Staffing & Scheduling

Enhancing Diffusion Models for High-Quality Image Generation

This report presents the comprehensive implementation, evaluation, and optimization of Denoising Diffusion Probabilistic Models (DDPMs) and Denoising Diffusion Implicit Models (DDIMs), which are state-of-the-art generative models. During inference, these models take random noise as input and iteratively generate high-quality images as output. The study focuses on enhancing their generative capab...

Mobilizing Waldo: Evaluating Multimodal AI for Public Mobilization

Advancements in multimodal Large Language Models (LLMs), such as OpenAI's GPT-4o, offer significant potential for mediating human interactions across various contexts. However, their use in areas such as persuasion, influence, and recruitment raises ethical and security concerns. To evaluate these models ethically in public influence and persuasion scenarios, we developed a prompting strategy us...

Parameter-efficient Fine-tuning for improved Convolutional Baseline for Brain Tumor Segmentation in Sub-Saharan Africa Adult Glioma Dataset

Automating brain tumor segmentation using deep learning methods is an ongoing challenge in medical imaging. Multiple lingering issues exist includin...

T$^3$-S2S: Training-free Triplet Tuning for Sketch to Scene Generation

Scene generation is crucial to many computer graphics applications. Recent advances in generative AI have streamlined sketch-to-image workflows, eas...

BanglishRev: A Large-Scale Bangla-English and Code-mixed Dataset of Product Reviews in E-Commerce

This work presents the BanglishRev Dataset, the largest e-commerce product review dataset to date for reviews written in Bengali, English, a mixture...

An Adaptive Balance Search Based Complementary Heterogeneous Particle Swarm Optimization Architecture

A series of modified cognitive-only particle swarm optimization (PSO) algorithms effectively mitigate premature convergence by constructing distinct...

AI-Driven Health Monitoring of Distributed Computing Architecture: Insights from XGBoost and SHAP

With the rapid development of artificial intelligence technology, its application in the optimization of complex computer systems is becoming more a...

The Impact of Generalization Techniques on the Interplay Among Privacy, Utility, and Fairness in Image Classification

This study investigates the trade-offs between fairness, privacy, and utility in image classification using machine learning (ML). Recent research s...

Towards Physically-Based Sky-Modeling

Accurate environment maps are a key component in rendering photorealistic outdoor scenes with coherent illumination. They enable captivating visual ...

Explicit and Implicit Graduated Optimization in Deep Neural Networks

Graduated optimization is a global optimization technique that is used to minimize a multimodal nonconvex function by smoothing the objective functi...

Grid: Omni Visual Generation

Visual generation has witnessed remarkable progress in single-image tasks, yet extending these capabilities to temporal sequences remains challengin...

A Universal Degradation-based Bridging Technique for Domain Adaptive Semantic Segmentation

Semantic segmentation often suffers from significant performance degradation when the trained network is applied to a different domain. To address t...

Familiarity: Better Evaluation of Zero-Shot Named Entity Recognition by Quantifying Label Shifts in Synthetic Training Data

Zero-shot named entity recognition (NER) is the task of detecting named entities of specific types (such as 'Person' or 'Medicine') without any trai...

Early Detection of At-Risk Students Using Machine Learning

This research presents preliminary work to address the challenge of identifying at-risk students using supervised machine learning and three unique ...

From Bench to Bedside: A Review of Clinical Trials in Drug Discovery and Development

Clinical trials are an indispensable part of the drug development process, bridging the gap between basic research and clinical application. During ...

Empirical Measurements of AI Training Power Demand on a GPU-Accelerated Node

The expansion of artificial intelligence (AI) applications has driven substantial investment in computational infrastructure, especially by cloud co...

PointCFormer: a Relation-based Progressive Feature Extraction Network for Point Cloud Completion

Point cloud completion aims to reconstruct the complete 3D shape from incomplete point clouds, and it is crucial for tasks such as 3D object detecti...

AsyncDSB: Schedule-Asynchronous Diffusion Schrödinger Bridge for Image Inpainting

Image inpainting is an important image generation task, which aims to restore corrupted image from partial visible area. Recently, diffusion Schr\"o...

Research on the Application of Spark Streaming Real-Time Data Analysis System and large language model Intelligent Agents

This study explores the integration of Agent AI with LangGraph to enhance real-time data analysis systems in big data environments. The proposed fra...

Explaining and Mitigating the Modality Gap in Contrastive Multimodal Learning

Multimodal learning has recently gained significant popularity, demonstrating impressive performance across various zero-shot classification tasks a...