, enabling neural net...
Differentially private stochastic gradient descent (SGD) algorithms provide formal privacy guarantees for training ML models, offering better protection against practical attacks. Researchers estimate protection levels using ε confidence intervals from membership inference attacks, but obtaining...
This solved the challenges of on-orbit printing and in-situ culture of tumor model samples. Additionally, they proposed a dual-color fluorescence microscopy space in-situ automatic imaging technology based on deep learning algorithms and designed a software system for automatic telemetry, control, and...
Existing Research Algorithms Performance Sun et al. sun2020deepdom DeepWalk, Metapath2Vec, GraphSAGE and SHetGCN Accuracy: - 97% Ngejane et al. ngejane2021digital LR, XGBoost, MLP & BiLSTM Accuracy:- 98 F1 Score :- 70% Wazirali et al. wazirali2021sustaining Feature Selection CNN (FS-CN...
In the fields of reinforcement learning and robotics, NVIDIA researchers will present two posters highlighting innovations that improve the generalizability of AI across different tasks and environments. The first proposes aframework for developing reinforcement learning algorithmsthat can adapt to new tasks...