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Last year, multimodal architectures served up a revolution in AI-based approaches and solutions, extending the capabilities of large language models (LLM). We propose an \textit{OmniFusion} model based on a pretrained LLM and adapters for…

CellProfiler is a widely used software for creating reproducible, reusable image analysis workflows without needing to code. In addition to the >90 modules that make up the main CellProfiler program, CellProfiler has a plugins system that…

We describe some progress towards a new common framework for model driven engineering, based on behavioral programming. The tool we have developed unifies almost all of the work done in behavioral programming so far, under a common set of…

Deep learning has achieved great success in a wide spectrum of multimedia applications such as image classification, natural language processing and multimodal data analysis. Recent years have seen the development of many deep learning…

Simulations with high accuracy are an essential part of scientific research to accelerate the innovation process. They are especially useful for finding novel approaches or optimizing existing methods. Today, powerful software tools are…

A major bottleneck of interdisciplinary computer vision (CV) research is the lack of a framework that eases the reuse and abstraction of state-of-the-art CV models by CV and non-CV researchers alike. We present here BU-CVKit, a computer…

Multi-modal image fusion (MMIF) integrates valuable information from different modality images into a fused one. However, the fusion of multiple visible images with different focal regions and infrared images is a unprecedented challenge in…

Multimodal semantic segmentation shows significant potential for enhancing segmentation accuracy in complex scenes. However, current methods often incorporate specialized feature fusion modules tailored to specific modalities, thereby…

Single image super-resolution(SISR) has witnessed great progress as convolutional neural network(CNN) gets deeper and wider. However, enormous parameters hinder its application to real world problems. In this letter, We propose a…

This thesis focuses on the intersection of mathematical and computational optimization and quantum information. Main contributions are open-source software code: A hybrid approach mixing "traditional" nonconvex and convex methods can make…

Equipping query processing systems with provable theoretical guarantees has been a central focus at the intersection of database theory and systems in recent years. However, the divergence between theoretical abstractions and system…

The increasingly popular light sheet microscopy techniques generate very large 3D time-lapse recordings of living biological specimen. The necessity to make large volumetric datasets available for interactive visualization and analysis has…

Particle image velocimetry (PIV) and related optical-flow methods are widely used to quantify fluid motion, but their development and evaluation are often hindered by fragmented software, inconsistent interfaces, and limited…

Consistency and reliability are crucial for conducting AI research. Many famous research fields, such as object detection, have been compared and validated with solid benchmark frameworks. After AlphaFold2, the protein folding task has…

Organizations are starting to realize of the combined power of data and data-driven algorithmic models to gain insights, situational awareness, and advance their mission. A common challenge to gaining insights is connecting inherently…

Federated learning (FL) has been widely adopted across various applications, such as healthcare, finance, and smart cities. However, as experimental scenarios become more complex, existing FL frameworks and benchmarks have struggled to keep…

Critical goals of scientific computing are to increase scientific rigor, reproducibility, and transparency while keeping up with ever-increasing computational demands. This work presents an integrated framework well-suited for data…

Unified image fusion aims to integrate complementary information from multi-source images, enhancing image quality through a unified framework applicable to diverse fusion tasks. While treating all fusion tasks as a unified problem…

Many interesting phenomena are characterized by the complex interaction of different physical processes, each often best modeled numerically via a specific approach. In this paper, we present the design and implementation of an…

Multi-object multi-part scene segmentation is a challenging task whose complexity scales exponentially with part granularity and number of scene objects. To address the task, we propose a plug-and-play approach termed OLAF. First, we…