Deep Learning

In the evolving landscape of psycholinguistics, language models (LMs) have carved out a pivotal role, serving as both the subject and tool of study. These models, leveraging vast datasets, attempt to mimic human language processing capabilities,...
The surge of advertisements across online platforms presents a formidable challenge in maintaining content integrity and adherence to advertising policies. While foundational, traditional mechanisms of content moderation grapple with the dual challenges of scale and efficiency,...

This AI Paper Explains the Effect of Data Augmentation on Deep-Learning-based Segmentation of Long-Axis Cine-MRI

Cardiac Magnetic Resonance Imaging (CMRI) segmentation plays a crucial role in diagnosing cardiovascular diseases, particularly ischemic heart conditions, which are a leading cause of...

Revolutionizing Cancer Diagnosis: How Deep Learning Predicts Continuous Biomarkers with Unprecedented Accuracy

Digital pathology involves analyzing tissue specimens, often whole slide images (WSI), to predict genetic biomarkers for accurate tumor diagnosis. Deep learning models process WSI...

Meet Hawkeye: A Unified Deep Learning-based Fine-Grained Image Recognition Toolbox Built on PyTorch

In recent years, notable advancements in the design and training of deep learning models have led to significant improvements in image recognition performance, particularly...

This AI Paper Introduces PirateNets: A Novel AI System Designed to Facilitate Stable and Efficient Training of Deep Physics-Informed Neural Network Models

With the world of computational science continually evolving, physics-informed neural networks (PINNs) stand out as a groundbreaking approach for tackling forward and inverse problems...

Researchers from the University of Washington Developed a Deep Learning Method for Protein Sequence Design that Explicitly Models the Full Non-Protein Atomic Context

A team of researchers from the University of Washington has collaborated to address the challenges in the protein sequence design method by using a...

This AI Paper Explains the Deep Learning’s Revolutionizing Role in Mapping Genotypic Fitness Landscapes

Fitness landscapes, a concept in evolutionary biology, represent how genetic variations influence an organism's survival and reproductive success. They are formed by mapping genotypes...

This AI Paper from UCLA Revolutionizes Uncertainty Quantification in Deep Neural Networks Using Cycle Consistency

With the growth of Deep learning, it is used in many fields, including data mining and natural language processing. It is also widely used...

This 200-Page AI Report Covers Vector Retrieval: Unveiling the Secrets of Deep Learning and Neural Networks in Multimodal Data Management

Artificial Intelligence has witnessed a revolution, largely due to advancements in deep learning. This shift is driven by neural networks that learn through self-supervision,...

Balancing Privacy and Performance: This Paper Introduces a Dual-Stage Deep Learning Framework for Privacy-Preserving Re-Identification

Person Re-identification (Person Re-ID) in Machine Learning uses deep learning models like convolutional neural networks to recognize and track individuals across different camera views,...

Meet MedGAN: A Deep Learning Model based on Wasserstein Generative Adversarial Networks and Graph Convolutional Networks for Novel Molecule Design

The growing urgency for innovative drugs in various medical fields, such as antibiotics, cancer treatments, autoimmune disorders, and antiviral therapies, underscores the need for...

Decoding Human Risky Choices: Unveiling Dataset Bias in Decision-Making Models Using Machine Learning

In understanding choices, there are two main models: normative and descriptive. Normative models explain why people should make certain decisions based on principles, while...

This Paper Explores the Application of Deep Learning in Blind Motion Deblurring: A Comprehensive Review and Future Prospects

When the camera and the subject move about one another during the exposure, the result is a typical artifact known as motion blur. Computer...

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