Staffing & Scheduling

DrugPTM-Bench: A Large-Scale Dataset for Predictive Modeling of Drug-Induced Cell Type-Specific Protein Post-Translational Modifications

Protein post-translational modifications (PTMs), particularly phosphorylation, serve as the primary molecular switches that orchestrate cellular signaling and drug response. While PTM dysregulation is a hallmark of cancer and neurodegeneration, the lack of standardized, drug-perturbed datasets has hindered the development of predictive models capable of capturing context-dependent PTM responses. E...

VibroML: an automated toolkit for high-throughput vibrational analysis and dynamic instability remediation of crystalline materials using machine-learned potentials

While machine-learned interatomic potentials (MLIPs) accelerate phonon dispersion calculations, merely identifying dynamical instabilities in computationally predicted materials is insufficient; automated pathways to resolve them are required. We introduce VibroML, an open-source Python toolkit driven by foundational MLIPs that shifts the paradigm from stability verification to automated structura...

Why Domain Matters: A Preliminary Study of Domain Effects in Underwater Object Detection

Domain shift, where deviations between training and deployment data distributions degrade model performance, is a key challenge in underwater environm...

CA-IDD: Cross-Attention Guided Identity-Conditional Diffusion for Identity-Consistent Face Swapping

Face swapping aims to optimize realistic facial image generation by leveraging the identity of a source face onto a target face while preserving pose,...

Empirical Ablation and Ensemble Optimization of a Convolutional Neural Network for CIFAR-10 Classification

Convolutional neural networks (CNNs) remain a central approach in image classification, but their performance depends strongly on architectural and tr...

Mammographic Lesion Segmentation with Lightweight Models: A Comparative Study

Breast cancer is a leading cause of cancer-related mortality among women worldwide, with mammography as the primary screening tool. While deep learnin...

Region Matters: Efficient and Reliable Region-Aware Visual Place Recognition

Visual Place Recognition (VPR) determines a query image's geographic location by matching it against geotagged databases. However, existing methods st...

Integrating Metabolic Networks into Hybrid Bioprocess Models

The optimization and control of bioprocesses require robust in silico models that can accurately capture the complex and dynamic behavior of living ce...

FLARE-BO: Fused Luminance and Adaptive Retinex Enhancement via Bayesian Optimisation for Low-Light Robotic Vision

Reliable visual perception under low illumination remains a core challenge for autonomous robotic systems, where degraded image quality directly compr...

Ramen: Robust Test-Time Adaptation of Vision-Language Models with Active Sample Selection

Pretrained vision-language models such as CLIP exhibit strong zero-shot generalization but remain sensitive to distribution shifts. Test-time adaptati...

Bridging the Training-Deployment Gap: Gated Encoding and Multi-Scale Refinement for Efficient Quantization-Aware Image Enhancement

Image enhancement models for mobile devices often struggle to balance high output quality with the fast processing speeds required by mobile hardware....

Directional Confusions Reveal Divergent Inductive Biases Through Rate-Distortion Geometry in Human and Machine Vision

Humans and modern vision models can reach similar classification accuracy while making systematically different kinds of mistakes - differing not in h...

PanGuide3D: Cohort-Robust Pancreas Tumor Segmentation via Probabilistic Pancreas Conditioning and a Transformer Bottleneck

Pancreatic tumor segmentation in contrast-enhanced computed tomography (CT) is clinically important yet technically challenging: lesions are often sma...

Generative Drifting for Conditional Medical Image Generation

Conditional medical image generation plays an important role in many clinically relevant imaging tasks. However, existing methods still face a fundame...

Deep learning based Non-Rigid Volume-to-Surface Registration for Brain Shift compensation Using Point Cloud

Soft-tissue deformation remains a major limitation in image-guided neurosurgery, where intra-operative anatomy can deviate substantially from pre-oper...

Speculative Decoding for Autoregressive Video Generation

Autoregressive video diffusion is emerging as a promising paradigm for streaming video synthesis, with step distillation serving as the primary means ...

STEP-PD: Stage-Aware and Explainable Parkinson's Disease Severity Classification Using Multimodal Clinical Assessments

Parkinson's disease (PD) is a progressive disorder in which symptom burden and functional impairment evolve over time, making severity staging essenti...

SSMamba: A Self-Supervised Hybrid State Space Model for Pathological Image Classification

Pathological diagnosis is highly reliant on image analysis, where Regions of Interest (ROIs) serve as the primary basis for diagnostic evidence, while...

UA-Net: Uncertainty-Aware Network for TRISO Image Semantic Segmentation

Tristructural isotropic (TRISO)-coated particle fuels undergo dimensional changes and chemical reactions during high-temperature neutron irradiation. ...

π-MSNet: A billion-scale, AI-ready living proteomics data portal

Artificial intelligence (AI) is reshaping proteomics workflows, delivering remarkable gains in both peptide identification sensitivity and quantitativ...