Academic Articles & Research Papers

Camera Calibration in High-Speed Robotic Assembly Operations

The increase in positioning accuracy and repeatability allowed the integration of robots in assembly operations using guidance systems (structured applications) or video acquisition systems (unstructured applications). This paper proposes a...

TRust Your GENerator (TRYGEN): Enhancing Out-of-Model Scope Detection

Recent research has drawn attention to the ambiguity surrounding the definition and learnability of Out-of-Distribution recognition. Although the original problem remains unsolved, the term “Out-of-Model Scope” detection offers a clearer pe...

Vehicle Ego-Trajectory Segmentation Using Guidance Cues

Computer vision has significantly influenced recent advancements in autonomous driving by providing cutting-edge solutions for various challenges, including object detection, semantic segmentation, and comprehensive scene understanding. One...

Structured Learning and Prediction in Computer Vision

Powerful statistical models that can be learned efficiently from large amounts of data are currently revolutionizing computer vision. These models possess a rich internal structure reflecting task-specific relations and constraints. This mo...

Aphid-ResNetSwin: An Image Recognition Method with Improved Attention Mechanism for Graded Identification of <i>Myzus persicae</i>

Myzus persicae is the most devastating piercing-sucking pest threatening tobacco production. Precise quantification of infestation severity is a prerequisite for precision pest management, making the integration of visual image analysis hig...

Does manufacturing specialization matter? Transfer accuracy of static surgical guides produced by general-purpose and dental-specific additive workflows: A paired in vitro study.

Part‐level attention networks for cross‐domain person re‐identification

Abstract Person re‐identification (Re‐ID) is in significant demand for intelligent security and single or multiple‐target tracking. However, there are issues in the person Re‐ID tasks, such as sharp decline in cross‐data sets detection accu...

Generalizable stereo depth estimation with masked image modelling

Abstract Generalizable and accurate stereo depth estimation is vital for 3D reconstruction, especially in surgery. Supervised learning methods obtain best performance however, limited ground truth data for surgical scenes limits generalizab...

Deep learning classification for macrophage subtypes through cell migratory pattern analysis

Macrophages can exhibit pro-inflammatory or pro-reparatory functions, contingent upon their specific activation state. This dynamic behavior empowers macrophages to engage in immune reactions and contribute to tissue homeostasis. Understand...

(Computer) vision without sight

Computer vision holds great promise for helping persons with blindness or visual impairments (VI) to interpret and explore the visual world. To this end, it is worthwhile to assess the situation critically by understanding the actual needs ...

AI and Chatbot-Supported Interventions for Physical Activity and Obesity-Related Lifestyle Behaviors: Scoping Review With Attention to Family Involvement

Abstract BackgroundAI-enabled chatbots and related conversational systems can facilitate human–computer interaction through natural language, personalization, and automated support. In pediatric health promotion, these tools hav...

Euclid Quick Data Release (Q1)

Strong gravitational lensing (SL) by galaxy clusters is a powerful probe of their inner mass distribution and a key test bed for cosmological models. However, the detection of SL events in wide-field surveys such as Euclid requires robust a...

A guided tour of computer vision

An introduction to computer vision, covering the structure and properties of the visual world. This concise guide stresses fundamental concepts, and also provides details and pointers with respect to recent developments. The author pursues ...

A Guide to Convolutional Neural Networks for Computer Vision

Applying Neural Networks: A Practical Guide

Techniques for building neural networks: introduction what are neural networks? how does neural computing differ from traditional programming? how are neural networks built? how do neural networks learn? what do I need to build an MLP? the ...

Incorporating structural plasticity into self-organization recurrent networks for sequence learning

IntroductionSpiking neural networks (SNNs), inspired by biological neural networks, have received a surge of interest due to its temporal encoding. Biological neural networks are driven by multiple plasticities, including spike timing-depen...

Overcoming catastrophic forgetting in neural networks

The ability to learn tasks in a sequential fashion is crucial to the development of artificial intelligence. Until now neural networks have not been capable of this and it has been widely thought that catastrophic forgetting is an inevitabl...

The transcription factor SoxD controls neuronal guidance in the Drosophila visual system

Abstract Precise control of neurite guidance during development is essential to ensure proper formation of neuronal networks and correct function of the central nervous system (CNS). How neuronal projections find their targets to generate a...

Practical neural network recipes in C

This text serves as a cookbook for neural network solutions to practical problems using C++. It will enable those with moderate programming experience to select a neural network model appropriate to solving a particular problem, and to prod...

Shear banding and flow instabilities in wormlike micelles: Modelling and mechanisms – A review

Worm-like micelles (WLMs) are dynamic, self-assembling supramolecular structures that exhibit complex viscoelastic behaviour due to their ability to undergo reversible scission, fusion, branching, and sequence rearrangement. This review pro...