Search Results for author:
Found 12 papers, 5 papers with code
Can LLMs substitute SQL? Comparing Resource Utilization of Querying LLMs versus Traditional Relational Databases
Large Language Models (LLMs) can automate or substitute different types of tasks in the software engineering process.
Augmenting Vision-Based Human Pose Estimation with Rotation Matrix
Fitness applications are commonly used to monitor activities within the gym, but they often fail to automatically track indoor activities inside the gym.
A Survey of AI Music Generation Tools and Models
In this work, we provide a comprehensive survey of AI music generation tools, including both research projects and commercialized applications.
Beta-Rank: A Robust Convolutional Filter Pruning Method For Imbalanced Medical Image Analysis
We demonstrated that our model performed significantly better than other methods for imbalanced medical datasets.
Ranked #1 on
Medical Image Classification
on IDRiD
LightDepth: A Resource Efficient Depth Estimation Approach for Dealing with Ground Truth Sparsity via Curriculum Learning
Our approach devises model-agnostic curriculum-based learning for depth estimation.
Ranked #1 on
Depth Estimation
on KITTI Eigen split
Speeding Up Question Answering Task of Language Models via Inverted Index
Natural language processing applications, such as conversational agents and their question-answering capabilities, are widely used in the real world.
ODSearch: Fast and Resource Efficient On-device Natural Language Search for Fitness Trackers' Data
Mobile and wearable technologies have promised significant changes to the healthcare industry.
FEDZIP: A Compression Framework for Communication-Efficient Federated Learning
Next, clients transfer local updates of model weights and biases (training data) to a server.
SEFR: A Fast Linear-Time Classifier for Ultra-Low Power Devices
A fundamental challenge for running machine learning algorithms on battery-powered devices is the time and energy limitations, as these devices have constraints on resources.
CovidCTNet: An Open-Source Deep Learning Approach to Identify Covid-19 Using CT Image
In order to facilitate the detection of Covid-19 globally and assist radiologists and physicians in the screening process, we are releasing all algorithms and parametric details in an open-source format.
Ranked #1 on
COVID-19 Diagnosis
on
A Natural Language Query Interface for Searching Personal Information on Smartwatches
Through analyzing these questions, we have constructed a light-weight natural language based query interface, including a text parser algorithm and a user interface, to process the users' queries that have been used for searching quantified-self information.
Learning Mobile App Usage Routine through Learning Automata
Since its conception, smart app market has grown exponentially.
