Deep Learning

Deep learning, a subfield of machine learning, focuses on training artificial neural networks with multiple layers to extract complex patterns from data. Current research emphasizes improving model robustness against noisy or adversarial inputs, exploring efficient architectures like Vision Transformers and convolutional LSTMs for various tasks (e.g., image classification, time series forecasting), and integrating physics-informed approaches for enhanced interpretability and reliability. These advancements are significantly impacting diverse fields, from automated industrial inspection and medical image analysis to improved weather forecasting and more efficient content moderation systems.

Papers

September 29, 2024

September 28, 2024

Toward Deep Learning-based Segmentation and Quantitative Analysis of Cervical Spinal Cord Magnetic Resonance Images
Maryam Tavakol Elahi (The University of Ottawa)
Deep Learning Medical Image Analysis Quantitative Analysis Deep Learning Based Medical Spinal X Ray Microstructure Segmentation Spinal Cord

September 27, 2024

September 26, 2024

September 25, 2024

Deep Learning

Papers

Efficient Quality Control of Whole Slide Pathology Images with Human-in-the-loop Training

Finetuning YOLOv9 for Vehicle Detection: Deep Learning for Intelligent Transportation Systems in Dhaka, Bangladesh

Toward Deep Learning-based Segmentation and Quantitative Analysis of Cervical Spinal Cord Magnetic Resonance Images

Differential privacy enables fair and accurate AI-based analysis of speech disorders while protecting patient data

State-of-the-Art Periorbital Distance Prediction and Disease Classification Using Periorbital Features

Enhancing Crime Scene Investigations through Virtual Reality and Deep Learning Techniques

A Survey on Neural Architecture Search Based on Reinforcement Learning

Predicting Anchored Text from Translation Memories for Machine Translation Using Deep Learning Methods

Intelligent Energy Management: Remaining Useful Life Prediction and Charging Automation System Comprised of Deep Learning and the Internet of Things

DREAMS: A python framework to train deep learning models with model card reporting for medical and health applications

Predicting the Stay Length of Patients in Hospitals using Convolutional Gated Recurrent Deep Learning Model

An Integrated Deep Learning Framework for Effective Brain Tumor Localization, Segmentation, and Classification from Magnetic Resonance Images

Classification of Gleason Grading in Prostate Cancer Histopathology Images Using Deep Learning Techniques: YOLO, Vision Transformers, and Vision Mamba

Deep Learning and Machine Learning, Advancing Big Data Analytics and Management: Handy Appetizer

Efficient Feature Interactions with Transformers: Improving User Spending Propensity Predictions in Gaming

Informed deep hierarchical classification: a non-standard analysis inspired approach

A parametric framework for kernel-based dynamic mode decomposition using deep learning

Let There Be Light: Robust Lensless Imaging Under External Illumination With Deep Learning

The Effect of Lossy Compression on 3D Medical Images Segmentation with Deep Learning

Ascend HiFloat8 Format for Deep Learning