Remove AI Research Remove Computer Vision Remove Deep Learning
article thumbnail

Researchers from the University of Oxford Developed a Deep Learning-Based Software for Precision Tracking of Fish Movement in Complex Environments

Marktechpost

Addressing these challenges, a UK-based research team introduced a hybrid method, merging deep learning and traditional computer vision techniques to enhance tracking accuracy for fish in complex experiments. The deep learning part involves the use of object detection and tracking.

article thumbnail

AI trends in 2023: Graph Neural Networks

AssemblyAI

What is the current role of GNNs in the broader AI research landscape? Let’s take a look at some numbers revealing how GNNs have seen a spectacular rise within the research community. We find that the term Graph Neural Network consistently ranked in the top 3 keywords year over year.

professionals

Sign Up for our Newsletter

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

article thumbnail

UCLA Researchers Propose PhyCV: A Physics-Inspired Computer Vision Python Library

Marktechpost

Artificial intelligence is making noteworthy strides in the field of computer vision. One key area of development is deep learning, where neural networks are trained on huge datasets of images to recognize and classify objects, scenes, and events. All Credit For This Research Goes To the Researchers on This Project.

article thumbnail

How to Visualize Deep Learning Models

The MLOps Blog

Deep learning models are typically highly complex. While many traditional machine learning models make do with just a couple of hundreds of parameters, deep learning models have millions or billions of parameters. The reasons for this range from wrongly connected model components to misconfigured optimizers.

article thumbnail

Microsoft Releases GRIN MoE: A Gradient-Informed Mixture of Experts MoE Model for Efficient and Scalable Deep Learning

Marktechpost

Artificial intelligence (AI) research has increasingly focused on enhancing the efficiency & scalability of deep learning models. These models have revolutionized natural language processing, computer vision, and data analytics but have significant computational challenges.

article thumbnail

Amazon Researchers Present a Deep Learning Compiler for Training Consisting of Three Main Features- a Syncfree Optimizer, Compiler Caching, and Multi-Threaded Execution

Marktechpost

The idea of compilation is a potentially effective remedy that can balance the needs for computing efficiency and model size. In recent research, a team of researchers has introduced a deep learning compiler specifically made for neural network training.

article thumbnail

A New AI Research Proposes VanillaNet: A Novel Neural Network Architecture Emphasizing the Elegance and Simplicity of Design while Retaining Remarkable Performance in Computer Vision Tasks

Marktechpost

ResNet expands on this achievement by including identity mappings through shortcut connections, enabling the training of deep neural networks with good performance across various computer vision applications, including image classification, object identification, and semantic segmentation.