Tootfinder

Pothole Detection and Recognition based on Transfer Learning
Mang Hu, Qianqian Xia
https://arxiv.org/abs/2509.06750 https://arxiv.org/pdf/2509.06750…

Pothole Detection and Recognition based on Transfer Learning
With the rapid development of computer vision and machine learning, automated methods for pothole detection and recognition based on image and video data have received significant attention. It is of great significance for social development to conduct an in-depth analysis of road images through feature extraction, thereby achieving automatic identification of the pothole condition in new images. Consequently, this is the main issue addressed in this study. Based on preprocessing techniques suc…

High-Resolution Sustain Pedal Depth Estimation from Piano Audio Across Room Acoustics
Kun Fang, Hanwen Zhang, Ziyu Wang, Ichiro Fujinaga
https://arxiv.org/abs/2507.04230

High-Resolution Sustain Pedal Depth Estimation from Piano Audio Across Room Acoustics
Piano sustain pedal detection has previously been approached as a binary on/off classification task, limiting its application in real-world piano performance scenarios where pedal depth significantly influences musical expression. This paper presents a novel approach for high-resolution estimation that predicts continuous pedal depth values. We introduce a Transformer-based architecture that not only matches state-of-the-art performance on the traditional binary classification task but also ach…

A Spatial Gap in the Sky Distribution of Fast Radio Burst Detections Coinciding with Galactic Plasma Overdensities
Swarali Shivraj Patil, Robert A. Main, Emmanuel Fonseca, Kyle McGregor, B. M. Gaensler, Charanjot Brar, Amanda M. Cook, Alice P. Curtin, Gwendolyn Eadie, Ronniy Joseph, Lordrick Kahinga, Victoria Kaspi, Afrokk Khan, Bikash Kharel, Adam E. Lanman, Calvin Leung, Kiyoshi W. Masui, Mason Ng, Kenzie Nimmo, Ayush Pandhi, Aaron B. Pearlman, Ziggy Pleunis, Mawson W. Sammons, Ketan…

A Spatial Gap in the Sky Distribution of Fast Radio Burst Detections Coinciding with Galactic Plasma Overdensities
We analyze the positional and morphological properties of about 3600 unique fast radio burst (FRB) sources reported in the second FRB catalog generated by the Canadian Hydrogen Intensity Mapping Experiment (CHIME) telescope. We find a two-dimensional dependence of FRB detections on sky position, and identify a significant absence of detections in a roughly circular region centered at Galactic coordinates (77.7$^\circ$, 0.9$^\circ$), spanning an area of 216.2 deg$^2$. This detection gap spatiall…

Optimal Young's convolutions inequality and its reverse form on the hypercube
David Beltran, Paata Ivanisvili, Jos\'e Madrid, Lekha Patil
https://arxiv.org/abs/2507.06115 …

Optimal Young's convolutions inequality and its reverse form on the hypercube
We establish sharp forms of Young's convolution inequality and its reverse on the discrete hypercube $\{0,1\}^d$ in the diagonal case $p=q$. As applications, we derive bounds for additive energies and sumsets. We also investigate the non-diagonal regime $p\neq q$, providing necessary conditions for the inequality to hold, along with partial results in the case $r = 2$.

The Shape of AGN-Driven Winds in the Seyfert Galaxy NGC 3516
Jacob Tutterow, Nicholas Ferree, D. Michael Crenshaw, Julia Falcone, Maura Kathleen Shea, Travis C. Fischer, Beena Meena, Mitchell Revalski, Kesha Patel, Madeline Davis
https://arxiv.org/abs/2509.06476

The Shape of AGN-Driven Winds in the Seyfert Galaxy NGC 3516
Active galactic nuclei (AGN) are known to drive ionized gas into their host galaxies, which may affect the evolution of both the central supermassive black holes and their hosts. In the case of NGC 3516, a nearby Seyfert 1 galaxy, these AGN winds have historically proven difficult to disentangle from galactic rotation. Using long slit spectroscopy at multiple position angles from the Hubble Space Telescope Space Telescope Imaging Spectrograph and the Apache Point Observatory Kitt Peak Ohio Stat…

"This Suits You the Best": Query Focused Comparative Explainable Summarization
Arnav Attri, Anuj Attri, Pushpak Bhattacharyya, Suman Banerjee, Amey Patil, Muthusamy Chelliah, Nikesh Garera
https://arxiv.org/abs/2507.04733

"This Suits You the Best": Query Focused Comparative Explainable Summarization
Product recommendations inherently involve comparisons, yet traditional opinion summarization often fails to provide holistic comparative insights. We propose the novel task of generating Query-Focused Comparative Explainable Summaries (QF-CES) using Multi-Source Opinion Summarization (M-OS). To address the lack of query-focused recommendation datasets, we introduce MS-Q2P, comprising 7,500 queries mapped to 22,500 recommended products with metadata. We leverage Large Language Models (LLMs) to …

Covariant Carrollian Electric and Magnetic Limits of General Relativity
Tanmay Patil (IIT Bombay), S. Shankaranarayanan (IIT Bombay)
https://arxiv.org/abs/2509.07601 https://

Covariant Carrollian Electric and Magnetic Limits of General Relativity
The Carrollian limit ($c \to 0$) of General Relativity provides the geometric language for describing null hypersurfaces, such as black hole event horizons and null infinity. Motivated by the well-established electric and magnetic limits of Galilean electromagnetism, we perform a systematic analysis of the low-velocity limit of linearized gravity to derive its Carrollian counterparts. Using a 1+3 covariant decomposition, we study the transformation properties of linear tensor perturbations (gra…

The spectrum of the Steklov-Helmholtz operator
Nilima Nigam, Kshitij Patil, Weiran Sun
https://arxiv.org/abs/2509.07249 https://arxiv.org/pdf/2509.07249

The spectrum of the Steklov-Helmholtz operator
We present a wavenumber-robust strategy for computing Steklov eigenpairs of the Helmholtz operator $-Δ-μ^2$. As the wavenumber $μ\rightarrow μ_D$ from below (where $μ_D^2 $ is a Dirichlet- Laplace eigenvalue of multiplicity $\ell$), the lowest $\ell$ Steklov-Helmholtz eigenvalues diverge to $-\infty$. Computationally, the Steklov-Helmholtz eigenvalue problem becomes severely ill-conditioned when $μ\approx μ_D$. We first reformulate the problem in terms of a suitably-defined Dirichlet-t…

Design and Implementation of an OCR-Powered Pipeline for Table Extraction from Invoices
Parshva Dhilankumar Patel
https://arxiv.org/abs/2507.07029 https://…

Design and Implementation of an OCR-Powered Pipeline for Table Extraction from Invoices
This paper presents the design and development of an OCR-powered pipeline for efficient table extraction from invoices. The system leverages Tesseract OCR for text recognition and custom post-processing logic to detect, align, and extract structured tabular data from scanned invoice documents. Our approach includes dynamic preprocessing, table boundary detection, and row-column mapping, optimized for noisy and non-standard invoice formats. The resulting pipeline significantly improves data extr…

Repeating vs. Non-Repeating FRBs: A Deep Learning Approach To Morphological Characterization
Bikash Kharel, Emmanuel Fonseca, Charanjot Brar, Afrokk Khan, Lluis Mas-Ribas, Swarali Shivraj Patil, Paul Scholz, Seth Robert Siegel, David C. Stenning
https://arxiv.org/abs/2509.06208

Repeating vs. Non-Repeating FRBs: A Deep Learning Approach To Morphological Characterization
We present a deep learning approach to classify fast radio bursts (FRBs) based purely on morphology as encoded on recorded dynamic spectrum from CHIME/FRB Catalog 2. We implemented transfer learning with a pretrained ConvNext architecture, exploiting its powerful feature extraction ability. ConvNext was adapted to classify dedispersed dynamic spectra (which we treat as images) of the FRBs into one of the two sub-classes, i.e., repeater and non-repeater, based on their various temporal and spect…