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One of the most common problems preventing the application of prediction models in the real world is lack of generalization: The accuracy of models, measured in the benchmark does repeat itself on future data, e.g. in the settings of real…

Computation and Language · Computer Science 2022-10-19 Abdel Aziz Taha , Leonhard Hennig , Petr Knoth

A scattering vector is a local descriptor including multiscale and multi-direction co-occurrence information. It is computed with a cascade of wavelet decompositions and complex modulus. This scattering representation is locally translation…

Computer Vision and Pattern Recognition · Computer Science 2013-11-21 Joan Bruna , Stéphane Mallat

With the development and widespread application of digital image processing technology, image splicing has become a common method of image manipulation, raising numerous security and legal issues. This paper introduces a new splicing image…

Computer Vision and Pattern Recognition · Computer Science 2024-05-20 Ao Xiang , Jingyu Zhang , Qin Yang , Liyang Wang , Yu Cheng

Pattern recognition techniques have been used with increasing success for coping with the tremendous amounts of data being generated by automated surveys. Usually this process involves construction of training sets, the typical examples of…

Astrophysics · Physics 2009-11-11 D. D. Proctor

Diffusion models have emerged from various theoretical and methodological perspectives, each offering unique insights into their underlying principles. In this work, we provide an overview of the most prominent approaches, drawing attention…

Machine Learning · Computer Science 2024-09-04 Solveig Klepper

Digital copiers and printers are widely used nowadays. One of the most important things people care about is copying or printing quality. In order to improve it, we previously came up with an SVM-based classification method to classify…

Computer Vision and Pattern Recognition · Computer Science 2025-04-07 Shaoyuan Xu , Cheng Lu , Mark Shaw , Peter Bauer , Jan P. Allebach

This review provides an overview of the literature on the edge detection methods for pattern recognition that inspire from the understanding of human vision. We note that edge detection is one of the most fundamental process within the low…

Computer Vision and Pattern Recognition · Computer Science 2016-02-16 Alex Pappachen James

Deep learning models extract, before a final classification layer, features or patterns which are key for their unprecedented advantageous performance. However, the process of complex nonlinear feature extraction is not well understood, a…

Computer Vision and Pattern Recognition · Computer Science 2020-06-18 Roozbeh Yousefzadeh , Furong Huang

Sketch segmentation involves grouping pixels within a sketch that belong to the same object or instance. It serves as a valuable tool for sketch editing tasks, such as moving, scaling, or removing specific components. While image…

Computer Vision and Pattern Recognition · Computer Science 2025-05-07 Mia Tang , Yael Vinker , Chuan Yan , Lvmin Zhang , Maneesh Agrawala

Plants are fundamentally important to life. Key research areas in plant science include plant species identification, weed classification using hyper spectral images, monitoring plant health and tracing leaf growth, and the semantic…

Computer Vision and Pattern Recognition · Computer Science 2020-09-15 K. K. Thyagharajan , I. Kiruba Raji

Model selection requires repeatedly evaluating models on a given dataset and measuring their relative performances. In modern applications of machine learning, the models being considered are increasingly more expensive to evaluate and the…

Machine Learning · Computer Science 2020-10-21 Anant Raj , Cameron Musco , Lester Mackey , Nicolo Fusi

Novelty detection is the unsupervised problem of identifying anomalies in test data which significantly differ from the training set. Novelty detection is one of the classic challenges in Machine Learning and a core component of several…

Machine Learning · Computer Science 2019-03-06 Rémi Domingues

While analyzing scanned documents, handwritten text can overlap with printed text. This overlap causes difficulties during the optical character recognition (OCR) and digitization process of documents, and subsequently, hurts downstream NLP…

Computer Vision and Pattern Recognition · Computer Science 2023-08-29 Sina Gholamian , Ali Vahdat

Neural networks for computer vision extract uninterpretable features despite achieving high accuracy on benchmarks. In contrast, humans can explain their predictions using succinct and intuitive descriptions. To incorporate explainability…

Computer Vision and Pattern Recognition · Computer Science 2023-07-04 Khalid Saifullah , Yuxin Wen , Jonas Geiping , Micah Goldblum , Tom Goldstein

A wavelet scattering network computes a translation invariant image representation, which is stable to deformations and preserves high frequency information for classification. It cascades wavelet transform convolutions with non-linear…

Computer Vision and Pattern Recognition · Computer Science 2012-03-09 Joan Bruna , Stéphane Mallat

In this paper, we present a machine learning based architecture for microwave characterization of inkjet printed components on flexible substrates. Our proposed architecture uses several machine learning algorithms and automatically selects…

Machine Learning · Computer Science 2024-04-09 Abhishek Sahu , Peter H. Aaen , Praveen Damacharla

With the current shift in the mass media landscape from journalistic rigor to social media, personalized social media is becoming the new norm. Although the digitalization progress of the media brings many advantages, it also increases the…

Computation and Language · Computer Science 2023-04-18 Ciprian-Octavian Truică , Elena-Simona Apostol

When describing images, humans tend not to talk about the obvious, but rather mention what they find interesting. We argue that abnormalities and deviations from typicalities are among the most important components that form what is worth…

Computer Vision and Pattern Recognition · Computer Science 2014-11-11 Babak Saleh , Ali Farhadi , Ahmed Elgammal

We propose a simple model to analyze the traffic of droplets in microfluidic ``dual networks''. Such functional networks which consist of two types of channels, namely those accessible or forbidden to droplets, often display a complex…

Fluid Dynamics · Physics 2008-01-30 M. Schindler , A. Ajdari

We develop techniques to quantify the degree to which a given (training or testing) example is an outlier in the underlying distribution. We evaluate five methods to score examples in a dataset by how well-represented the examples are, for…

Machine Learning · Computer Science 2019-10-30 Nicholas Carlini , Úlfar Erlingsson , Nicolas Papernot