Tootfinder

VRAE: Vertical Residual Autoencoder for License Plate Denoising and Deblurring
Cuong Nguyen, Dung T. Tran, Hong Nguyen, Xuan-Vu Phan, Nam-Phong Nguyen
https://arxiv.org/abs/2509.08392

VRAE: Vertical Residual Autoencoder for License Plate Denoising and Deblurring
In real-world traffic surveillance, vehicle images captured under adverse weather, poor lighting, or high-speed motion often suffer from severe noise and blur. Such degradations significantly reduce the accuracy of license plate recognition systems, especially when the plate occupies only a small region within the full vehicle image. Restoring these degraded images a fast realtime manner is thus a crucial pre-processing step to enhance recognition performance. In this work, we propose a Vertica…

3D Mapping of Defects and Moir\'e Corrugations via Electron Ptychography Atomic Coordinate Retrieval
Jeffrey Huang, Yichao Zhang, Sang hyun Bae, Ballal Ahammed, Elif Ertekin, Pinshane Y. Huang
https://arxiv.org/abs/2509.07140

3D Mapping of Defects and Moiré Corrugations via Electron Ptychography Atomic Coordinate Retrieval
Defects and reconstructions in 2D moiré materials cause out-of-plane deformations which strongly modify their electronic properties but are difficult to experimentally access. Here, we solve the 3D atomic coordinates of twisted bilayer WSe$_2$ with picometer-scale accuracy using multislice electron ptychography (MEP) acquired from a single orientation. The resulting atomic models individually visualize each of the six atomic planes, revealing the curvature of each WSe$_2$ layer, variations in …

The Rosario Dataset v2: Multimodal Dataset for Agricultural Robotics
Nicolas Soncini, Javier Cremona, Erica Vidal, Maximiliano Garc\'ia, Gast\'on Castro, Taih\'u Pire
https://arxiv.org/abs/2508.21635

The Rosario Dataset v2: Multimodal Dataset for Agricultural Robotics
We present a multi-modal dataset collected in a soybean crop field, comprising over two hours of recorded data from sensors such as stereo infrared camera, color camera, accelerometer, gyroscope, magnetometer, GNSS (Single Point Positioning, Real-Time Kinematic and Post-Processed Kinematic), and wheel odometry. This dataset captures key challenges inherent to robotics in agricultural environments, including variations in natural lighting, motion blur, rough terrain, and long, perceptually alias…

An Adaptive Responsible AI Governance Framework for Decentralized Organizations
Kiana Jafari Meimandi, Anka Reuel, Gabriela Aranguiz-Dias, Hatim Rahama, Ala-Eddine Ayadi, Xavier Boullier, J\'er\'emy Verdo, Louis Montanie, Mykel Kochenderfer
https://arxiv.org/abs/2510.03368

An Adaptive Responsible AI Governance Framework for Decentralized Organizations
This paper examines the assessment challenges of Responsible AI (RAI) governance efforts in globally decentralized organizations through a case study collaboration between a leading research university and a multinational enterprise. While there are many proposed frameworks for RAI, their application in complex organizational settings with distributed decision-making authority remains underexplored. Our RAI assessment, conducted across multiple business units and AI use cases, reveals four key …

Investigating Location-Regularised Self-Supervised Feature Learning for Seafloor Visual Imagery
Cailei Liang, Adrian Bodenmann, Emma J Curtis, Samuel Simmons, Kazunori Nagano, Stan Brown, Adam Riese, Blair Thornton
https://arxiv.org/abs/2509.06660

Investigating Location-Regularised Self-Supervised Feature Learning for Seafloor Visual Imagery
High-throughput interpretation of robotically gathered seafloor visual imagery can increase the efficiency of marine monitoring and exploration. Although recent research has suggested that location metadata can enhance self-supervised feature learning (SSL), its benefits across different SSL strategies, models and seafloor image datasets are underexplored. This study evaluates the impact of location-based regularisation on six state-of-the-art SSL frameworks, which include Convolutional Neural …

Good morning from Harlem
#GoodMorningFromHarlem

🔧 Key Features
Character Consistency
Maintains appearance of characters or objects across multiple prompts and edits. Enables placing the same character in different environments, showcasing products from multiple angles, or generating consistent brand assets.
✏️ Targeted Transformations
Precise local edits using natural language commands:
Blur backgrounds
Remove objects or stains
Remove people from photos
Alter poses
Add color to black and whit…

AI for Sustainable Future Foods
Bianca Datta, Markus J. Buehler, Yvonne Chow, Kristina Gligoric, Dan Jurafsky, David L. Kaplan, Rodrigo Ledesma-Amaro, Giorgia Del Missier, Lisa Neidhardt, Karim Pichara, Benjamin Sanchez-Lengeling, Miek Schlangen, Skyler R. St. Pierre, Ilias Tagkopoulos, Anna Thomas, Nicholas J. Watson, Ellen Kuhl
https://a…

AI for Sustainable Future Foods
Global food systems must deliver nutritious and sustainable foods while sharply reducing environmental impact. Yet, food innovation remains slow, empirical, and fragmented. Artificial intelligence (AI) now offers a transformative path with the potential to link molecular composition to functional performance, bridge chemical structure to sensory outcomes, and accelerate cross-disciplinary innovation across the entire production pipeline. Here we outline AI for Food as an emerging discipline tha…

Stacking-Controlled Magnetic Exchange and Magnetoelectric Coupling in Bilayer CrI$_2$
B. Vald\'es-Toro, I. Ferreira-Araya, R. A. Gallardo, J. W. Gonz\'alez
https://arxiv.org/abs/2509.22827

Stacking-Controlled Magnetic Exchange and Magnetoelectric Coupling in Bilayer CrI$_2$
We use a first-principles calculations approach to reveal the electronic and magnetic properties of chromium diiodide (CrI$_2$) bilayers and establish a hierarchy of magnetic interactions across stable registries. The monolayer presents a x-stripe antiferromagnetic ground state, while in bilayers the BA$^\prime$ stacking is the global minimum with antiparallel interlayer magnetic alignment. Bilayer configurations strengthen the exchange in the plane by 6 % to 10 %, while the exchange between la…

CAD2DMD-SET: Synthetic Generation Tool of Digital Measurement Device CAD Model Datasets for fine-tuning Large Vision-Language Models
Jo\~ao Valente, Atabak Dehban, Rodrigo Ventura
https://arxiv.org/abs/2508.21732

CAD2DMD-SET: Synthetic Generation Tool of Digital Measurement Device CAD Model Datasets for fine-tuning Large Vision-Language Models
Recent advancements in Large Vision-Language Models (LVLMs) have demonstrated impressive capabilities across various multimodal tasks. They continue, however, to struggle with trivial scenarios such as reading values from Digital Measurement Devices (DMDs), particularly in real-world conditions involving clutter, occlusions, extreme viewpoints, and motion blur; common in head-mounted cameras and Augmented Reality (AR) applications. Motivated by these limitations, this work introduces CAD2DMD-SE…